UNITED STATES OF AMERICA

	DEPARTMENT OF HEALTH AND HUMAN SERVICES

	PUBLIC HEALTH SERVICE

	FOOD AND DRUG ADMINISTRATION

	CENTER FOR DRUG EVALUATION AND RESEARCH

	ANTIVIRAL DRUGS ADVISORY COMMITTEE

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	MEETING

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	THURSDAY,

	JANUARY 11, 2001

		The meeting was held at 8:30 a.m. in the Versailles Rooms I, II, and III of the Bethesda Holiday Inn, 8120 Wisconsin Avenue, Bethesda, Maryland, DR. ROY M. GULICK, Acting Chair, presiding.
PRESENT:

	ROY M. GULICK, M.D., M.P.H., Acting Chair
	COURTNEY V. FLETCHER, Pharm.D.
	PRINCY KUMAR, M.D.
	WILLIAM CHRISTOPHER MATHEWS, M.D., M.S.P.H.
	ROGER J. POMERANTZ, M.D.
	SHARILYN K. STANLEY, M.D.
	BRIAN WONG, M.D.

	TARA P. TURNER, Pharm.D.
	Executive Secretary

CONSULTANTS PRESENT (voting):

	WILLIAM BLACKWELDER, Ph.D.
	MICHAEL SAAG, M.D.

PATIENT REPRESENTATIVES (non-voting):

	LYNDA DEE, Patient Representative
	YVETTE DELPH, M.D., Patient Representative
	RALPH DeMASI, Ph.D., Industry Guest
	JULES LEVIN, Patient Representative

GUESTS PRESENT:

	COLEEN K. CUNNINGHAM, M.D.
	STEVEN DEEKS, M.D.
	VICTOR DeGRUTTOLA, Sc.D.
	JOSEPH ERON, M.D.
	JUDITH FALLOON, M.D.
	CARLTON HOGAN
	JOHN MELLORS, M.D.
	CARLA PETTINELLI, M.D., Ph.D.
	JONATHAN M. SCHAPIRO, M.D.
	MARTIN T. SCHECHTER, M.D., Ph.D., FRCPC
	DOUGLAS WARD, M.D.

FDA REPRESENTATIVES PRESENT:

	TOM HAMMERSTROM, Ph.D.
	HEIDI JOLSON, M.P.H., M.D.
	KATHERINE LAESSIG, M.D.
	KIMBERLY STRUBLE, Pharm.D.
	JEFFREY MURRAY, M.D., M.P.H.
	DIANNE MURPHY, M.D.

PUBLIC PRESENT:

	OTTO AH CHING, M.D.
	MICHAEL MARCO
	JIM ROONEY
	EMMANUEL TRENADO
	DANIEL VITTECOQ

	I‑N‑D‑E‑X

AGENDA ITEM	PAGE

Call to Order/Welcome	5
	Roy M. Gulick, M.D., M.P.H.
	Acting Chair, AVAC

Introduction of Committee	5

Conflict of Interest Statement	8
	Tara P. Turner, Pharm.D.
	Executive Secretary, AVAC

Introduction/Opening Remarks	13
	Heidi Jolson, M.D., M.P.H.
	Director
	Division of Antiviral Drug Products, FDA

Trial Design Issues	25

Therapeutic Challenges for Antiretroviral	25
Experienced Patients:  A Clinical Perspective
	Douglas Ward, M.D.
	DuPont Circle Physicians Group

Overview of Trial Design Options:  Adults	36
	Martin T. Schechter, M.D., Ph.D., FRCPC
	Professor, University of British Columbia
	National Director
	Canadian HIV Trials Network

Overview of Trial Design Options:  Pediatrics	59
	Coleen Cunningham, M.D.
	Associate Professor of Pediatrics
	SUNY Upstate Medical University

Trial Design Options:  Patient Perspective	70
	Carlton Hogan
	Community Programs for Clinical Research
		on AIDS (CPCRA)
	University of Minnesota School of Public
		Health
	Division of Biostatistics/CCBR

	I‑N‑D‑E‑X (Continued)

AGENDA ITEM (Continued)	PAGE

The Study of Antiretroviral Agents in Heavily	101
Pretreated HIV Infected Patients:
A Regulatory Perspective
	Katherine Laessig, M.D.
	Division of Antiviral Drug Products, FDA

Questions to the Committee	115

Open Public Hearing	180
	Emmanuel Trenado	180
	Otto Ah Ching, M.D. - Oxo Chemie AG	184
	Michael Marco - Treatment Action Group	185
	Dr. Vittecoq - EMEA, France	189
	Dr. Jim Rooney - ICC	200

Continue Questions to the Committee	216

II.  Endpoint Issues	268

Response Rates in Heavily Pretreated HIV	269
Infected Patients
	Roy M. Gulick, M.D., M.P.H.
	Assistant Professor of Medicine
	Weill Medical College of Cornell
		University

Statistical Considerations for Endpoints in	294
Heavily Pretreated Patients
	Victor DeGruttola, Sc.D.
	Professor of Biostatistics
	Harvard School of Public Health

Questions to the Committee	311

	P‑R‑O‑C‑E‑E‑D‑I‑N‑G‑S
	(8:34 a.m.)
	CALL TO ORDER/WELCOME
		ACTING CHAIRMAN GULICK:  Good morning.  I'm Trip Gulick from Cornell.  I'm the Acting Chair today.  I would like to welcome everyone to this meeting of the Antiviral Advisory Committee, where we will be speaking about HIV salvage therapy.
		I would like to start with introductions of the Committee members.  Please state your name and your affiliation.  And I would like to start with Yvette Delph, all the way down in that corner.
	INTRODUCTION OF COMMITTEE
		DR. DELPH:  Good morning.  I'm Yvette Delph from Silver Spring, Maryland.  And I work with the Treatment Action Group, a community‑based activist organization.
		MS. DEE:  Hi.  I'm Lynda Dee, and I'm from AIDS Action Baltimore and the Treatment Action Group.
		MR. LEVIN:  I'm Jules Levin, the Executive Director of NATAP, the National AIDS Treatment Advisory Project, ‑‑ we're based in New York City ‑‑ and also a community representative on the CCG and the ACTG.
		DR. MELLORS:  John Mellors, University of Pittsburgh.
		DR. SCHECHTER:  Martin Schechter, Canadian HIV Trials Network, guest speaker today.
		DR. DeMASI:  Ralph DeMasi, Director of Biometrics at Trimeris.
		DR. PETTINELLI:  Carla Pettinelli from the Division of AIDS, the National Institutes of Health.
		DR. FALLOON:  Judy Falloon, Intramural NIAID.
		DR. DEEKS:  Steven Deeks, San Francisco General Hospital.
		DR. WARD:  Doug Ward.  I'm also a guest speaker in private practice in Washington, D.C.
		DR. CUNNINGHAM:  Coleen Cunningham, Upstate Medical University in Syracuse and a member of the Pediatric ACTG.
		DR. SCHAPIRO:  Jonathan Schapiro from Stanford University and Tel Aviv University.
		DR. TURNER:  Tara Turner, Executive Secretary for the Committee.
		DR. MATHEWS:  Chris Mathews, UC‑San Diego.
		DR. FLETCHER:  Courtney Fletcher, University of Minnesota.
		DR. WONG:  Brian Wong, VA Hospital in West Haven and Yale University.
		DR. SAAG:  Mike Saag, UAB in Birmingham.
		DR. STANLEY:  Sharilyn Stanley, Texas Department of Health.
		DR. POMERANTZ:  Roger Pomerantz, Thomas Jefferson University.
		DR. KUMAR:  Princy Kumar, Georgetown University.
		DR. BLACKWELDER:  I'm Bill Blackwelder from the Biologics consulting group.
		DR. HAMMERSTROM:  Tom Hammerstrom, statistician, FDA.
		DR. LAESSIG:  Katie Laessig, Medical Officer, FDA.
		DR. STRUBLE:  Kim Struble, FDA.
		DR. MURRAY:  Jeff Murray, FDA.
		DR. JOLSON:  Heidi Jolson, Director of the Division of Antiviral Drug Products, FDA.
		DR. MURPHY:  Dianne Murphy, Office Director, FDA.  And I want to comment that yesterday this Committee provided an excellent discussion on trial design for antifungals.  I hope we hear the same sort of discussion again today.
		ACTING CHAIRMAN GULICK:  And I have no doubt about that.
		(Laughter.)
		ACTING CHAIRMAN GULICK:  This is one of the largest committees I think that has been convened.  In fact, I can barely see people at the end of the table.
		Okay.  Tara Turner will now read the conflict of interest statements.
		DR. TURNER:  Thank you.
	CONFLICT OF INTEREST STATEMENT
		DR. TURNER:  "The following announcement addresses the issue of conflict of interest with regard to this meeting and is made a part of the record to preclude even the appearance of such at this meeting.
		"Based on the submitted agenda for the meeting and all financial interests reported by the Committee participants, it has been determined that all interests in firms regulated by the Center for Drug Evaluation and Research which have been reported by the participants present no potential for an appearance of a conflict of interest at this meeting with the following exceptions.
		"Since the issues to be discussed by the Committee at this meeting will not have a unique impact on any particular firm or product but, rather, may have widespread implications with respect to an entire class of products, in accordance with 18 U.S.C. 208(b), each participant has been granted a waiver which permits them to participate in today's discussions.
		"A copy of these waiver statements may be obtained by submitting a written request to the agency's Freedom of Information Office, Room 12A‑30 of the Parklawn Building.
		"With respect to the FDA's invited guests, there are reported interests which we believe should be made public to allow the participants to objectively evaluate their comments.
		"Dr. Coleen Cunningham would like to disclose that she served as co‑investigator on a Glaxo‑Wellcome study in 1999.  She also received fees from Boehringer‑Ingelheim for a virology consultation and a lecture.
		"Mr. Carlton Hogan would like to disclose that he is an unpaid scientific adviser to Glaxo‑Wellcome, Boehringer‑Ingelheim, Abbott Labs, Trimeris, Gilead Sciences, Agouron, and Roche.
		"Mr. Hogan's employer, the University of Minnesota, has a cooperative agreement with the NIH.  They are the statistical and data management center for a clinical trials network called the CPCRA.  Mr. Hogan works at the CPCRA, which is housed at the Coordinating Center for Clinical Research at the university.  He does not directly handle data or see patients.  In addition, one of the study sites is currently receiving Combivir as the study drug in one of their trials.  And industry has supplied study drugs in prior trials.
		"Dr. John Mellors would like to disclose that he receives consulting fees from the Agouron Pharmaceuticals, Glaxo‑Wellcome, Visible Genetics, Abbott Labs, DuPont Merck, Bristol‑Myers Squibb, Boehringer‑Ingelheim, Gilead Sciences, and Merck.  He also receives consultant fees with stock options from Virco, Novirio, and Pharmasset.
		"Dr. Jonathan Schapiro would like to disclose that he is negotiating a contract with Roche to study Fortovase.  He received honoraria from Roche for his past lectures on HIV resistance.  He has also served as a scientific adviser to Roche and Agouron.
		"Dr. Steven Deeks would like to disclose that he has received contracts and grants from Abbott, Gilead Sciences, and Triangle.  He is also a research for ViroLogic and Viable Genetics, and he receives honoraria from Agouron, Glaxo‑Wellcome, Hoffman LaRoche, Merck, and Bristol‑Myers Squibb.
		"Dr. Victor DeGruttola would like to disclose that he owns stock in Pfizer Pharmaceutical.  In addition, he has a contract with Visible Genetics for data analysis.  Dr. DeGruttola has also received consulting fees from Tibotec, Incorporated.
		"Dr. Ralph DeMasi would like to disclose that he owns stock in Trimeris.
		"Dr. Martin Schechter would like to disclose that he is currently on an arm's‑length data safety monitoring board for a trial sponsored by Glaxo‑Wellcome.
		"Dr. Jules Levin would like to disclose that his organization, the National AIDS Treatment Advocacy Project, receives unrestricted educational grants from all HIV pharmaceutical companies.  NATAP also received the Ryan White Treatment Education Grant from HRSA.
		"Dr. Joseph Eron would like to disclose that his employer, the University of North Carolina, receives contracts from several major pharmaceutical companies to perform research for which he is listed as principal investigator.
		"Dr. Eron also receives consulting fees from Merck, Glaxo‑Wellcome, Trimeris, and Triangle.  Dr. Eron also receives honoraria from several pharmaceutical companies involved in development and marketing of antiretrovirals.  Additionally, he serves as a scientific adviser to Glaxo‑Wellcome, Merck, and Triangle.
		"Lastly, Dr. Douglas Ward would like to disclose that he owns stock in Vertex Pharmaceutical.  Dr. Ward also serves as a researcher for Glaxo‑Wellcome, Bristol‑Myers Squibb, Schering Plough, Agouron, Triangle, Merck, DuPont, and Gilead Sciences.
		"In addition, he serves as a consultant for Glaxo‑Wellcome, DuPont, Abbott, Roche, Agouron, Boehringer‑Ingelheim, Vertex, and Bristol‑Myers Squibb.  Dr. Ward also serves as a speaker for Glaxo‑Wellcome, DuPont, Chiron, and Agouron.
		"In the event that the discussions involve any other products or firms not already on the agenda for which an FDA participant has a financial interest, the participants are aware of the need to exclude themselves from such involvement.  And their exclusion will be noted for the record.
		"With respect to all other participants, we ask in the interest of fairness that they address any current or previous financial involvement with any firm whose products they may wish to comment upon."
		Thank you.
		ACTING CHAIRMAN GULICK:  Thanks very much.  I would like to turn it over to Dr. Jolson for introduction and opening remarks.
	INTRODUCTION/OPENING REMARKS
		DR. JOLSON:  Good morning.  I'm always asked to go first so that I can test out the equipment.  So I'm always sort of a guinea pig.
		We're really pleased to be able to convene this meeting today.  We realize it is long overdue and is probably the most important generally broad scientific meeting that we have convened in recent memory.
		In the next couple of minutes, I would like to just sort of state what the issues are that we think there will be general agreement on, talk a little bit about our meeting objectives, define the patient population that we're going to be speaking about today, talk a little bit about historically how we think we've reached this point as an agency and where we think that the field needs to go.
		I'll mention what FDA's role and interest and focus is just as a reminder, talk a little bit about how we went about seeking public comment, go over the agenda and acknowledgements for the meeting.
		So I tried to list a few issues that I think most of us will agree upon.  And for most of these things, you will hear data later today.
		First and foremost, I think we can all agree that the utility of initial regimens, both the first regimen, the second HAART regimen, is time‑limited.  Our first speaker today, Dr. Ward, will be talking to this point.
		Second, I think we understand loud and clear both from the community and as health care providers ourselves that there are insufficient treatment options for heavily treatment‑experienced patients.
		Thirdly, we are painfully aware that very, very few antiretroviral labels have information on either dosing, safety, or efficacy in treatment‑experienced patients.  And I'll talk a little bit about why that has come to be in a few moments.
		Fourth, I think we can all agree that the development of new agents and their identification as well as subsequent labeling is a major public health priority.
		So today's objectives, these are really the broad objectives beyond some of the technical issues that we will be discussing.  Fundamentally, we are interested as an agency in helping to facilitate and promote the development of new therapies for patients who we believe are most in need of treatment options.
		Second, we strongly wish to foster collaboration between companies in terms of conducting studies together, jointly developing promising products, and sharing placebos for study designs that would be appropriate.
		Third, we're hoping from this large expert Committee that we have assembled today to obtain recommendations that we will incorporate into our either existing or developing guidance documents.
		The HIV RNA guidance document is what is currently available on the Web.  It has recently been updated, but we would hope to incorporate the advice that we receive today into that general drug development guidance document as well as we would anticipate incorporating this information into our guidance documents that are in development which have to do with resistance testing during HIV drug development and also development of alternative dosing regimens.
		We realized as we were planning this meeting that for purposes of discussion, we needed to put forward a definition of the relevant patient population. because otherwise we appreciated that we would probably spend the better part of the morning trying to decide and come to agreement on a common definition.
		There's no question that clinically there are many different ways to define patients who are in need of therapeutic options, but we have put forward purely for purposes of discussion the following definition.  And that would be patients who have experienced loss or lack of virologic response to at least two combination HAART regimens and patients who within those regimens have had experience with at least one member of each of the three pharmacologic classes.
		Why this definition when so many others could have been chosen?  We feel that, as a minimal definition, this would identify patients in whom designing comparative trials has been particularly problematic.
		Next slide, please.  So how did we reach this point?  It's certainly easy to say we reached this point because FDA hasn't done enough.  Well, I think that is a little simplistic.
		Historically, in fact, we have recommended that new antiretrovirals be studied in many patient groups and in a very broad population to match the use in actual practice.
		We have, additionally, provided for flexibility in what the endpoint is.  However, in reality, we are painfully aware that most registrational studies have been conducted in either treatment‑naive patients or nucleoside‑experienced patients only with very few exceptions.
		Why is that when we realize that there are other patients in need of therapy and in need of having data and labeling?  One is sort of the practical element that often the treatment standards have evolved since trials, registrational trials, would have been initiated a couple of years ago.  That no longer is a good excuse, but that is probably the case for drugs that may have been approved about two years ago.
		Second, unfortunately, sometimes the new drug is just not expected to be particularly effective or active in a more experienced population because of cross‑resistance.
		The third possible reason is really the reason we have convened this Committee, because we will recognize the challenges of trial design and also data interpretation in a treatment‑experienced population.
		Next slide.  We have thrown out just a few of the challenges that we are aware of from speaking to patient groups and also to industry.  Why are these trials so difficult to do?  Why do we need a meeting?  And why do we need probably the largest advisory committee that we have ever assembled to discuss this issue really speaks to what a challenge these trials are to design and interpret.
		One is the heterogeneity of the population.  It's certainly easy to put a population definition on a slide, but in reality, as everyone knows, each patient is different and each patient comes with a different history, probably a different resistance profile, and has different treatment needs.
		Second, it is difficult enough to put together one regimen that would be acceptable for a given patient, but then to figure out what would be an acceptable comparator for the control group becomes even more problematic.
		Third, although traditionally we have hoped to maximally suppress viral replication, that may not be possible with all the therapeutics that are currently in development.  So that means we have to look to alternative either virologic or immunologic or clinical endpoints, but we need to discuss as a group which endpoints are clinically relevant and for any given agent what endpoints are likely to be achievable.
		Fourth, we're increasingly aware that additional dose finding is necessary for many products in treatment‑experienced populations.  I think that we're starting to see more interest amongst industry to do additional dose finding, not just in treatment‑naive subjects but also in previously treated patients.
		Fifthly, every new drug needs a safety database.  Certainly with some of these trial designs, safety assessments will be more complicated because of the additional therapies and lack of clear‑cut comparators.
		Next slide.  Well, where do we need to go?  Hopefully we all will agree on this, that we do need new agents that have both acceptable tolerability but also established efficacy.  That means you need real data to support their use and what I have in yellow here, the development of novel clinical trial design approaches that we hope to formulate today.
		Next slide.  So what is our role in all of this?  It has been really interesting as we have had ongoing discussions with community and industry.  It has become clear that FDA has a major role to play in bringing forward this issue.  And it has been very interesting to see both the community and industry looking to us to kind of lead the way and to put people's minds together to try and deal with some of these problems.
		In 1999, we sent a letter to all ID holders, the pharmaceutical sponsors, to articulate that there is absolutely no prohibition against use of more than one investigational agent in either a clinical trial protocol or through expanded access, there had been a common misconception that the law didn't allow that.  It is absolutely not true, and we think that this is an important component of most clinical trials in this population.
		Additionally, we have increasingly been trying to provide both labeling and other regulatory incentives to promote development.  As an example of newer labeling, I would refer you to the newly approved Kaletra label, which certainly has labeling that is somewhat different than has previously appeared with previous drugs when there is data that we think is important for practitioners and patients to be aware of for use in a more treatment‑experienced population.
		Other regulatory incentives would be the accelerated approval provisions.  Certainly development of drugs for treatment‑experienced patients is probably the best use of accelerated approval provisions as well as priority review, meaning a faster time frame for reviewing a new drug application.
		I think it was clear in talking to both industry and the community that there was the consensus about a need for an FDA‑sponsored working meeting on this topic.  After I made this slide, it is not to say that other advisory committees aren't working meetings, that you all don't work at them, but this is one where we are coming to you with very open‑ended questions and asking you to do work at the meeting and trying to develop answers.
		Just as a reminder, what is FDA's focus?  There are many different types of trials.  This is always a point of confusion.  What does FDA need to put something on the label or make a regulatory decision?  Well, usually these are registrational studies, which are also described as the adequate and well‑controlled pivotal trials.  They are somewhat different than the equally clinically important strategy studies, which are studies that are more exploratory in nature, which would assess the overall efficacy of a regimen.
		The major distinction is that it's the registrational study that would allow us to evaluate the contribution of a given drug.  That is the burden that sponsors have in order to put that information in labeling.
		But that's not all we're interested in.  We're also interested in other trial designs and data collection tools that will provide important prescribing information for labeling.  Examples would be dose finding, drug interactions, other special focus questions.
		Next slide.  In order to plan this meeting, we very broadly solicited public input.  And we sent out on October 3rd hundreds and hundreds and hundreds of letters to both industry and to I think several hundred community groups.  I want to thank Richard Klein's help with that from the Office of Special Health Issues.  We also published a Federal Register notice.
		In this letter and letter and official notice, we specifically asked for proposals for trial design and the role of specific designs, comments on the relevant patient population in need, and baseline stratification characteristics.
		We asked for comment on what are appropriate or inappropriate control arms and the result of resistance testing to construct an optimal regimen.
		We asked for feedback on appropriate outcome measures, different clinical trial endpoints, as well as any additional comments on special considerations for pediatric populations.
		Next slide.  And so with that feedback, which you'll be hearing about a lot today, we put together the following agenda.  First I would like to thank all of today's speakers, who have come in from, really, around the world to try and hit some of the major high points for consideration before the Committee approaches these very difficult questions.
		We'll be starting out this morning with the clinical perspective, kind of setting the stage for what is the clinical reality in the year 2001; then moving on to trial design options for adults, kind of an overview of the trial design science; additional options for consideration for pediatric population; and, importantly, an opportunity to hear from a patient perspective what are acceptable trial design options.
		Following those presentations, our division will present a summary of the many responses that we received from the public as well as our regulatory perspective on some of these options.
		Next slide.  Of course, plenty of time for discussion.  And in the afternoon, we'll start out with an open public hearing.  I know that there are several speakers who have signed up and I think will also add significantly to our understanding of the issue.
		And then we'll be turning later this afternoon to the issue of endpoints, and we'll be talking about what response rates have previously been in previously conducted trials as well as what some of the important statistical considerations are that have further discussion and questions to the Committee.
		Next slide, please.  In closing, I really would like to acknowledge the unbelievably valuable input we have gotten from numerous community groups as well as from industry groups that are summarized here.
		I read them when they initially came in.  And yesterday afternoon, I wanted to refresh my memory.  I was just really impressed with the quality of thought and attention that everyone listed here on this slide brought to this issue and really speaks to the widespread recognition of the importance of today's meeting.
		And, lastly, I want to end by acknowledging the folks in our division as well as Richard Klein, who put together this meeting and have really worked very hard, in addition to doing all of their usual work, to bring forward what I think will be a very productive discussion and informative for us all and which we feel will really help stimulate the field.
		Thank you.
		ACTING CHAIRMAN GULICK:  Thanks, Dr. Jolson.
	TRIAL DESIGN ISSUES
		ACTING CHAIRMAN GULICK:  Can we turn now to begin the morning presentations, focusing on trial design issues.  The first speaker will be Dr. Douglas Ward from the DuPont Circle Physicians Group, who will be speaking on a clinical perspective for challenges for experienced patients.
		DR. WARD:  Thank you very much.
THERAPEUTIC CHALLENGES FOR ANTIRETROVIRAL
EXPERIENCED PATIENTS:  A CLINICAL PERSPECTIVE
		DR. WARD:  The first thing I did this morning when I woke up was talk to myself a little bit to see if I had my voice back.  Unfortunately, it's not.  So if you close your eyes, you can just imagine you have Brenda Vaccaro talking about this for you.
		My job this morning is to just go over the therapeutic challenges for heavily pretreated patients from the viewpoint of someone as a primary care treatment provider and someone who does clinical research.
		I would point out that I'm going to be using the politically incorrect term of "salvage," which when I thought about this, I went back to my Merriam Webster's and found that the verb "salvage" means to rescue or save.  So I think in this situation, it is an appropriate term to describe our treatment approaches for patients in these really pretreated situations.
		Next slide.  Defining salvage or treatment failure is a difficult subject.  Certainly it can be based on failure of treatment regimens as the definition that is being used for today's meeting, failing at least two HAART regimens that have included at least one drug of each group/class.
		Certainly there's a question of in that situation:  How do we define failure?  Is it increasing viral load, failure to become undetectable?  And certainly this is a variable answer for different patients.  One of my patients who has been undetectable would certainly consider a viral load of 1,000 a failure; whereas, I have other patients who would give their eyeteeth to be at 1,000.
		Alternatively, we could base salvage on other definitions, including resistance, either genotypic or phenotypic.  Certainly these two definitions are very closely related.  Treatment failure generally leads to resistance.
		Next slide.  Very briefly, one study published this year just looks at in the first, second, and third regimens there is a decrease in response rate and a decrease in sensitivity to the drugs, which explains the decreased response rate.
		Next slide.  Why do we need salvage therapy in this day and age with many antivirals of different classes available?  For a naive patient, we really do get very good success rates.  I can be very optimistic with a naive patient new to treatment that we can do a very good job of getting them undetectable and keeping them undetectable for a long time.  However, there are treatment failures out there, experienced patients, who have this failure for multiple reasons.
		One of the more common I see is patients who have been on treatment for years, even over a decade now, very commonly having a prolonged history of sequential mono therapy of the RT inhibitors before a HAART became available so that they have very extensive RT resistance and when the proteases and non‑nucs became available had a poor response to those because they didn't have accompanied drugs to use with them.
		Another very common cause of treatment failure is noncompliance.  This is a chronic problem with patients.  And if a first regimen fails because of noncompliance, there is certainly a high incidence of failure of subsequent regimens for the exact same reason.
		There are poor treatment choices, either from inexperienced providers or I will certainly admit and in retrospect, I made a lot of bad choices in years past simply for lack of knowledge of how to use some of our drugs.  I have done things that I would never do nowadays.
		And certainly there are treatment failures that we just can't explain.  Nothing is black and white in the treatment of HIV.
		Next slide.  How common is this problem?  If you look at clinical trials, failure rates range anywhere from 5 to 60 percent.  I can name trials that on treatment have 100 percent success rate and other trials even lower.
		Looking at surveys of clinical practices, success rates are even lower than we see in clinical trials, where you generally have motivated, well‑monitored patients.
		When a first regimen fails, the success rate in subsequent regimens is even lower and makes the prognosis for further regimens even worse.  And the resistance from the original regimen carries over.  So you've got two failed regimens to work with on subsequent ones.
		The HOBBES database that I participate in, database of about 2,500 people, Frank Pellom looked at the durability of response to subsequent regimens.  Certainly the first regimen on a Kaplan‑Meier curve here has significantly longer duration of response than the second or third regimens, which tend to fail more rapidly.
		Next slide.  Looking at the prevalence of treatment failures, I did a review of my own patient population, which I actually for the first time found out is about 300 patients and found that 54, or 19 percent, of my patients are not on treatment.  Either they haven't needed it or, for various reasons, have gone off treatment.
		Twenty‑six percent are undetectable, below the limit of quantification, under first HAART regimen.  Seventy‑seven, 27 percent, have been on treatment for a long time, became undetectable once they began a HAART regimen, and have stayed undetectable since.  With 53 percent of patients undetectable on a HAART regimen, I think I'm probably a little bit above the average.
		Thirty‑three patients, or 12 percent, are patients who have failed multiple regimens, can be defined as someone who needed a salvage regimen and have been successful on that salvage regimen, have a prolonged undetectable viral load.
		Importantly, I have 34 patients, or 12 percent of my patient population, who currently need salvage.  They have been through multiple therapies.  They have extensive resistance.  And I don't have anything to offer them currently for an improved regimen.  About four percent are in various regimens that I just couldn't assign to one of these categories.
		Next slide.  Salvage treatment is obviously very difficult, which is the reason we're here today.  There is a lot of cross‑resistance to previously used drugs and cross‑resistance of these drugs to potential new agents.  So we're limited in what we can do.
		Multi‑drug regimens or MegaHAART, trying to use as many drugs as possible, can be difficult to take, difficult to tolerate.  Traditionally, historically new agents have become available one at a time.  So as with the RT inhibitors, we have successive mono therapy and then single new agents to add in to a failing regimen.
		The one exception to this I can remember was around '98, when the expanded access program for three different drugs, efavirenz, abacavir, and adefovir, were all available at the same time.  And certainly as clinicians, we took advantage of this for our failing patients.
		In my three‑physician practice, we had over 100 patients enrolled in these expanded access programs at the time trying to use multiple new agents for these salvage patients.  And, indeed, a number of the patients that we had at this time we did finally get into a successful new regimen.
		Doing clinical trials in the salvage situation is also very difficult.  As has been mentioned, it is a very diverse patient population, both in treatment history and resistance.  And trying to draw conclusions from very different starting points is difficult.
		New agent trials have generally been designed for registrational purposes and can be difficult to show efficacy in a salvage situation.  So the trials are not used for this purpose.
		I just did a check of the trials that my practice was offered in the last year, seeing how many trials are available for salvage.  We had eight trials offered to us for treatment‑naive patients.  We get two or three naive patients a month.  We were able to participate in some of these trials and enroll well.
		We had two trials offered to us for experienced patients.  However, they were very restrictive in their entry criteria; for instance, first protease failure, non‑nuc‑naive.
		I use a lot of non‑nucs.  I had absolutely no one to enroll in these trials.  And we did a very poor job of enrollment or simply turned the trial down because we didn't think we could enroll.
		We had two trials offered to us, truly useable in a salvage situation; one of them, expanded access program with tenofovir.  But, once again, by and large, simply adding in one new agent, even though it does seem to have efficacy in the setting of resistance, and one trial with interferon for HIV, simply, once again, an add‑on therapy without hope of true salvage.  So the trials so far don't appear to be out there for what we need looking for this.
		Next slide.  From the viewpoint of someone who is providing care to their patients as well as doing clinical trials, I have a number of things I want in salvage trials; first of all, a reasonable expectation that the new agent or new regimen is going to be effective and offer hope to my patient of a good response.  This includes both new agents or new regimens of existing agents.
		Salvage trials need to be planned and executed, even before licensing of a drug, so that we can use the agent in these trials, even before it's widely available on expanded access programs.
		Patients want access to these drugs.  And by the time the trials many times are done as Phase IV trials, there is already extensive experience with the drugs, making the trials difficult to enroll.  Entry criteria for trials need to be applicable to the populations that they're relevant to, not extremely restrictive, so that we have them available for the patients who need them.
		The definition of success in salvage trials may not be the same as that in registrational trials.  We may have different endpoints, less strict endpoints, but also we have to be flexible in how we apply these trials with bailout options for lack of efficacy in the trials.
		As with all clinical trials, even in salvage, placebo controls are acceptable if the efficacy of an agent is truly unknown.  And trials can also be designed to include non‑drug interventions, treatment interruptions, immune stimulants, and other interventions that we may have available.
		Next slide.  If I can deign to approach this from the patient's viewpoint, once again, in entering a clinical trial, a patient has a reasonable expectation of efficacy of the new agent.  Many of these patients who have been through many treatment regimens over the years continually failing and decreasing immune system are desperate for effective therapy.  They want agents, access to new effective agents, as soon as possible because they don't have time to wait.
		Patients also are aware that using new agents as mono therapy is simply going to make the new agents less effective.  And those patients who are clinically stable, despite treatment failure, are going to wait for multiple therapies used together for a more effective regimen.
		In the salvage situation, we may be willing to accept more risk of toxicity if there is a possibility of success where we haven't had it before.  Unfortunately, these patients after extensive treatment and frequently with advanced disease may be more prone to toxicity.
		So, finally, I just want to mention to keep in mind that for the patients entering salvage trials, this isn't just an experiment.  It's their treatment and their life.  I think we need to keep this in mind also.
		Thank you.
		ACTING CHAIRMAN GULICK:  Thank you, Dr. Ward.
		Are there one or two questions from the panel?
		(No response.)
		ACTING CHAIRMAN GULICK:  Must be crystal clear.  Thank you.
		Our next presentation is Dr. Martin Schechter from the Canadian HIV Trials Network, who is going to talk about trial design options in adults.
	OVERVIEW OF TRIAL DESIGN OPTIONS:  ADULTS
		DR. SCHECHTER:  First of all, thank you to Dr. Jolson and the Committee for the invitation to talk today.
		I'm going to try to talk about some of the challenges in dealing with trial designs and probably have to warn you that there are probably more questions than answers ahead.  And if there is a laser pointer around?  Ah, there is.  Great.
		The first question that people have approached me with is the question of whether we actually have to do randomized controls and whether in the context of salvage therapy we can look to other options.
		I go back.  I'll be talking a bit about the history of medicine today, the case of tuberculous meningitis.  It was universally fatal prior to 1945.
		In 1946, streptomycin appeared.  It was a new drug in very short supply.  And some treated patients were given this drug, were treated with it, and they survived.  It was deemed that randomized controls were unnecessary because the experience was so different from what historically had been observed.
		The point, though, is that in this situation, we're dealing with an extremely homogeneous patient group.  They all had end‑stage and accurate lethal infectious disease.  The outcome was mortality.  The prior outcome pattern; that is, 100 percent lethality, had been fully characterized.  And this was a very short‑term study.  Adherence was not an issue.
		Now, one of the things we're dealing with is that as we move from naive populations to salvage populations in time, there is something that is rising sharply.  It could be viral load.  It could be other things.  But, in fact, one other thing that is rising very, very sharply is patient heterogeneity in time.
		What is increasing is the drug history.  This is how people diverge in time through this period.  The drug exposure intensity that they have experienced; genotype; phenotype; virologic status; immunologic status; clinical status; toxicities they have experienced; malabsorption; previous treatment interruptions; adherence patterns; and, finally, their attitude about treatment, which is very important.  So that curve, people diverge continuously in time as we move.  And, as well, unknown confounders are also diverging.
		Now, heterogeneity per se does not matter.  So in and of itself, it doesn't matter if you have a heterogeneous population.  It does matter when these variables are strongly prognostic.
		Now, I borrowed some data from the Julio Montaner at our place from a multi‑drug rescue therapy.  The point here is not to look at actual data, but this is variables predicting achieving a decline below 400 in people who had multiple drug failures in the past using many, many drugs.
		I just want you to look at some of the strengths of the odds ratios at predicting the ability to suppress virus in a salvage population.  3TC resistance had an odds ratio of .17, meaning that means people one‑sixth as likely to achieve suppression of viral load, one‑sixth as likely.  That's equivalent to an odds ratio of six.
		You'll see when you look at these odds ratios that they are stronger than any treatment effect we might anticipate.  So, in fact, the predictor variables can be stronger than the treatment effect.  And when that's true, it's very dangerous when you have heterogeneous populations.
		Now, as patient heterogeneity rises in time, there's something else falling.  This could be the CD4 count, but also it's our ability to control confounders.  This is plummeting in time as we move towards salvage populations.
		Salvage studies, this is the previous graph of increasing heterogeneity, inability to control confounders.  And this is where salvage studies live:  out in this territory.
		Now, can we avoid randomized trials?  The attraction, obviously, when people have approached us to talk about historical controls, it's obviously a very attractive approach.  And you will see, in fact, in the binder we receive numbers and numbers of case series of people, 30, 40, 50 patients trying to extrapolate what their viral load outcomes were against the observation in other groups.
		There are lessons from the history of medicine; for example, gastric freezing for duodenal ulcer.  The President of the American College of Surgeons decided to try cooled gastric balloons.  And he did a very impressive case series.
		By the way, this was in the '60s.  This is not in the 1800s.  He wrote, "Since 1961, no patients with duodenal ulcer referred for elective operation have been operated on in the senior author's service.  This circumstance itself bespeaks the confidence in the method by patients as well as surgeons."
		Well, this led to the sale of 2,500 gastric freeze balloons.  An estimated 15,000 patients were chilled.  Finally, a double‑blind randomized control trial was done in the '60s.  The outcomes were poor outcomes:  Surgery, bleed, or intractable pain.  They did a sham procedure.  Their rate was 44 percent.  In the freeze group, they had a higher rate of poor outcomes when it was done as a randomized trial.
		There is a VA study of estrogen in the treatment of prostate cancer.  This is an RCT of 2,300 patients recruited over 7 years, no change in the eligibility criteria throughout the trial.  When you look at what happens to placebo patients in the first two and a half years, they had worse survival than the estrogen patients in the last 2.5.  So someone could very easily come along, take this as a series, use these patients as historical controls, and conclude that estrogen was effective when, in fact, in the trial overall, there was no treatment effect.
		In uncontrolled Phase II cancer studies in advanced bowel cancer in 20 different case series of rapid injection 5‑FU, when you look at the 6 largest series, 40 to 150, the response rates ranged from 11 percent to 55 percent.
		So this author could use this author as control and note a treatment effect of fivefold.  These numbers are kind of the range of things you see in the literature about ability to achieve a plasma viral load suppression.
		So traditional orthodoxy is that it is well‑known that historical control studies are far more likely to yield positive results.  There are a number of articles in the literature that show this.  And that has led to the dominance of the randomized control trial.
		There continues to be an ongoing debate.  And just to show you a paper published this year in the New England Journal, I know you can't see this, but let me just try to tell you there are five treatment conditions here.  And on each of these, these are the odds ratios of treatment effect.  The closed circles are the results from randomized trials.  The open circles are the results from case control or cohort studies.
		You can see that, in fact, well‑done observational studies don't do too badly.  I think this is here to show you the range that you can get from different clinical trials, that the observational studies do pretty well at mimicking the treatment effect that you see in some of the RCTs.  This was in the New England Journal this year, Concato, Shaha and Horwitz, the point being that those were well‑designed case control and cohort studies.
		And those are not the same as historical control studies or chart reviews.  These involve the careful selection of controls.  They're usually concurrent.  But they could play a role in a situation where prognostic variables are completely categorized.
		Now, what about the idea of using non‑randomized concurrent comparisons by post‑randomization variables?  That's a mouthful, but what's an example?  When you do a within‑study comparison based on adherence to a regimen, a very attractive alternative, for example, within the context of the trial, if people who adhere to the drug do better, doesn't that prove that the drug is effective than people who don't adhere as well?
		So we go to the history of medicine again, and we look at a lipid‑lowering trial.  This is people in one arm of a study who were given a medication called medication A.  These are people who adhered, less than 80 percent.  By pill count, these are the people who adhere, greater than 80 percent.
		There are the numbers.  You can see the mortality rate was double in the people who did not adhere than the people who adhered.  This, by the way, was adjusted for 40 baseline predictors, so everything you can think of, the things that we would think of in HIV, they have thought of for cardiovascular mortality:  blood pressure, prior MI, New York clarification, angina, and so on.  So quite a clear effect that if you take this drug, you do twice as well as if you don't take it and, in fact, turns out that this was the placebo arm of the trial.  In fact, this table looks identical to the table you got in the active arm.
		So what does this mean?  Does placebo work better or does it tell us that people who adhere are destined to do better because they adhere?  It reminds us that there are more confounders on heaven and Earth that are dreamt of in our philosophy.
		Salvage therapy and non‑randomized controls.  As I said, we are dealing with very heterogeneous populations, some variables measurable, some not.
		We have some very strong prognostic factors, many as yet identified:  variable, surrogate marker, outcomes.  So I think we have to deal very cautiously, particularly in this population.
		Now, it could be that if we were to move the definition of salvage therapy further along the natural history to where it became homogeneous again, we might do better.  So if we can move later and we define people by being in worse categories right across the board and getting closer to what might we use the word "salvage" really for, we can possibly get to a situation where outcomes are well‑characterized and where this is possible.
		However, in the meantime, how do we control confounders?  We have randomization.  We have large sample size.  And when you have the combination therapy of these two things, randomization, large sample size, you can get a likely result that you can distribute known and unknown confounders equally.
		Now, if you look, for example, in the package we were sent, you will see a few papers with very large sample sizes, but you will also see a whole number of case series involving 18, 20, 13, 25, 40 patients.
		What are the remedies for confounding and smaller sample size studies?  Well, we can stratify the randomization, which means you pick your strongest prognostic factors.
		You stratify first and then you randomize.  If there are n such variables, you will have 2n strata.  And this becomes unwieldy.  Sometimes people will build a risk index combining different variables and stratify based on that.
		There are schemes in which you have an adaptive allocation, which minimizes the imbalances between the groups.  So as you go along, if you see that you have an imbalance with regard to some prognostic factor, you would adjust the randomization to try to address that.  So that is an adaptive allocation.
		And, also, there is always post hoc adjustment.  Now, the worry with post hoc adjustment by multi‑variate analysis is the debate about whether you are having an effect on unknown confounders.  And there is the issue of what happens when your crude result is different from your multi‑variate result.
		Again, let me just state something that we all know.  There is no within‑study remedy for lack of power in small sample size studies.  You see these small case series of 18 and 20 and 25 patients.  So this is worth remembering when we see that.
		The issue of blinding is an interesting one in the context of salvage.  It's orthodoxy, of course, that blinding is required in trials.  There are numerous studies that have shown that less bias occurs when you have fully blinded studies and you have a far more likelihood of positive results.
		For example, this is a large series, a meta analysis, published in JAMA in 1995, 33 meta analyses, 250 trials involving 52,000 participants, 12,000 outcome events.
		This is what they call blinding.  They called it "allocation concealment."  "Adequate" meant the ideal.  "Unclear" was sort of a middle category.  And "inadequate" would be sort of an unblinded randomization.
		These are the odds ratio, one being referent for adequate.  You can see that as you move down to less and less blinding, you get stronger and stronger treatment effects.  There are a number of papers in the literature that show this to be the case.
		However, one shouldn't get too strident.  Is blinding feasible, for example, in the context of salvage therapy?  That's obviously an important question for multi‑drug studies.  And can the artifact of blinding introduce more bias than it prevents?
		For example, in a study that we are looking at in which we are going to compare standard therapy, less than four drugs, versus MegaHAART, if you look at the issue of blinding, you first think about that standard therapy may benefit by greater adherence.  That's how if it were to become more efficacious in the result it may do so simply because adherence is better.
		If we were to try to blind this study, we would, first of all, need from 9 to 17 different types of pills.  And, more importantly, we would put on the standard therapy arm an artificial pill burden that would not be experienced in real life under real life standard HAART.  So, in fact, this bias, this artifact in the clinical trial, the blinding, could wipe out the adherence advantage and introduce a virus.
		Another problem as we move through naive to salvage is that intent to treat and treatment received diverge during this time period.  This raises particular clinical trial challenges, rapid crossover and dropout.
		For example, if you, say, cease in a study, you are actually moving from multi‑drug to an interruption arm.  Intent to treat becomes meaningless.  Treatment received becomes highly biased.
		The availability of new treatments or strategies as you move forward in time, genotypic testing, compassion, and access are dangerous when they are not built or accommodated into the protocol.
		Now, if we deal with some of these, offer of early versus late therapy may induce better protocol adherence to keep people in the arm to which they are allocated.
		For example, if we are doing an interruption trial, we may do interruption now versus interruption in X months from now.  And participant education is very important to keep treatment received.  And the possibility of a switch after a poor response triggering a crossover is also a way to try to maximize that.
		The availability of new treatments or strategies, we need obviously to think about rolling protocols that can roll with the punches and preplan future randomizations of future options.
		Let me speak briefly about factorial designs and give you an illustration.  One could ask a question.  In people who were treated with indinavir who are NNRTI‑naive and who we would like to try different strategies, you could try a simple randomized trial of saquinavir, ritonavir, delavirdine, versus nelfinavir, and adefovir, which will answer one question but obviously leave a number of questions unanswered after that trial was done.
		Well, an alternative way to approach this ‑‑ and here is the question again:  What is the role of adefovir, delavirdine in these kinds of patients?  What about approaching it this way, which is what was done in ACTG 359, is to say there are three options in this axis, delavirdine, adefovir, or combination of both, and in this axis ritonavir or nelfinavir all in a base of saquinavir?  We randomized approximately 50 people to each of these 6 arms.
		What do you get out of this?  Well, you get a lot of things because you have 100 patients on delavirdine, 100 on adefovir, 100 on the combination.  That gives you the comparisons in the vertical axis.
		In the horizontal access, you have about 150 patients randomized to ritonavir and nelfinavir.  So you're answering a number of questions.  And, even better, if there are any interactions, for example, between two drugs, ‑‑ and I don't mean drug interactions; I mean treatment effect interactions ‑‑ you will be able to discern these within this context.
		We are currently looking at a study where, instead of looking at combinations of drugs, we are looking at combinations of strategies.  Optima is a two‑by‑two factorial which involves a treatment interruption, no interruption, MiniHAART versus MegaHAART.
		And it will be a two‑by‑two factorial design, which will allow the study of the effect of the interruption, the study of the effect of mini versus mega, and possibly the fact that these two strategies might interact and lead to some kind of synergy.
		Here is another one, which is a trial of HIV‑infected women in Tanzania in the Lancet, 1998.  This was to test general vitamins, Vitamin A, whether their combination worked versus double placebo.  So you could have one vitamin, both vitamins, or nothing.  In fact, this showed that I believe the multivitamins were effective and the Vitamin A was not.
		Interestingly, when I did a Medline search and I used the term "factorial design" as a keyword anywhere in the text and I cross‑referenced that with HIV, I actually found three references, which struck me as very low, but that's what I got.  I think it's safe to say that factorial designs are woefully under‑utilized in the medical literature in general.
		Now, the variables that we use in a factorial design can be the combination.  So here, for example, is a two‑by‑two factorial study, where there are four different combinations.  And that looks like the little two‑by‑two table I just showed you.  So that's one two‑by‑two factorial.
		Now, rather than randomizing on another variable, we might have a stratification.  This might be a genotypic resistance, and this might be its absence.  What we do is stratify and send each group to their two‑by‑two factorial trial.  So the same four combinations are used.
		Now, not only do you get the Combo 1 versus Combo 2 comparisons in the presence or absence of these, but you get the vertical comparisons.  And you can look at the interaction of these treatment effects with whether the factor is present or absent.
		Now, suppose we have a complex situation, we have one factor, like a mutation which has three straight up.  We have another factor which has three straight up.  And we have three combinations of drugs we want to compare, one, two, and three.
		You can see if we were to do a full factorial design, we would be talking about 27 different cells.  And it becomes quite unwieldy.  So we can turn to something called the Latin Square design.  This is something that is used in basic science, in pharmacokinetic studies, and very commonly in veterinary science.
		A Medline search using the term "Latin Square" as a text word with the cross‑reference to HIV revealed no hits.  So I haven't seen this done, but there is a very good article in 1998 JID which talks about the efficiencies of this.
		In this case, rather than doing 27 cells, which would be the full factorial, you build a three‑by‑three table.  A, B, C is this variable, I, II, III here.  And, rather than trying to offer I, II, III in each cell, you move across like this.
		So every vertical row has each of the combinations present.  Every horizontal row has each of the combinations present.  There are efficiencies here in the comparisons you can make.  It's obviously not as robust as the full factorial design, but it's also one‑third as large.
		So factorial designs are ideally suited when you have multiple therapies that exist and we can give them in different combinations.  They're ideally suited when you have different strategies that can be combined.  So you might be looking at drug combinations against interruptions, drug combinations against vaccines or immunomodulators or adjunctive therapies or complementary therapies.  There are ideal scenarios for setting up factorial designs that involve each of these or two of them at a time.
		You can look at independent treatment effects within the design, and you can also look for synergies of different combinations.  These are symmetric, and they're highly efficient.  Again, if you look at several publications; for example, the JID publication will show you the power curves that tell you the efficiencies and the fact that you do receive much more bang for your buck when you go this route.
		Again, as I mentioned earlier, they're woefully under‑utilized in the clinical trial literature, particularly in HIV, where we don't see them all that often.
		Now let me conclude by looking at an issue which is not easy to solve, but it is one that we are left with, which is the issue of drug‑wise versus strategy‑wise evaluation.  I will deal with this hypothetically.
		Suppose we have new drugs A and B in two different classes and we're hopeful because they appear to have new resistance patterns within their class and A is available for trials now and B is going to be available in six months, say.  Well, what might happen?
		Well, you can see in the drug‑wise evaluation, first somebody will do a trial of A and then later, six months later, a trial of B will begin, switch B versus non‑switch.
		Now, each of these trials will probably contaminate the other because people in the first trial will want access to B and vice versa.  So what you end up with is two not mono therapy trials but switch of mono therapy with possible co‑intervention in each trial.  And the picture looks like this, where you get two independent questions possibly answered but with contamination.  That would be the drug‑wise approach.
		Now, what if we were able somehow to take a strategy‑wise approach to this evaluation?  We could start trial one of switch A versus non‑switch.  We preschedule a second randomization of switch B versus non‑switch when B is available.  This is a two‑by‑two factorial design.  And the trial would look like this.  Okay?  So that's a two‑by‑two factorial.
		Another way we could approach strategy‑wise drug evaluation would be to wait and say, "Let's wait six months.  And let's actually do the double switch" because if that's the clinically relevant question, let's do it that way.  And we perform a two‑by‑two factorial double switch with double the sample size and look at the interactive effect.  So that trial would look like that.  You get AB and combination AB from the outset if you were to wait.
		Miscellaneous considerations:  randomized consent designs or Zelen designs, which is where if the two arms in the study are much less or wildly different from one another.
		The classic example where this was used is in the lumpectomy versus mastectomy trial.  And, rather than asking women to submit themselves to a randomization, where they were depending on the flip of a coin to determine what kind of surgery they got, they actually randomized first and then sought consent.  This sometimes works in trials where there is a marked difference between the treatment arms.
		There is an ‑‑ now, this is a very controversial subject ‑‑ adaptive assignment, so‑called play the winner.  You have to be in a situation where you have rapid endpoints, you are always seeing what is going on in the trial.  But there have been classic examples where this has failed miserably.  And it violates the simple rapid objective foolproof thing we would like in treatment assignment.
		Finally, I will just end quickly with a little talk about things besides ‑‑ this really is a bad title.  It should be "Other Endpoints."  Quality of life, economic costs and savings, survival, quality‑adjusted life years, and cost per quality.  These are issues I think that have to be addressed in salvage trials particularly, rather than simply looking at surrogate marker endpoints.
		Just some comparators.  There is a list of U.S. dollars per quality of life year gained, various different types of procedures.  Where I come from, we have to show when we introduce a new thing into our formulary, where it fits in onto the table and can be justified.
		So I will stop there.  Thank you very much.
		ACTING CHAIRMAN GULICK:  Thanks, Dr. Schechter.
		(Applause.)
		ACTING CHAIRMAN GULICK:  Are there one or two quick questions?  Dr. Wong?
		DR. WONG:  I didn't understand the Latin Square design.  Could you just expand a little, maybe show an example of how that might be done?
		DR. SCHECHTER:  Well, actually, it comes from agriculture and from different sciences.  I wish I could get that table back.  If you had three different combinations and you had ‑‑ I think the example in the JID paper looks at ‑‑ let's see if ‑‑ well, anyway, imagine a three‑by‑three table and you have ‑‑ let's say across the top, the categorization is three different mutation patterns and vertically, say, numbers of protease mutations.
		If you wanted to assign each of the three combinations you were looking at to each of those nine combinations of mutation and resistance patterns, you would require 27 different allocations.
		But if you do it by going one, two, three, then two, three, one, then three, two, one, rather than needing 27 different cells, you need 9 cells because every vertical column will have all 3 combinations in it and every row will have all 3 combinations.
		So you will be able to look at the three combinations in the context of each of the three mutation patterns. and each of the three other factors that you're looking at.  But you do not get the full robust number of comparisons that you can make with a factorial.
		ACTING CHAIRMAN GULICK:  Dr. Mellors?
		DR. MELLORS:  Martin, factorial design is appealing for many of the reasons you outlined, but one of the issues always becomes that you can be powered to assess differences across the factors but not between the individual cells and that what happens is you get underpowered cells that may be of particular interest.  And when you power those cells for inter‑cell comparisons, your sample size becomes enormous.
		DR. SCHECHTER:  Yes, that's an issue.  I guess the thing to say about factorial designs is that if you were to have one burning clinical question and have 300 patients to answer it with, probably you would not want to dilute that through a factorial design.
		So the efficiencies of factorial design only can be fully gained if you're willing to go up marginally in sample size because if you have 300 patients, you might be able to answer 3 questions with them, rather than one.
		So I don't want to deceive anyone that with the same number of patients by using a factorial design, you achieve the same amount of power on the within‑self comparisons.  That's not true.
		But if you were willing to increase your sample size overall or go multi‑center, you can with an increase in the number of patients answer far more questions than you could if those patients were distributed among three different questions at three different places.
		ACTING CHAIRMAN GULICK:  Okay.  Thanks again.
		Our next speaker is Dr. Coleen Cunningham from SUNY Upstate, who will be talking about trial design options in pediatrics.
	OVERVIEW OF TRIAL DESIGN OPTIONS:  PEDIATRICS
		DR. CUNNINGHAM:  Thank you for the invitation to speak here today.  I have a very difficult task following that excellent presentation, and I hope I manage it well.
		I just want to say that I was told my main job here was when discussions get around to trial designs and proposed studies that just every five or ten minutes, I'm just supposed to say, "Then don't forget the child."  So that part of the job I will have no trouble with.
		And I hope that in these few minutes I can give you ‑‑ I won't wander away from it ‑‑ some of the issues related to pediatrics that I was asked to cover.
		Before I forget, I also want to thank Steve Spector and Tory Rendon from the PACTG, who gave me some updated information about actual numbers that are available at clinical trial sites.  So when we talk about pediatric numbers, I have some hard data.
		The three bullets that I was asked to cover today were to talk about:  the epidemiology of treatment experience in pediatrics; how does the smaller number of HIV‑infected children, as compared to adults, impact on trial designs that are feasible; and how does management of HIV disease in children impact the type of trial design options, as compared to adults.  I will try to cover each of those three areas quickly.
		So, first of all, to talk a little bit about the epidemiology of treatment experience in children.  I can't tell you nationwide exactly how many children have received what combination, but I can tell you that the vast majority of HIV‑infected children are multi‑drug‑experienced.
		And because of the evolution of drug availability in this country, the majority, or at least a large number of kids who are infected were exposed to sequential mono, dual therapy and then combination therapy, or at least dual combination, then triple combination.
		There really are three major factors I think that account for or that explain why our current population of children has the treatment experience that they do.
		First of all is the evolution of treatment.  Second of all is, although that evolution of treatment may not be optimal compared to what we do today, it did allow for increase in survival of children who were alive and ill with their HIV disease in the '90s.  We now have significantly decreased mortality, and many children are living longer and, therefore, exposed to more drugs over that time period.
		Finally, we had the fortunate experience of having relatively few newly infected infants.  As I will show you, there really is a limited number of newly infected young infants, not to say there is none but the numbers of young children who are treatment‑naive is becoming smaller all the time.  And so we have a sort of pool of kids or population of kids who are growing older and seeing more and more drugs.
		Next slide, please.  So first I want to cover the evolution of treatment in pediatrics.
		You can go to the next slide.  As most of you also have experienced, treatment evolved over the '90s.  In the early '90s, we were often using AZT mono therapy because that is all we had.  We then went to combinations including AZT/ddI, AZT/3TC.  The first PI that was extensively used in pediatrics was ritonavir.  And the three‑drug regimens really came into relatively common use around '97.
		Next slide.  I just want to show you some data from PACTG 219, which is a long‑term follow‑up study, of children.  Previously to be enrolled in this trial you had to be a child in another PACTG study.  And then you went on to 219, which included follow‑up to age 21.
		So there is some bias in that if you were enrolled in this trial at this time point, you had to have been on some study and, therefore, probably were more likely to be treated than the kids that didn't go on this study.
		However, this is follow‑up data on children that were enrolled into that study, HIV‑infected children that were enrolled onto that study, prior to January 1st, 1996.  And as you can see, in 1995 there was virtually no PI use.  By 1997, 30 percent of the children were on some PI.  And in 1999, over 70 percent of the children were on some PI.
		Certainly kids have been on triple combinations and MegaHAART therapy.  Unfortunately, many of the kids had some experience to nucs prior to going on the triple combinations.  And so the success rate of treatments has not always been optimal.
		Next slide, please.  This evolution of treatment has led to a decreased mortality.  More of the infected children are surviving for years.
		Next slide.  From the same study and the same cohort of  infected children that were enrolled prior to 1995, as you see, over time mortality in 1996 ‑‑ and this is percent per year.  I'm sorry.  When my slide converted to this, some of the things got omitted.  But you can see the mortality is less than one percent in 1999.
		Next slide.  That mortality decrease occurred across all racial and ethnic groups.
		Next slide.  And it also occurred across age groups.  The yellow bars are the youngest age group, the two to six‑year‑olds.  The blue bars, not a good choice of colors, but the 6 to 13‑year‑olds, also declines.  And the over 13‑year‑olds declined not quite as much.  Many of those children have been infected for a long time.
		Next slide.  Finally, data that shows the relatively limited pool of newly infected kids.  And, again, this is a slide that didn't quite convert right, but prior to 1993, historically the transmission rate in this country is roughly 25 percent.
		And that is what it was on the placebo arm of PACTG 076.  The HIV transmission from mother to baby was eight percent in AZT mono therapy, as shown in 076.
		PACTG 185, the transmission rate in both arms was 4.8 percent.  And the results of 316 are not officially available, but we do know that the transmission rate was significantly less than the 5 percent hypothesized for the study.  So I put three percent in there.  But we know that the transmission rate is continuing to decline in this country.
		Next slide.  So, to wrap up the epidemiology part of the discussion, children with HIV in this country are primarily treatment‑experienced, often multiple class‑experienced, and may need also sequential mono and dual nucleoside therapy.
		Exploring options for the treatment‑experienced children is critically important for these children in order to provide care for these children.  We really have to evaluate treatment options, management strategies, and effectiveness of every new agent in this population.
		Now to talk a little bit about how many infected children are there and whether or not that would impact on trial design and are these children potentially available to participate in clinical trials and what age groups are available.  And I just want to show you some data from PACTG.  This was collected within the last month.  So it's quite current.
		As most of you know, the Pediatric AIDS Clinical Trials Group is made up of two separate subgroups that really function as one working entity.  The NICHD tends to represent the smaller sites and has 28 relatively small sites.  Those sites report that they care for a total of 2,671 infected children.  Of that total, 413 are new children; that is, new, infected children that presented within the last year, and 1,213 are adolescents.
		Among the NIAID sites, there are 23 sites that care for 5,800 infected children, 736 new, and 1,738 adolescents; so overall, over 8,000 infected children who are currently in care at PACTG sites.
		Next slide.  The racial and ethnic breakdowns of the children are available.  I just want to point out in the infant category here, the zero to 23‑month, the vast majority of these children are babies born to HIV‑infected mothers.  Very few of them will end up being HIV‑infected; so would not obviously be available for treatment trials.
		Next slide.  How do the numbers impact on trial design options?  I think that there is a very, very limited ability to do pediatric studies in treatment‑naive children.
		Any studies that could be done in that population would be very small focused and really targeted to ask very specific questions.  However, I do think that the number of experienced children is much greater.
		And, really, a number of efficacy studies could be done, particularly if endpoints were virologic and not clinical.  We definitely need pharmacokinetic safety and activity data, and we have the numbers of children to be able to collect that data.
		Next slide.  I just want to spend one minute talking about some of the treatment issues that are unique to pediatrics.  Why do we even need to do these studies in children?  Why can't we just take what you learn from adults and go on our merry way, take care of the children?  Because there are a number of things about children that I can't just take your data and use it.
		First of all, I don't know the dose to use.  You cannot predict pediatric dosing based on adult pharmacokinetics.  Really, I don't just have to answer the pharmacokinetics for sort of the generic adult.  I have to know the dosing, the appropriate dose, for a 2 and a half‑kilo 4‑week‑old and the appropriate dose for a 100‑kilo 14‑year‑old.  It's a huge range.  The dose and a number of pharmacokinetic parameters will vary greatly across that range.
		Dosing the volume, palatability.  I don't mean to pick on one particular PI, but all the PIs taste terrible.  And I just want to ask you if you have all tasted some of the liquid PIs.
		Imagine giving a large volume of liquid ritonavir to a child several times a day.  It's a huge issue.  I actually want to point out that that's a reason that the placebo comparators really just can't be done in these pediatric trials with a liquid preparation.
		The frequency issues.  We have to fit things into school schedules.  Toxicities may be different in children.  I think, fortunately, my general experience is things have been better tolerated in children.  At least they don't complain quite as much as adults do.
		Certainly long‑term toxicities, the lipid abnormalities and the mitochondrial toxicities, those exposures over years may be very different in a child than they are in an adult.
		I think I'm almost done.  Just some other issues that are somewhat different.  Pretty much all the children are dependent on an adult to have the medicine delivered.  And that may lead to better adherence.  It may lead to worse adherence.  That's obviously going to be different than what you see in adults.
		Children have frequent minor viral illnesses, the common viral crud, as I like to call it.  These are illnesses that every child gets but may lead to a couple of days of vomiting or a couple of days of inability to eat.  And those kinds of treatment interruptions are incredibly common in pediatrics and may affect drug usage.  Children are exposed to a number of other antibiotics and medications on a relatively frequent basis.
		And some general comments.  Just viral load set points and CD4 counts, both are generally much higher in pediatrics and make patient selection and trial design issues a little bit different in children as well.
		In summary, I really want to remind people that pediatric trials really must run concurrently with adult trials.  When you have decided that a drug works in adults, we can't then just start from scratch doing the evaluations of treatment in children.  That will put the children's treatment a couple of years behind adult treatment, and that's not appropriate.
		We must have pediatric formulations available for all drugs.  The PK and tolerability, which clearly includes palatability, and safety data must be available.  We need to understand long‑term safety.  And we do need to evaluate different management strategies.
		The last slide is just a plug that, really, the majority of the trials carried out, actually, in the U.S. have been within the Pediatric AIDS Clinical Trials Group.  And there really is a large number of children currently in care at those sites.  A number of trials could be done and really must be done to address many of these issues for children.
		So thank you.
		ACTING CHAIRMAN GULICK:  Thanks, Dr. Cunningham.
		(Applause.)
		ACTING CHAIRMAN GULICK:  Are there one or two burning questions for Dr. Cunningham?
		(No response.)
		ACTING CHAIRMAN GULICK:  Okay.  Thank you.
		Next is Mr. Carlton Hogan from the CPCRA and the University of Minnesota School for Public Health to present a patient perspective on salvage trial design.
	TRIAL DESIGN OPTIONS:  PATIENT PERSPECTIVE
		MR. HOGAN:  Good morning to the Committee and to everyone else.  Thanks for having me here.  I am a member of a group called the Coalition for Salvage Therapy.  And a great deal of what I say is going to represent positions of that group in those areas where perhaps my personal opinions may differ a little bit or areas where we have not accurately discussed, I'll do my best to clarify so that the two agendas don't get mixed together.
		There is a definitional problem in what is a true salvage patient.  We have seen a number of ad hoc definitions of salvage.  I say "ad hoc" because they sort of have appeared in eligibility criteria, have not been formalized in any sense.
		Some of these we would not consider salvage patients, NNRTI‑naive, experienced with only two protease.  These are clearly patients who have exhausted some of the armamentarium, but it would be premature to say they have exhausted all of the armamentarium.
		What we provisionally use as a definition of a salvage patient within the Coalition of Salvage Therapy is a person who cannot achieve an adequate virological response given the existing agents.
		And it is our very strong and heartfelt conviction that, as difficult a group as this is, as unlikely as it is to see a response in this group, as challenging as this is for regulatory trials, this is our number one priority in HIV therapeutics right now.
		A lot of us who were able to control the virus to some degree using existing therapies have some coast time.  There are people who do not.  And so for the purpose of Coalition of Salvage Therapy, we are focusing on persons who have no conventional treatments left available to them.
		Next slide, please.  Just to talk a little bit about the Coalition of Salvage Therapy, it's an ad hoc coalition.  I think it is safe to say we have members of all the major AIDS activist groups involved.  As I said, we focus on patients with few or no viable options.
		One of our biggest interests and where we have expended a lot of effort is to facilitate inter‑sponsor collaborative research.  I'm happy to say that to a very substantial degree, industry has been very responsive and has really been willing to try some new things to challenge themselves to rewrite the play book.
		So we really appreciate that and offer our thanks to those companies that have been willing to entertain these ideas.  We feel it's incredibly important that for persons who have no options and who may or may not be eligible for current trials, that there be some form of a limited expanded access.
		We're not talking ddI expanded access with 20,000 patients.  We're talking about very limited expanded access simply for those people who really need a new option now.  We feel that this is an important consideration.  We would like to see it occurring earlier than it has been recently.
		The last few drugs which have had expanded accesses, we have seen expanded accesses open up very, very shortly before registration.  We feel that while that might be within the letter of expanded access, it's not within the spirit.  And we would like to see earlier access to these therapeutics for patients who have no other options.
		Next slide.  We're uncomfortable with studies that involve patients, salvage patients, as we have defined them being on mono therapy or what we call virtual mono therapy for any substantial duration.  By "virtual mono therapy," we mean merely adding one new agent to an already failing background therapy.
		We do understand the scientific issues involved.  We understand the need to get clean PK and pharmacodynamic data, to get initial indications of activity before we look at efficacy.
		These are not issues which we blithely dispose of.  However, we feel very, very strongly that where these studies need to be done, patients need to be exposed to those agents as mono therapy or virtual mono therapy for as short a period as possible.
		Some of this has come under the rubric of intensification trials.  Again, this is a term that is poorly defined, and I think you would get probably half a dozen definitions of what an intensification trial is if you asked half a dozen people in this room.
		By "intensification trial," we mean exactly what we were talking about about mono therapy, merely throwing a new drug on top of a failing regimen.
		Beyond the concerns which we have already said, there is certainly inherent futility in this approach.  What are you going to keep doing:  add a drug, wait until it fails, add another?
		I mean, we already have people on eight or nine drugs.  We are getting to the point where it is possible that we are going to end up killing them off of therapy before they actually get a virological response.
		So, I mean, it's reductiu ad absurdum, but it is important to realize that intensification as a primary principle of therapy is inherently futile.
		Next slide.  These are issues which I have already touched on a little bit.  We would like to see some of the pharmacodynamic stuff done in HIV‑negative patients if it's possible.  We understand the drug interaction stuff probably cannot be, but wherever possible, persons in earlier stages of disease, patients who are HIV‑negative, it would be very nice to see as much of that research as is scientifically feasible be done on those populations.
		This may be overly optimistic, but we have got people who are willing to enroll in research studies and enroll in PK or pharmacodynamic studies which are among the most intensive designs in terms of patient involvement, in terms of what you are asking from the patient.
		So this is a population that clearly is eager and willing to be research participants.  And they offer opportunity to look at the persons who first got on the drug.  If these people are maintained on drugs, they will have the longest exposure of anybody out there.  So, wherever possible, we would like to see longer‑term follow‑up with those studies.
		I need to sort of bracket that point and say this is perhaps ‑‑ I can't speak to whether that's the coalition's position or not because we haven't actually discussed that exact, specific issue, to my knowledge.
		Next slide.  Concentration‑controlled trials.  Well, it's obvious to everybody in the room that there are a staggering number of determinants of successful therapy.  Just in the past couple of years, we have become aware of the importance of things like cytochrome p450.
		Protein‑binding, of course, has sunk I don't know how many protease inhibitor candidates.  Just recently, there is a growing interest in p‑2 glycoprotein.  And we feel that this may be a very significant area in relation to toxicity.  So we would like to see more research in there.
		Impaired gastrointestinal function certainly in later‑stage patients may be a very important determinant of therapy.  There are differences between intracellular and extracellular concentrations.  Very important to us, very, very important to us, is the effect of hepatitis and other comorbidities on drug absorption and retention and other perhaps unknown drug and food interactions than those that are listed above.
		Next slide.  So in regards to these type of studies, some of the questions that we feel that are important, need to be looked at are:  What are the implications of transient dips below therapeutic levels?
		We have seen dosing schemes of some drugs in the past few years where there are brief periods during the day where, in some patients at least, the drug does drop below what would be considered an adequate therapeutic level.  How important is that?  How long a duration can that be tolerated for?  How significant is that?  It's just something where there is no clarity on.
		I think everybody feels a concern about it, but I personally am unaware of very much research that really looks directly at that issue.  Of course, the big issue this year is:  Can resistance be overcome by increased drug concentration?  It seems like fairly soon Baskin Robbins is going to be offering ritonavir ice cream the way it is being added to every possible combination out there.
		Whether simply increasing drug concentration can overcome resistance is probably a very nuance question and very drug‑dependent.  And, again, this may perhaps represent my concerns a little bit more than the coalition's.
		I have real concerns about blockading p450 for four, five, six, seven years.  We have no idea what the effects are of doing that.  Over the history of evolution, plants have sort of developed various things to keep us from being limp.  We developed more sophisticated livers to be able to process this stuff.  And there is a reason for those liver enzymes.
		I personally believe that blockading p450 may even open up the possibility to toxicities from some foods.  Now, that's sheer speculation, of course, but it illustrates the fact that we really just don't know what this means.
		Of course, when you add in the concomitant medications, we have already seen the enormous complications of balancing drug levels in people having to get therapeutic drug monitoring to adjust some of their concomitant medications in the presence of ritonavir or other potent inhibitors.
		Next slide.  There is probably more research into this, but we would like to see it even more clarified.  What is the variance between individuals, not only in drug concentrations at particular points in time but sort of over the day of the dynamics?  Of course, all of the other factors, like concomitant medications, will impact that to a substantial degree.
		Is it the case that there is a point of balance between simplicity of dosing and adequate or over‑adequate drug levels?  I mean, is there some sort of trade‑off where maybe one‑state dosing will improve adherence to the point where it may overcome the fact that there are transient dips in level?
		This is an open question.  We don't know, but there is clearly going to be some balance between adherence and drug concentration as we get to these simpler and simpler regimens that are taken less and less frequently.
		This next point, to my knowledge, we have not discussed in the Coalition for Salvage Therapy, but it's a great issue of mine.  Do what degree are we seeing host resistance?  For people who have been on nucleosides, for example, for a decade now potentially, what is happening to their ability to phosphorylate nucleoside enzymes?  There will probably be other host resistance phenomena that will crop up as we study these drugs over longer and longer periods of time.
		Clearly there are new equilibriums established in terms of having action.  Does that, in fact, raise the risk of some host resistance phenomena as well?  Of course, inducer drugs, drugs that induce p450 cytochrome, will complicate this issue even more.
		We're now looking at the option of some treatments that simply cannot be administered orally.  How much is compliance going to differ from oral compounds?  What is going to be the virological impact of that difference in compliance?
		It's our sense that for patients who are truly in a salvage position where they really cannot get their viral load down, that they are more likely to be highly compliant with injection regimens.  This is speculation, of course, but we feel like people who are aware that this may be their last chance are going to be a little bit more careful.  In less severe populations, we are very curious to see how treatments will be accepted that are not administered orally.
		Next slide.  There are some real priorities out there.  At the moment, perhaps the salvage population to the research community, to industry, to patient groups is sort of a niche group or a minority group.  We fear this may not be the case indefinitely.
		We have now seen documentation of drugs resistant to each of the three classes separately and transmission of drugs resistant to all three classes.  Of course, there is an artifact of survival, not that I'm speaking out against survival, but the fat is the longer you survive, the longer you are on drugs and have an opportunity to acquire resistance.
		So the group of patients that are highly resistant to therapies we believe is going to grow and become a very substantial proportion of patients who are being treated.
		Next slide, please.  This gets back to our definition of salvage.  We have seen some studies recently that are important to salvage trials that we feel really are not salvage trials.  We are glad these trials occurred.  They were important trials.  But they don't address the group of our greatest interest.
		Parenthetically, I mean, we do understand the reservations.  We do understand the difficulty of seeing a response, the enormous number of confounding factors in salvage populations.  We're not blithely rushing that stuff aside.
		But, again, our priority is persons who are at imminent risk of serious illness or death.  And we're not going to back away from that.  So we're going to work with you to figure out solutions to those very real problems, which we're not just brushing them aside.  We understand they are there.
		Next slide.  It is our strong contention that any enzymes that offer only one novel agent are very unlikely to succeed.  The great risk there is suppose you have salvage agent A available today and salvage agent B available in six months.  Patients starting A now may end up ruining their chance of getting a very powerful response from the combination of A and B.  So, wherever possible, we would like to see more than one novel agent be used at a time in salvage populations.
		Again, we are going to talk a little bit about the design issues in a moment.  We are not being pie in the sky in saying this is easy and you guys should just be giving us drugs and drugs in the bodies.
		We understand there are safety issues around this.  However, it is really not in patients' interest to acquire resistance to new therapies before they can be used in adequate combinations.
		It has never been easy to coordinate trials with multiple sponsors, but in the last year, there has really been a sea change.  We really have to offer a lot of credit to companies like Abbott, Gilead, Trimeris that have been willing to talk to us about these issues, have been willing to entertain the idea of overlapping expanded accesses, possibly salvage trials from more than one experimental agent.
		But, you know, we understand these companies are businesses.  Their primary goal is registration.  So what we absolutely need ‑‑ and if there is one key point I think the Coalition for Salvage Therapy would like to bring forward at this meeting, we need strong guidance from the agency to industry about how if it is possible to use multiple experimental agents in a registrational trial and what the parameters of that are.
		We want everybody to know what the rule book is and so the industry can go into these trials and know to what degree they can put this trial into the registrational packet and have it serve their ends as well because the drug companies are not charities.  They're in to get their drugs approved.  And they need guidance on how to do this sort of work and still achieve their goals.
		So our message to you folks at FDA is you really need to come up with some very clear‑cut rules and make industry aware of those rules and sort of give a very clear view of the playing field.
		Next slide.  Background therapy in salvage trials is really a challenge.  The heterogeneity of previous treatment regimens makes it just about impossible to come up with a background therapy.  I doubt you could find any two patients with identical treatment histories in every a very large HIV clinic.
		We feel that background therapy needs to be flexible.  And we would like to see it individually optimized using phenotypic and genotypic resistance.
		There are some confounding issues here.  However, in properly randomized trials that are adequately powered, we think that this is achievable.
		And preservation of future treatment options vis‑a‑vis later combinations should always be a strong consideration.  And it might even be a useful endpoint for some of these trials to look at the end of the trial at what the resistance profiles are and whether one drug may have offered a clinical benefit; yet, impacted the future course of treatment by increasing resistance.
		We think it is very important, and we urge that it be considered as a secondary endpoint in trials to look at resistance at the end of the trial.
		Next slide.  Assuming we get several sponsors to support a salvage trial, we would like to see that trial produce the most information.  We would like to optimize it and milk it for what it's worth.
		In the case of two experimental drugs, such a study might look like background therapy versus drug A plus background therapy versus drug B plus background therapy plus A plus B.  This is a classic factorial design on top of optimized background therapy.
		I need to insert the note that some of my colleagues are uncomfortable with this and are uncomfortable with the optimized background therapy arm.  So there is not a clear consensus on this.
		But this is a true factorial on top of background therapy.  And it will allow us to assess not only the relative contributions of A and B on top of background therapy comparing them to each other but also comparing those to the combination.
		What we prefer is what we call a modified factorial.  Unfortunately, that would be a very difficult concept to implement with only two experimental drugs available.  It is really much easier to conceptualize with three drugs.  It is possible, but you end up losing what is probably an important control arm in doing so.
		Next slide.  So when we talk about a modified factorial trial, a traditional factorial with three factors would be nothing.  The three factors would be the combination of two factors and the three factors together.
		What we would propose is knocking out all of the mono therapy portions of that.  So it would be all of the two‑drug combinations versus the three‑drug combinations.  And the comparisons you would make would be, for example, all arms containing A to arms not containing A, all arms containing B to arms not containing B.  This also will give us some preliminary information on which combinations of these drugs are more likely to be successful.
		Next slide.  As I have undoubtedly hammered home many times, there are advantages and disadvantages.  The clear advantage in our mind is that such a study may offer a better chance of virological control in every arm and reduce the risk of persons being harmed by clinical trials.
		This is a very important consideration to us.  We understand the need for good data.  We don't want to see people harmed doing it.  And we would be the last to say that that is an easy paradox to reconcile.
		This sort of design may delay further resistance to both the study agents and the elements of background therapy if there isn't complete resistance to those already and may allow median rank to the relevant merits of the various combinations.  It's also a design that would be very, very attractive to potential participants.
		Some of the disadvantages are that there is no true control arm in the study.  There is no optimized background therapy alone arm, which scientifically ‑‑ I mean, I look at this with two hats.
		Scientifically I think that that is problematic.  However, in the case of patients where there truly is very, very little chance that optimized background therapy is going to make any difference at all and there is imminent risk of serious morbidity or mortality, the rules may have to change a little bit.  And the studies that actually are truly well‑controlled may have to be done in slightly earlier populations.
		There is an exception to that.  And here I need to stress that this is absolutely my own opinion and not that of the Coalition for Salvage Therapy.  I do think that there is room in patients.  We simply do not see virologic response to do no‑drug comparisons or placebo comparisons to see whether in patients who when we're not affecting the virus we're analyzing these drugs on, we're merely harming.
		I need to stress that is not the coalition's position.  It is mine.  But I do think when we're not seeing a virologic response in people, it is very legitimate to ask:  But why are we giving these drugs in the first place?
		Other difficulties with this design are it is going to be more difficult to conclusively ascribe adverse events to any one agent.  And if even this combination does not achieve virologic control, patients may have to endure more toxicities without commensurate benefits, but, of course, that's a risk in any trial.
		Next slide, please.  Endpoints.  Well, in a true salvage population, percent below level of quantification is just not a realistic endpoint.  Powering the trial will be extraordinarily difficult because it's very unlikely that you're going to get a major proportion of patients who do go below level of quantification.  And so change in RNA may be a much more powerful and meaningful endpoint for such trials.
		Where clinical endpoints are considered, the classic composite endpoint of progression or death may not be as relevant in these patients.  It may be important to include major toxicities.
		We're going to talk about lipodystrophy but things like major cardiovascular disease, incompetent clinical endpoints where clinical endpoint studies are done.  So something along the lines of progression, major cardiovascular disease, diabetes, or death would be a possible clinical endpoint.
		In any study that is done, we feel secondary endpoints should be rates of genotypic and phenotypic resistance to both the study agents and the background therapies.  The issue here is that we are very interested into whether the study agents may actually preserve some of the benefit of the background therapy should any benefit be left.
		Since we are in general defining these folks on the basis of a lack of virologic movement, HIV RNA may not be the primary endpoint.  Also, as I speak to Dr. Deeks right here, there are some folks with elevated RNAs who seem to be doing pretty well.
		So it may be realistic to think about preservation of CD4 count as endpoint in trials intra‑salvage patients as opposed to changing to HIV RNA because we may not get those changes in HIV RNA.  Yet, the patients may still be seeing some benefit.
		Next slide.  Some what do we need from the agency?  Well, as I said in the beginning, sponsors need clear, unambiguous guidelines about what sort of novel studies are to be used in support of the NDA and perhaps even some over‑encouragement to seek salvage indications.
		We need open discussion into what the incentives are for research into further niche populations, pediatric, injection drug users, and so forth.  We need a commitment from everyone in the room to encourage and do meaningful expanded access programs, especially in the salvage population, and not just weeks before licensure.
		To open the expanded access program two weeks before the drug is on the shelves is basically a slap in the face to the community.  And it does you more harm than good in our eyes.  It's not the intent of expanded access, and it's not okay with us.  If you're going to do expanded access, get it out there as early as you can.
		Co‑enrollment of expanded access programs.  This is something that has just been piloted this year or at least theoretically became acceptable, although it has not been actualized yet.
		We heartily applaud this.  And we would like to particularly tip our hats to Abbott because we feel that they have been the people who have actually had drug out there and have said:  We have drug in our hands, and we are willing to do it now, as opposed to other companies who have said:  Yeah.  Well, we're into this in principle, but we don't have drug for you right now.  Abbott said:  We have lopinavir.  We will do it today.  And so we applaud them for that.
		Next and last slide.  This is perhaps my own diatribe.  Long‑term follow‑up in AIDS trials has been an absolute disgrace.  Even before the accelerated approval regulations were loosened, very few sponsors fully fulfilled their post‑marketing requirements.
		This is not an abstract or a purely political issue.  None of the major protease inhibitor toxicities were seen prior to registration in terms of things like lipodystrophy, cardiovascular disease, insulin resistance.
		I mean, we are aware of the elevated triglycerides but certainly the other more serious, life‑threatening toxicities did not show up in those pivotal trials.
		Now, we are glad those pivotal trials occurred quickly.  We're glad that there was such unambiguous indication of benefit.  The drugs were on the shelf.  We would also like to see longer‑term follow‑up to see what the effects are of prolonged exposure to these drugs.
		I mean, you look at some cases like AZT myopathy.  I don't think that was actually formally recognized until five years after AZT was licensed.  That's not acceptable.
		Of course, during the AZT/DTC/ddI years, those were when the emphasis on Phase IV trials was much stronger.  And even then, we didn't see full compliance.
		We feel that this is not entirely a problem of the agencies in that you guys don't have the administrative tools to force compliance with Phase IV commitments.
		I mean, basically you can pull a drug off the shelves or you can leave it on the shelves.  And so I would hate to think that we would have to go to legislation on this, but we do feel it's important that the agency have some means of coercing that compliance with Phase IV commitments.
		We're not exactly sure what that would look like, whether it would take the form of fines or incentives or how that would work, but we would really like to see some formal mechanisms for the agency to enforce Phase IV commitments.
		This is particularly important in salvage patients, where it is quite possible there may be no virological indication response and, yet, there may indeed be a clinical benefit or there may indeed be a clinical harm.  And it will only be longer‑term studies that will determine that.  So, especially in populations where you really don't get a good virological comparison, we feel that long‑term BOP is very important.
		I think that basically hits all of our major points.  Any questions?
		ACTING CHAIRMAN GULICK:  Thanks very much.
		Are there questions?  Mr. Levin?
		MR. LEVIN:  Jules Levin.  I think it is important to fully appreciate that the community is diverse and the opinions are diverse.  Okay?  So I just want to comment on one thing that Carlton talked about, and that is factorial designs.
		I don't think ‑‑ and other community people agree with me ‑‑ don't think that they ‑‑ not only that they are not useful, but I think they are counterproductive, a waste of resources.
		And I don't think that an optimal regimen ‑‑ first of all, there are no three drugs right now for salvage therapy available right today.  But if there were, I certainly don't think it's an optimal regimen to take standard of care plus A versus standard of care plus B plus standard of care plus three.  That is not optimal therapy.
		I would not enroll in a study like that, and I wouldn't like anyone with HIV, my best friend or my worst enemy, to enroll in a study like that.
		ACTING CHAIRMAN GULICK:  Ms. Dee?  Thanks, Jules.
		MS. DEE:  Lynda Dee from AIDS Action‑Baltimore, the Treatment Action Group.
		First of all, I would like to reiterate what Carlton says, that the consensus except for, Jules, as I remember, on the Coalition for Salvage Therapy was that factorial designs were very good for this population.
		I think the problem is that we know that people, the true end‑stage, late‑stage salvage patients are going to need more than one drug with an optimal background regimen.
		The problem with the drug companies has been that many of the drug companies are willing to work with another drug company to use two investigational drugs in one trial, but they haven't known what these trials are going to or should look like for the agency, what the agency is going to accept in order to get their compounds registered.  I mean, it's just as simple as that.
		I would assume that since we have had Dr. Schechter's wonderful presentation today, that that means the agency has put their imprimatur on these kinds of factorial designs and that maybe the agency will indicate with the sponsors in their discussions that these are acceptable ways to answer a couple of questions at once, to get more bang for your buck, and to offer three drugs ‑‑ excuse me ‑‑ more than one drug, two drugs, two or three, to this population.
		I would also say that the Coalition for Salvage Therapy disagreed with Carlton with respect to the placebo cell.  And we thought that maybe a structured treatment interruption might be more appropriate there.
		And as far as the post‑marketing Phase IV stuff, I mean, I think that the agency just has to ask the sponsors.  I think that you have that authority and you have that power.  And I just think that sometimes you don't realize what power you have to say, "Look, this is what we want."
		I mean, look at the EMEA.  They said, "We want to know about lipodystrophy.  We want to know what it means, definitions of it," and they're doing it.  They're doing it.  The sponsors are doing it among themselves, paying for it themselves.  I think you just have to be a little bit more firm or proactive.
		In the United States, these issues are very politically, but hopefully, especially now with this new administration coming in, you will require the sponsors to do what the accelerated approval mechanism requires, and that is post‑marketing studies.
		ACTING CHAIRMAN GULICK:  Let me stop us there at that point.  We're going to have plenty of more opportunities today to get into some of the issues in terms of discussion.
		I would like to thank the four presenters for their talks this morning.  Let's take a ten‑minute break and reconvene at 10 of 10:00.
		(Whereupon, the foregoing matter went off the record at 10:38 a.m. and went back on the record at 10:55 a.m.)
		ACTING CHAIRMAN GULICK:  Welcome back from the break.  We're ready to reconvene.  I wanted to give Dr. Jolson an opportunity to respond to some of the comments that were made right before we went to break.
		DR. JOLSON:  I thought it would be worthwhile before we went on to respond to a couple of the comments that were raised just before the break.
		I think there are two important issues.  We're going to be talking a lot more about these as the day goes on.  So it's probably worth just presenting the agency's perspective in a nutshell.  And then as Dr. Laessig speaks, she is going to be talking more about the regulatory perspective.
		The first issue that was raised was:  In concept is a factorial design acceptable to the agency?  I know that we have gone on record in a written letter in 1999 to industry that we were extremely supportive of this approach because we think that it provides interpretable trial data and also, importantly, provides access to more than one novel agent for a patient because we are extremely concerned whenever we see trials such as either intensification studies or single‑drug, add‑on therapies that they are not providing optimal therapy to patients.
		We have consistently articulated that issue whenever we're approached with a trial design.  So I think we would be very, very supportive of trials that can accomplish both providing interpretable data and satisfactory treatment alternatives.  And we have gone on record with pharmaceutical companies in that respect.  Dr. Laessig when hopefully the proxima is fixed is going to be discussing more about that.
		The second is the issue of Phase IV commitments.  This comes up all the time in terms of what is our regulatory authority vis‑a‑vis Phase IV commitments?  When I say "our," I mean FDA as a whole.
		There were two types of Phase IV commitments, and they have different legal teeth.  One is the accelerated approval commitments, which are 100 percent binding.  And if a drug company does not follow through with those Phase IV commitments for accelerated approval, the drug can be withdrawn from the market.  And that is a legally binding Phase IV commitment.
		So drugs that you have seen that have gone through the accelerated approval process, ‑‑ for example, nelfinavir comes to mind as one that has recently gone from accelerated to traditional approval ‑‑ it is by living up to that mandatory Phase IV commitment.
		The other Phase IV commitments, the more typical types of things to do additional studies, it needs to be recognized that we ask for those.  However, they are not legally binding.  That's something that is in the law, and that really needs to be understood.
		We have routinely been asking as Phase IV commitments for data on treatment‑experienced patients.  And, by and large, sponsors have worked with us in good faith.  But it needs to be understood that there is a limit to what we as an agency can require.
		A lot of our time and energy is spent with working with companies and providing other incentives to get them to live up to their Phase IV commitments in a timely way.
		MR. HOGAN:  Dr. Jolson, just a quick comment.  I would hate to think that I came across overly critical of the agency because we do recognize the enormous progress you guys have made and how aggressively you're confronting this issue.
		Our concern is that withdrawal of a drug from the shelves is a very drastic step.  It would be very nice if there were some intermediate administrative remedies because nobody wants to see a drug go off the shelf.  Certainly it's of no service to the patient population to do so.
		DR. JOLSON:  Right.
		MR. HOGAN:  And, I mean, there are cases.  There was an example of one of the nucleosides where they went four or six years before they fulfilled their clinical endpoint trials.  So there has been some abuse of the system.
		We would like to see you guys have some tools to deal with that because nobody wants to see drugs pulled off a shelf.
		DR. JOLSON:  In general, we agree with you.  And, as you know, to date no drugs from accelerated approval have been withdrawn.  There are actually very few that still remain under accelerated approval.
		The way that we encourage that to be done is through incentives.  Labeling is a very, very powerful incentive.  So to have, for example, 16 or 24‑week clinical trial data in the label is not a very meaty label when it comes to trying to advertise the drug.
		There is a strong incentive to put longer‑term, more clinically relevant data showing prolonged viral suppression or whatever the endpoint is.  That's really almost the best incentive to get companies to develop longer‑term data.
		MR. LEVIN:  Just one brief thing.  Certainly I don't want drugs taken off the market either.  You sort of made a line between what is enforceable with Phase IV and what is not.
		DR. JOLSON:  Right.
		MR. LEVIN:  And I think that line is where you're talking about, things like, for example, we have no real studies on hepatotoxicity on HIV medications at this point.
		That's sorely needed.  I don't see it being even really discussed very fervently.
		DR. JOLSON:  That's a fair point.
		ACTING CHAIRMAN GULICK:  Why don't we stop discussion at this point.  We'll come back to these points.  I would like to introduce our final speaker of the morning, Dr. Katherine Laessig from the Division of Antiviral Drug Products, to speak, to really summarize the public response and regulatory perspective.
THE STUDY OF ANTIRETROVIRAL AGENTS IN
HEAVILY PRETREATED HIV INFECTED PATIENTS:
A REGULATORY PERSPECTIVE
		DR. LAESSIG:  Good morning.  The organization of my presentation is as outlined here.  I would like to begin by defining some terms that are relevant to today's discussion.
		Next I will summarize the responses we received to our request for public input regarding study components, including the patient population, study regimen, endpoints, and study duration, as well as review of specific study designs:  historical controlled, open label, and blinded intensification‑type trials, concentration‑controlled, and dose‑response, and factorial.
		Then I will elaborate on three potentially useful designs which were suggested.  These include an add‑on‑type design, a two‑part hybrid, and modified factorial.  And, finally, I will end with some regulatory conclusions.
		The heavily treatment‑experienced therapy refers to a new or recycled drug regimen that is used to treat patients who have experienced therapeutic failure for either efficacy or safety reasons.
		It is unlikely that a signal new drug will suffice as salvage therapy.  However, for regulatory purposes, the contribution of a new drug to the regimen is what is of interest.  This is in contrast to clinical management strategies, where the regimen is the entity of interest.
		And, as previously defined for this meeting, the heavily treatment‑experienced patients are those who have had previous therapy with more than or two HAART regimens containing greater than or equal to one agent from each of the currently approved drug classes.
		I would like to differentiate between a drug of last resort versus one that might have a broader use.  This is a crucial distinction because it impacts the overall drug development plan.
		A drug of last resort would have activity but might be restricted for use only in the heavily treatment‑experienced because of toxicity, a less desirable route of administration, or other reasons.  This is in contrast to a first‑in‑class or a next‑in‑class agent that could be used for both early or later treatment‑experienced patients.
		Now I will begin discussing the summary of the public responses.  Regarding the patient population, aside from the definition we have already arrived at, it was felt that there should be broad representation of these patients, including those with low CD4 counts of less than 50 and high viral loads of greater than 100,000 copies.
		In addition, aside from including patients who may have failed previous regimens due to resistance, patients who have failed due to pharmacokinetic tolerability or adherence reasons should also be included because they need new regimens as well.
		Regarding stratification, which has historically been based on viral load and CD4 count, it is probably unnecessary for extensive stratification because well‑powered and randomized trials should control for the inherent heterogeneity, although examination of patient subsets may be useful for exploratory analyses.
		Regarding study regimens, there was general agreement that resistance testing should be used to construct background regimens, expanded access agents should be allowed, and pharmacologic enhancers should be included.  There should be flexibility in the number of background agents, and pharmacokinetic enhancers should not be included in the total number of background agents.
		There is a caveat, certainly, that MegaHAART may decrease tolerability in adherence and increase overlapping toxicities, drug interactions, and number of dropouts.
		Regarding the study duration, traditional approval has been based on demonstration of durability of virologic suppression to 48 weeks or longer, and there was no feeling that this should be changed.  However, for accelerated approval, which has been based on 24‑week data, there were suggestions that earlier assessment of antiviral effect should be considered for this population with longer‑term safety.
		So, therefore, I pose the question to the Committee that:  When should we make the determination of an antiviral effect for these patients?
		Regarding the endpoints, specifically virologic, proportion undetectable may not be a feasible endpoint except when using multiple investigational or highly potent agents.
		Some alternatives which have been used in the past and may be appropriate in this setting include mean change from baseline and viral load, proportion with a greater than X log drop in viral load, area under the curve minus baseline.  And we would gladly entertain any other suggestions.
		With respect to non‑virologic endpoints, specifically clinical, these have been previously new CDC Class C events, which equate to about 20 conditions.
		Some suggested alternatives were to include fewer Class C events, specifically those that occur later in the disease process, such as CMV and MAC.  Another possibility is a composite endpoint of efficacy and safety toxicity.
		Our perspective is that there needs to be better collection and adjudication of clinical endpoints, regardless of the primary endpoint or the patient population.
		It is also difficult to weight toxicity in a composite endpoint.  For example, how would one weight nausea versus CMV?  And the agency needs to examine efficacy and safety separately to make risk‑benefit assessments.  Now I will move to a discussion of specific study designs.
		There was general agreement regarding historical controlled trials such that historical results were not obtained in equivalent populations.  This is due to the inherent heterogeneity and progressive heterogeneity of the heavily treatment‑experienced patients.
		In addition, there is an evolving standard of care.  And one could argue that there is actually no consensus on how best to manage these patients.
		In addition, there is probably incomplete data from historical cohorts to allow for adequate evaluation and comparisons, although the natural history of these patients on failing or currently available salvage therapy regimens is not disputed.
		Our position regarding historical control is that when there is a concurrent control that is feasible, a single arm trial is not advocated.  However, use of a concurrent observational cohort may be possible.
		With respect to blinded versus open label trials, there was general agreement that blinding all drugs in a study regimen is difficult due to a large pill burden, unavailability of placebo, and a consensus that resistance testing should be used to design optimized background regimens.  Therefore, partial blinding of test and control is sufficient.
		There are also multiple statistical considerations for open label studies, specifically that blinding reduces bias.  And some of the source of the bias is that patients and physicians have expectations when treatment assignments are known.
		There is a potential for differential dropout due to switches of treatment or loss to follow‑up, which need to be accounted for in the analyses.
		One method to assess the potential for differential dropout that has been used successfully is to monitor subsequent enrollment of patients in the clinical trials for a given investigational agent who discontinue that trial into that drug's expanded access programs.
		Regarding intensification trials, which were defined as adding on a new agent to a preexisting regimen with incomplete viral suppression, there were concerns on all sides that this may promote resistance because it is essentially mono therapy and it may exhaust an option that could have been used later.
		However, it may be potentially useful if resistance to an agent develops slowly.  In any event, the duration of intensification should be short and include an early escape option for suboptimal virologic response.
		Regarding concentration‑controlled dose‑response trials, the community feedback was generally favorable because this avoids suboptimal levels.  And higher drug levels may overcome resistant mutants.
		There are multiple industry concerns, including that real‑time reporting for dose adjustment in trials is difficult.  There is high intra and inter‑subject variability.  And patient adherence may impact results.
		In addition, it is unclear which specific exposure measurement is best correlated with response.  There was also some feeling that the maximally tolerated dose should be used in this population.
		Next.  Regarding the dose‑response trials, these have previously been used for registration of antiretroviral agents.  However, to discern a treatment effect is necessary to study doses on this deep part of a dose‑response curve.  Unfortunately, some participants may receive suboptimal doses.
		We certainly agree that higher doses may be necessary to suppress resistant virus.  Some of these points are illustrated by the following slide, which compares the dose‑response curves of the wild‑type, intermediately resistant, and a resistant virus to drug X.  The x‑axis shows log of the concentration of drug X, and the y‑axis shows percent of virologic suppression.
		For the wild‑type and intermediately susceptible virus, dose one and two will show a treatment response because you are on the steep part of the curve.  However, for the resistant virus, you won't see a treatment effect.  It's not until you get to dose three that you will actually see a treatment effect.
		The problem lies that we may not necessarily know how far to the right the dose‑response curve has shifted for a resistant virus.  This emphasizes the need for appropriate dose selection in the heavily treatment‑experienced population.
		Concentration‑controlled trials have not to date been used for registrational purposes for antiretroviral agents.  We agree at this time that there are assay considerations such that they are unapproved and not widely available, although this may change with time.
		Regarding a true factorial design, the industry had concerns about the potential for drug interactions overlapping toxicities, the difficulty of ensuring a timely availability of drug supply, and the ultimate ownership of IND and data.
		Although the community and FDA are in favor of this approach, the industry concerns are valid but certainly not insurmountable.  The factorial design can be modified to be useful.  And a factorial design is a randomized trial that participants are more likely to complete because they may be able to receive more than one investigational agent.
		An additional benefit is that expenses for one trial can be shared by two or more companies.  And since the company is already collaborating, blinding and provision of placebo should be easier.
		Now I will discuss three suggestions of potentially useful trial designs.  The first two are non‑collaborative studies of single investigational agents.  The first is an add‑on to optimized background regimen.  The second is a so‑called two‑part hybrid.  Then the third design is a modified factorial, which is a collaborative design for more than one investigational agent.
		So the add‑on is optimized background regimen plus or minus placebo versus optimized background regimen plus study drug.  Randomization in blinding is preferred.  However, this is a less desirable design that modified factorial due to the fact that some patients will be randomized to receive placebo and some will only receive one investigational agent.  However, the risk of patients is lessened by having an early escape option for suboptimal and virologic response.
		This is the second design, which is a so‑called two‑part hybrid design.  It's designated two‑part hybrid because for the first ten days, the patients are randomized to one of three arms.  And the second part is a prospectively designed cohort, where all patients receive the same treatment.
		The x‑axis shows time and days out to day ten and then a break in the access in weeks out to week 24.  The y‑axis is log viral load.
		Patients are randomized to one of three arms:  drug X plus their previous regimen, optimized background regimen, or their previous regimen alone.
		Next slide.  Since the trial is essentially uncontrolled after day ten, the contribution of the study drug to the treatment effect can be demonstrated by incorporating evaluation of an indirect dose‑response through the use of prospectively defined phenotypic cohorts.  In this example here, patients with more susceptible virus achieve a better virologic response, which provides evidence of the activity of the study drug.
		So, again, the two‑part refers to an initial randomization and then a prospectively defined observational cohort.  In addition, it refers to the determination of the antiviral effect, which is directly assessed during the first ten days and then indirectly via correlation with baseline phenotype for the remainder of the trial.
		Although the ten‑day chosen for this example is just arbitrary, the assumption is that the lead‑in period is brief enough so that patients on their preexisting regimen plus study drug X don't develop resistance to drug X during that period and patients continuing their preexisting regimens don't have adverse consequences due to not changing therapies sooner.
		Clearly the lead‑in period needs to be long enough to assess an antiviral effect and to demonstrate that.  This type of design probably would provide supportive evidence in an NDA package.
		The third design is a modified factorial design; in this example, a four‑arm trial for three investigational drugs, A, B, and C.  Arm 1 is optimized background regimen plus A plus B.  Arm 2 is optimized background regimen plus A plus C and so on.
		The assumption is that optimized background regimen or optimized background regimen plus a single study drug alone is inferior.  A major benefit of this type of design is at the end, it is 33 percent less than would be needed for three separate trials, this because the same active arm is compared against three control arms.
		Now the unavoidable regulatory conclusions.  The focus of today's meeting is drug‑specific and not centered on regimens or management strategy.  We need to determine what the contribution of a given drug is to safety and efficacy in broad patient populations as well as in the heavily treatment‑experienced.
		Some caveats about these trials is that we need to know the drug interactions up front and that dose selection is very important and may be different for the heavily treatment‑experienced.  In addition, the baseline resistance testing is useful for construction of the optimized background regimens and also for outcome analysis.
		Some additional points to consider are that multiple agents make determination of adverse event causality for drug toxicity difficult.  Trials of shorter duration may adversely affect the safety database.
		Resistance may develop to first‑in‑class agents and compromise later virologic response to next‑in‑class agents.  Therefore, we need to provide data for a spectrum of patients, particularly the heavily treatment‑experienced or first‑in‑class or promising next‑in‑class drugs.
		It is important to consider the overall strength of an NDA package.  One controlled study plus other well‑designed studies in the heavily treatment‑experienced may be preferable to two identical studies and naive in less treatment‑experienced patients.
		Lastly, all study designs must take into account targeted use of the drug, heavily treatment‑experienced versus all patients.
		Now I will turn it back over to Dr. Gulick.
		ACTING CHAIRMAN GULICK:  Thank you.
		Are there clarifying question for Dr. Laessig before we launch into our discussion?  Ms. Dee?
		MS. DEE:  Just one comment.  You know, in that Slide Number 3 about the three investigational drugs, for instance, we could use Kaletra as one of those drugs.  Even though it is approved, there are a lot of patients who haven't yet had the opportunity to use this drug.  So this is not always dependent on three investigational drugs per se.
	QUESTIONS TO THE COMMITTEE
		ACTING CHAIRMAN GULICK:  Okay.  Thanks.
		The way I think we should approach our discussion is to recognize a couple of things.  We are going to do the discussion actually in two parts:  one prior to lunch and then one after a few presentations in the open public hearing after lunch.  So we will probably get through some of the questions but not all prior to lunch.
		Secondly, just note from the questions that the questions for the morning really are trial design issues.  And then we're going to make a switch after the open public hearing to endpoint issues.  And it would be helpful to try to leave the endpoint issues for the afternoon after some formal presentations.
		The last request I have is that Dr. Laessig outlined three potential study designs that we will discuss as a group and others around the table have other study designs they will present.
		I think before we jump into specifics, it is appropriate to address Question Number 1 first before we get into the specifics of the individual studies.  And here we have it.
		So the question before the Committee, the most broad question, about treatment in heavily experienced patients is:  What type of information would you most like to see from studies conducted in treatment‑experienced patients, both adults and children?
		And then, as a general question, more specifically comment on the use of studies in these populations to support the efficacy for registration versus their use for supportive information for addressing more focused questions, such as drug interactions, dosing, and resistance issues.
		So who would like to start us off?  Dr. Saag?
		DR. SAAG:  I think that, even though the meeting has defined what the treatment population is; that is, at least two HAART regimens in all classes, still begs the question of those highly experienced patients who have really gone through all options because I sense that there is some confusion about what optimized based background therapy is.
		For example, optimized background therapy is more likely to work somebody failing their second HAART regimen versus their eighth HAART regimen.  I think that has to be taken into consideration when we talk about designs later.
		The bottom line I think we need to talk about is:  What are the objectives of treatment, just in the clinical situation and then about it from a trial situation?
		At least in our clinic, it's a lot different maybe than Dr. Ward's.  We're having a lot more treatment failures than he presented.  We're having at least a death a week now back again.  So we have actually more than that.  We have 70 deaths this year out of our 1,000 patient population, which is maybe different than what other people are seeing.  Perhaps that's because we were using protease inhibitors early, early on, but whatever the case is, it's what we're seeing.
		In our situation, what we are finding is that we are having to redefine what our goals of therapy are for those patients.  So that's what I want to present as a point.
		In those patients who have really, really far advanced in multiple HAART regimens, we were far away from the cure paradigm.  So, therefore, treating to the level of detection is not even discussed.  It's not what we're going for.
		Rather, what we shoot for is some decrease in viral load below their highest set point value that we can define.  Usually that is easy to get because they have had a holiday somewhere along the line where they have bounced back up to, let's say, 400,000.  And then we're happy just to get them a .5 log below where they started.
		I think that in that scenario, what we're really doing here is ‑‑ I am not really as concerned about prevention of resistance.  They have already got that.  What I am concerned with is prevention of clinical progression.
		I think that in my sense of coming to this meeting, when I'm thinking about a salvage situation, that's the population that I'm thinking of.
		So preventing resistance is a secondary or tertiary objective at this point.  The goal is to keep people alive and living well.  In that regard, I would propose that what we ought to think about is getting patients to at least a .5 log below where their highest viral load has been and sustaining that for as long as we can.  And whatever drugs or strategies accomplish that I think is a key point.
		So what type of information would I like to see from studies?  I would like to see regimens in this salvage population, the highly advanced treatment‑experienced patients, to sustain at least a .5‑log reduction in viral load from their baseline and sustain that for as long as possible.
		ACTING CHAIRMAN GULICK:  Dr. Deeks?
		DR. DEEKS:  I entirely agree with basically everything that Mike just said.  I would like to add onto that and speak to some of the comments that Dr. Schechter had made earlier regarding the heterogeneity of our patient population.
		I think as the way we define the heavily treatment‑experienced patient population right now, it's very heterogeneous.  I have patients who have failed 3 classes of drugs who have 500 t‑cells, a viral load of 5,000, and are doing very well.
		So across all patients, there is a huge amount of heterogeneity in this group of patients, but I do believe that this patient population is ultimately moving toward less heterogeneity.
		And we have and Mike does as well, I think, a small group but a growing number of patients who have very high viral loads, very low CD4 t‑cell counts, an RT protease genetic background that is inconsistent with any real good antiviral response to any drugs now.
		I would agree with Mike that these patients are now getting very sick.  We have actually a large number of deaths in our clinic as well, and many of these patients are now dying from clear HIV‑related complications.
		So when I think of salvage therapy, I have a very different mind set.  Like Mike does, I'm thinking now of that group of patients who have ten t‑cells and who have run out of options for whom a study that was a single arm and had only one drug; for example, T‑20, would be something that would be highly desirable to me, something that my patients would be very much interested in going into.
		And I would prefer to have access to those studies for that patient population, in contrast to the A plus B versus B plus C‑type stuff, which I think is more designed for patients who are less desperate earlier on who might be able to wait for that type of study.
		So, actually, the bottom line is I think that there is less heterogeneity in this very, very heavily treated patient population than some of the presentations which exist.
		ACTING CHAIRMAN GULICK:  Dr. Schapiro?
		DR. SCHAPIRO:  First of all, since this deals with resistance assays, I would like to add to my disclosure that I received financial support from Visible Genetics and research support from ViroLogic, both that deal with resistance assays.
		I think, to touch on the points that Mike and Steve mentioned, we mentioned drug, but I think we should realize that the way we use drugs makes them different drugs.
		We categorize a drug based on a certain approval on the studies that were done, but I think we should realize, I think a lot of the work done by the previous speakers, shows us that the drugs are really different drugs when you use them at different doses at different schedules.
		And although we may say this patient now has no options, we're really looking at the data on the way the drug was used in naive patients.  And we should keep that in mind.
		When we try to compare, you know, we stratify for resistance to this drug, resistance is relative.  It's completely relative.  Drugs are not resistant or susceptible.  They become more and more resistant or less and less susceptible as mutations or full change phenotypic resistance occurs.
		So we probably have to add for dimension drugs are not black and white.  We probably have to consider the dosing of the drugs.  I think we have the most data for protease inhibitors, but we might find as we learn more about the other drugs that in other classes of drugs, we may have ways of boosting them as well.
		There may be metabolic ways of boosting NRTIs, which are around the corner.  But definitely for protease inhibitors, if we consider how we are using them in the salvage patient, we may actually find that the same drug is a different drug when we use it in naive patients, where we will look for considerations of easy adherence, minimal toxicity.
		And when we have the patients, I think that Mr. Hogan described earlier that Steven and Mike touched on patients that in clinics are dying now again.
		For those patients who will look at the drug entirely differently, we'll be willing to administer the drug more frequently and possibly much more toxic doses.
		We're really not going to get all beat up about some metabolic changes if the patient isn't dying.  And I think when we make this discussion, we should consider the fact that the drugs are relative.  We cannot put down how many mutations affect this drug without considering what exposure the drug is getting.
		Therefore, I think in some of these study designs, we should keep in consideration that we have to be looking all the time not only at resistance but at exposure.  And we cannot make sweeping conclusions about drugs and resistance but how we are going to use them.
		And since basically these patients don't have options, we have to be creative.  We're saying, "Oh, these are patients who have no options.  So how are we going to optimize therapy if they have no options?"  There is no optimizing therapy.  We have to take into consideration that we may have to be creative.
		I think what it will probably mean is using different doses, and we will have sort of a sliding degree of toxicity and no exposure.
		ACTING CHAIRMAN GULICK:  Dr. Pettinelli?
		DR. PETTINELLI:  What I would like to see in this patient population is a comprehensive approach.  I think that there is space for registrational trials.  There is also the possibility for other trials.
		I totally agree with Mike and Steve.  This patient population is very heterogeneous.  In the one, there is maybe a possibility for some of them to build up to what we call an optimized regimen on the base of the resistance, phenotypic resistance assay, genotypic or phenotypic resistant assay.  If we can do that, then we could indeed do some of the trial that has been proposed in our standardized optimal therapy versus one or two new drugs.
		For others, that will not be possible.  I hope that during today we will discuss the different possibilities for these different patient populations.
		Also, I think what I would like to see, really, to understand what is the long‑term efficacy of whatever intervention we do, one may be that 24 weeks is enough for accelerated approval.  I don't think it is really enough to understand how we are going to use these drugs.
		So definitely we should have a longer‑term follow‑up.  And then, additionally, we really should understand what happens when those patients are failing.  Now we're talking in certain standards the earlier failure.  When those patients fail those regimens, what are the options afterwards?  We might have a drug that's very powerful but then limited successful options.
		Those are things I think we should discuss today.
		ACTING CHAIRMAN GULICK:  Could people comment on testing the activity of a new agent in this patient population?  In other words, what are you looking for?  And what kind of duration would you call for to demonstrate that activity?
		Currently ‑‑ correct me if I am wrong, but regulatory‑wise 24 weeks of activity data is what you like to see for an accelerated approval.  Is that different in this patient population?  Dr. Eron?
		DR. ERON:  Well, I think there are a couple of issues.  I mean, I agree with both Mike and Steve and having clinic populations that are probably similar.  But where it gets dicey is:  At what cutoff of, for example, CD4 cell count do you consider a patient unable to wait for a combination of agents?  And that's something that I think would take some discussion to limit the heterogeneity of that group as much as possible, though I think it can be done.
		I think what you were suggesting was a single arm study.  I actually think that if you can define the group well enough ‑‑ and I think there are enough patients now that you can.
		I think, to try to get to Trip's question, for other than that kind of single arm study, I think what is different in the salvage setting is the amount that is kind of Phase II work that one has to do before approaching a larger Phase III trial when you talk about what happens at 24 weeks or whatever.
		I think in the population that you're going to test, you want to define the activity of the drug because there may be two logs over two weeks in naive patients, but it may be half a log over two weeks in the population you're after.  And in order to design a study, you need that type of information.  I think that's a little bit of what Jonathan was saying, depending on the background resistance.
		So before you embark on figuring out whether it is 16 or 24 weeks, I think the drugs, each of them, need to be defined very carefully.  And, in addition, we have lots of examples of kind of these whoops examples, where "Whoops.  We didn't know about that PK interaction of efavirenz and amprenavir."  I think we have to minimize those kinds of things.
		So while the second part of the question deals with what I am talking about, I think those are things that have to be carefully defined first in order to address the first part of the question.
		As far as duration in a larger trial, I think, again, Steve is probably as equipped as anybody to talk about that in the issue of transient viral load changes accompanied with positive CD4 responses.
		One of the earlier speakers mentioned no viral load change in a positive CD4 response.  I've not really seen that before.  There is always some change, even though it's transient.
		So I think that for the purposes of taking care of very advanced patients, the amount of time that the antiviral effect has to last does not have to be very long, 8 weeks, 16 weeks, something like that, provided it's accompanied by an immunologic benefit.  So I think you would actually want the immunologic change to be actually part of your primary evaluation.
		ACTING CHAIRMAN GULICK:  Dr. Jolson?
		DR. JOLSON:  I just wanted to slightly rephrase this first question to make certain that we really stay focused.  Again, it's recalling the distinction between trials that are done in the course of drug development for a specific drug versus treatment strategy studies.
		What we would really like to hear your thoughts on are the former, the studies that could be done which would allow a sponsor to make a specific other efficacy or safety claim about their drug when used with other drugs.  It's probably unlikely that is going to be accomplished through a single orb study unless there is an appropriate historical control group or there's some other indirect analysis incorporated into the design.
		It's not to minimize the importance of those strategy trials, but it's a slightly different research agenda than what pharmaceutical companies need to make lawful claims about their drugs.
		So I would reword the question to say, "What types of information should be in drug‑specific labeling that would help it when making treatment decisions to use a particular drug in treatment‑experienced adults and children?"
		ACTING CHAIRMAN GULICK:  So you're asking us to consider:  How do you document safety and efficacy of a new drug in this patient population, a single new drug?
		DR. JOLSON:  Yes or safety and efficacy in a broad way, which would include drug interactions and all of those things, how you develop a drug, develop a new drug, to make certain that at the end of the day, you don't have all of your data derived from treatment‑naive patients.
		ACTING CHAIRMAN GULICK:  Dr. Saag?
		DR. SAAG:  Yes.  Just to follow up and answer the question directly, I don't think you need necessarily a single arm study, but you can look at early versus deferred access to that new agent.
		I mean, I'm being very specific.  The population whom you're questioning, as Carlton was saying, whether even to treat them at all, whether it's any benefit to the control therapy, then what you do is you take them, you create an optimized background regimen, and you randomize, indeed, or get access to the new drug or the optimized background regimen initially and then you watch for a response.  I mean, we can debate about what the cutoff is, but let's say a half a log below baseline.
		Then for the group who got their optimized background regimen and did not have that response, that would be failure.  And it would go into access to the drug, which is like an expanded access program anyway.
		If they did have a response, then you measure the length of response.  You also measure the safety.  You get safety out of both populations, and it's early versus deferred.
		Again, we have to be very precise about who is going into this study.  It's a study of someone who has very few other options and is at risk of bad things happening in the short term.
		It's I think ethical because they get access to the drug.  It's just a question of careful monitoring and making sure you, if you will, rescue them from a failing regimen if they are failing quickly.  So it requires frequent evaluation so you don't put them at high jeopardy.
		ACTING CHAIRMAN GULICK:  Dr. Wong?
		DR. WONG:  I think that what Mike suggested is really quite a good design.  I mean, we yesterday, just yesterday, voted unanimously to recommend approval of a drug for which there were no concurrent controls and for which the only controls were a flawed historical subset.
		So this design that you're proposing is superior to that.  I think that would convince me if someone came in and showed data that there was a clear difference between those groups.
		ACTING CHAIRMAN GULICK:  And another common thread, just to point out, between yesterday's discussion and today's, is a very ill patient population who have few therapeutic options.  That's what they have in common.
		Dr. Murray?
		DR. MURRAY:  I just wanted to comment on one of the comments I guess from Dr. Deeks and maybe came up from Jules about maybe not preferring a factorial design in even doing a one drug versus a top of optimized background versus optimized background.
		I guess I am not quite clear on that because, I mean, if you could possibly have access to two or three drugs, no matter how desperate, I think that even if you were more desperate, if your t‑cell count was low, that you would want access to more drugs than just one.
		And I think this is something that we have been pushing and I think we would like to hear more feedback to push industry to collaborate together.  It seems like I've heard a bit of the opposite why you would ‑‑ is there any reason not to want a possible factorial design where you get access to more drugs for these patients?
		ACTING CHAIRMAN GULICK:  Dr. Mellors?
		DR. MELLORS:  Would it be too much to show an overhead about the factorial design and its major limitation?
		ACTING CHAIRMAN GULICK:  Knock yourself out.
		MR. LEVIN:  Are we talking now about studies for deep salvage or just treatment studies past the first‑line regimen?
		DR. JOLSON:  The intent was really not to limit the discussion to what you're saying is deep salvage because we think there is really a range of patients who do need options and we want to see drugs developed across that range.
		So this would be part of the discussion but hopefully will not be all of the discussion because the considerations are going to be different.  And I think both groups of patients need attention in terms of drug development.
		ACTING CHAIRMAN GULICK:  While we're waiting for that to warm up, a couple of other people.  Dr. Cunningham?
		DR. CUNNINGHAM:  I just wanted to make a comment about the issue of factorial design.  I think when people are talking about what people have now termed the "deep salvage" patients, I think that's a group where the factorial design might not be the best approach because those patients really need to have every option available.
		But I think for the people to have "time to cruise," I think was the term that was used in one of the earlier talks, they certainly have failed one or two regimens, but they're not desperate.  That's a situation where I think factorial designs might be very useful and might also look at the issue of whether or not you're better off cruising for a little while before you go into and wait until there are multiple regimens available and can test that hypothesis.
		ACTING CHAIRMAN GULICK:  Dr. Mellors?
		DR. MELLORS:  Yes.  I think these points have been made, but I think they need to be emphasized.  For a desperate patient population, a factorial design for registrational study is a bad idea because if you look at the way it's set up, ‑‑ and Martin pointed this out ‑‑ the number of cells required is 2n, n being the number of drugs you're studying.
		So if you study 2 new drugs, it's 4; 3 new drugs, it's 8; and 4 new drugs, it's 16.  The number of cells that get all of the new drugs is one to 4; one to 8, one out of 8; and one out of 16.
		So if you study 4 new investigational agents together, in a desperate population, only one‑sixteenth of the people enrolled get what you would like to do in clinic, which is give them as many new drugs as possible.  Okay.
		And that's just shown here nicely for the two by two, where this is the cell you want to be in, two news.  You really don't want to be in three news.  You don't really want to be in this and this.  And by "desperate," I would define desperate by the CD4 count because that is the most important predictor next to viral load of short‑term events.  These arms are probably less satisfactory than the nothing arm because they use up one option at a time.
		So I don't think factorial design accomplishes what we want to do for our patients.  It may tease out the individual components, but I think that's more efficiently done in the standard approach that's been offered for registrational trial, which is you identify a qualifying population, you do resistance testing to see if they qualify, and then with that resistance testing, you optimize the background therapy.  And I have some comments about what that means.  And then you randomize to optimize background plus the investigational agent plus placebo.
		By optimized background therapy, I think there needs to be some kind of guidance.  You need to calculate the phenotypic or genotypic sensitivity score of the selected regimen and possibly stratify enrollment by the PSS or GSS and clearly allowed expanded access agents, have endpoints that are most clinically relevant, change in viral load, change in CD4, and the proportion that develop resistance to the investigational agent.
		Then when you cross this over, it addresses the issue of safety.  There's always a tension between the time of or the duration of the trial and the accuracy of the safety information.
		I just have one more to show, and I think this is what Mike was talking about.  I favor the design that a registrational trial should be comparing one new investigational agent to really optimize background.  That way it's easiest to sort out the information you want to know about safety, pharmacokinetics, drug interactions, and the relationship between exposure to response and the relationship between exposure baseline susceptibility and response.  When you start to do that in an eight‑cell factorial design, it becomes much more complicated.
		The strategy trials, which should complement the registrational trials, are to compare multi‑drug regimens that increase the likelihood of success.  And this is what Mike was talking about, taking the most desperate population and comparing multiple drug regimens with new investigational agents versus the best approved or expanded access regimen that a clinical can put together.  These should be relatively short with crossover at an arbitrary time but closer to 16 weeks than 48 and/or a clinical event and CD4 and RNA response.
		So I think that the strategy should satisfy our need to treat patients with the most available expanded access or investigational agents.  The registrational trial I think has a hopeless problem when you want to treat the most with the most number of investigational agents.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi and then Mr. Hogan.
		DR. DeMASI:  Yes.  I just had a couple of general comments.  First, I wanted to reinforce John's comments about the factorial design.  Obviously one of the advantages of factorial design is being able to get multiple investigational agents to patients in a particular study but in a balanced two‑by‑two factorial, as John just pointed out, the number of patients or percentage of patients that have access to both investigational agents is 25 percent.
		If you do allow the use of investigational agents as concomitant to antiretroviral medications as part of the optimized background regimen and you add a component, such as a two‑to‑one randomization, to the investigational agent of interest, if two‑thirds of the patients are on that agent and because of the patient population approximately 50 percent of the patients have access to the other agent, 35 percent of the patients have access to 2 agents.  Therefore, it's actually higher than what you would have in the two‑by‑two factorial design.
		So the combination of a two‑to‑one randomization and the use of investigational agents I think is a way to promote optimal use of investigational agents in a single study.
		The second point I wanted to make is just one of the distinctions between the efficacy of the regimen and the activity of the individual drug.  If you look at multiple drugs that have intrinsic antiviral activity, as measured by 10 to 14‑day responses, for example, in RNA, and you combine those in a multi‑drug salvage regimen, you are most likely going to get efficacy of the regimen beyond 2 weeks.
		That's something that could be confirmed but just to reinforce the distinction between the efficacy of a salvage regimen versus the activity of an individual drug that is being studied for potential approval, submission and approval.
		The third point I wanted to make is regarding the types of the clinical designs, clinical trial designs, that we're actually seeing.  Because of the heterogeneity of patient population in terms of the baseline factors resistance profile, I think that a one‑size‑fits‑all strategy in terms of development of salvage drugs may not be appropriate and that there should be flexibility in the design of pivotal registrational trials in terms of selection of the patient population, the design itself, the duration of therapy, and other factors.
		ACTING CHAIRMAN GULICK:  Mr. Hogan?
		MR. HOGAN:  I would like to politely but very strongly disagree with Dr. Mellors that the desirable thing is to pile on as many new drugs as possible.  I think I can speak with some authority to this issue because it was prior to the era of HIV RNA testing, but I have experienced facing a single t‑cell.  You know, it's a very serious clinical situation.  So I think I can extrapolate how I would feel in that situation.
		I had always been on combination therapy from the days of ddI expanded access.  Yet, I had no desire to pile on more drugs at that time.
		I think, particularly with experimental drugs, you have some credible dilemmas if you pile them on all at once without some form of comparison between them.
		For example, if I pile on three investigational agents and I have a novel toxicity, which one do I stop?  How do I determine which one to ‑‑
		DR. MELLORS:  Can I respond to that?
		ACTING CHAIRMAN GULICK:  Yes.
		DR. MELLORS:  You determine that in a registrational study design that I outlined.  The individual characteristic of that drug is the cleanest way to do it.  You then design strategy trials that incorporate the information from that into multi‑drug combinations.
		I would agree with you you don't blindly pile on investigational agents.  I'm talking about agents that have proven activity and a reasonable safety profile when examined in addition to background therapy.
		MR. HOGAN:  I guess a key point is as a patient, my preference would be to take the minimum number of drugs that will achieve a satisfactory response.  And I would like to see clinical trial designs that would establish that.
		So that's one reason why I'm a fan of the factorial approach because it does allow you to look at the individual toxicities of drugs, to look at specific subcombinations, AB versus BC and so forth, and then it allows me to find out where I can get adequate antiviral bang without excess toxicity.
		DR. MELLORS:  We are talking about the people that are most desperate.
		MR. HOGAN:  I understand.
		DR. MELLORS:  And if you undershoot and come up with one drug too light in the regimen, that may be it for that individual.
		MR. HOGAN:  Yes.  Cardiovascular disease kills people as quickly as CMV.
		DR. ERON:  But, John, that I think is the fundamental problem of your study design for registration, actually.  Just take a concrete example of T‑20 and tenofavir.  Let's say tenofavir is an expanded access in a couple of months.
		The problem with your study design ‑‑ I think it goes to what Dr. Murray was saying ‑‑ is that if you're allowing expanded access agents in your control arm, then those people are getting exactly what you said you don't want them to have.
		So if there is only one agent available which is going to prove anything, the optimized therapy really is just kind of scrambling around things.  And you don't really know whether they're better or not.
		DR. MELLORS:  What's wrong with including the expanded access?  By the time agents get to expanded access, the characteristics of the drug are fairly well‑identified.
		DR. ERON:  No, but the point is that the people who get randomized to get the only one additional drug ‑‑ let's say in the expanded access situation ‑‑ are ending up exactly in the situation you just said you wouldn't want someone to be in.
		DR. MELLORS:  There's an insolvable dilemma between the two.
		DR. ERON:  Well, we have to try to solve it.  The potential might be for an optimized background or no change in therapy, as Mike was talking about, and sequential addition in very short order.
		DR. SAAG:  I would like to get out of this circle here because I don't think there's a lot of disagreement, actually.  If we segregate out what's for registrational purposes versus what's for use in practice ‑‑ and they are two different issues.  I don't think there's much disagreement here.
		I think for the registrational purposes, you have to identify the activity of the drug because you can't approve it based on its activity in conjunction with other investigational drugs alone.  You've got to have that individual.
		I think that is what John proposed first.  I think that still has to happen.  What happens after that, maybe we shouldn't spend much time on because I think that that is going to bog us down.
		MR. HOGAN:  Well, here's I think a point of key disagreement.
		ACTING CHAIRMAN GULICK:  Let's take people in order.  Go ahead.
		MR. HOGAN:  I don't think it's reasonable to say that by the time we get ready for these studies, that the activity and tolerability of the drugs is necessarily well‑characterized.  And, again, I would refer you to the multitude of toxicities that have propped up post‑registration for various drugs.
		DR. SAAG:  I'm not disagreeing.  All I'm saying is that fundamentally, no matter how we slice it, there is going to be a need to identify the new drug and its activity and its safety.
		We have to have some way of doing it.  That's a given.  What happens after that, you're right.  Those can be happening concurrently.  And you want to have as much early information as you can with the intent for that to happen.  But I think from the company's perspective, from the agency's perspective, there has got to be some way to tease out the activity and safety of a single drug.  And that's what we really I think should focus on.
		ACTING CHAIRMAN GULICK:  Dr. Hammerstrom?
		DR. HAMMERSTROM:  Well, I would like to say that Dr. Mellors is basically 100 percent wrong in the relative merits of the 2 registrational trials versus a modified factorial design.
		In his proposal, 50 percent of the subjects get on the control arm, either against drug A or against drug B.  The other 50 percent get only one active arm.  In the modified control, factorial design, where there isn't any optimum background cell, you add both drugs or you add one drug, nobody gets no new drugs.  And everybody gets at least one.  More than a third get two new drugs because the optimal assignment just on statistical grounds is 14 to the double thing, to each 10 on either A or B.
		So you either have nobody would be getting ‑‑ in the modified factorial, nobody gets background.  There are ten subjects who get A only.  For every ten subjects who get B only, for every 14 who get A plus B, factor ‑‑
		DR. ERON:  The problem is it may be worse to get A only or B only than ‑‑
		DR. HAMMERSTROM:  But if you do a registrational trial, everybody gets background or background plus A or background or background plus B.  Nobody gets A plus B unless you do a modified factorial.
		ACTING CHAIRMAN GULICK:  Dr. Schechter?
		DR. SCHECHTER:  Yes.  I just want to echo that that, first of all, the bar has been changed.  I think when we go into deep salvage, you're starting to move towards a tuberculous meningitis model, where the stakes are different.
		I agree a single new drug tested in that population is entirely appropriate, especially if they're at such great risk that a second drug won't be available during this crisis period.  So there's no disagreement there.
		Simply put, if two companies are about to do registrational trials for drug A and drug B separately, then with the same number of patients from each company, they can do AB and AB and have two registrational trials and both drugs given for the same amount of money.
		So I have to disagree with John.  If he says only one‑quarter of patients get the double therapy, if you do it separately, nobody gets it.
		ACTING CHAIRMAN GULICK:  Dr. Mellors, response?
		DR. MELLORS:  Yes.  I think that the three cells that don't get the double ‑‑
		DR. HAMMERSTROM:  There aren't three cells.  There are only two.  There is no EBT cell.
		DR. MELLORS:  You're talking about a different design.  I'm talking about a ‑‑
		DR. HAMMERSTROM:  No one wants the factorial.
		DR. MELLORS:  Okay.  While I made that ‑‑
		DR. HAMMERSTROM:  They only want the modified factorial.
		DR. MELLORS:  I made the point that nobody wants the straight factorial design.  The modified factorial increases the number that get the double drug.  And if there are two companies that want to do a registrational trial together, then I'm certainly not going to stand in the way.
		But knowing we're talking about a desperate population, two investigational agents may not be sufficient.  So we're talking about a third factor in the factorial.  There's where it becomes much more ‑‑
		DR. HAMMERSTROM:  No, it doesn't, because, again, we use the modified factorial, which Dr. Laessig's slide put up there.  You have A plus B, A plus C, B plus C, or you have all three.  Those are the only four cells.
		DR. MELLORS:  But you're not able to tease out the ‑‑
		DR. HAMMERSTROM:  I am certainly able to tease out each contribution.  I test the three A, B, C against BC.  That's the contribution of A.  I test the A, B, C against AC.  That's the contribution of B.  I test the A, B, C against BC.  That's the contribution of A.
		PARTICIPANT:  That assumes there is no drug interaction.
		ACTING CHAIRMAN GULICK:  Let's take the people in order.
		DR. DEEKS:  One of the issues ‑‑
		ACTING CHAIRMAN GULICK:  Okay.  One second.  Several people have been waiting patiently.  Ms. Dee and then Dr. Deeks.  Then we'll pick up some of the others.
		MS. DEE:  Thank you.  You know, I think we need to get a little bit real here.  When you talk to companies about registrational trials versus strategic trials, they're not going to do the strategic trials if they don't have to.  Some of them might.  Most of them won't.
		So what do we have?  If we use Dr. Mellors' model, we have this everybody's switching around, getting expanded access drugs maybe, maybe not.  I really wonder what we're going to know when we get down that trial in the long run.
		We're looking at viral load measures that may be a measure of clinical benefit.  Maybe they're predictive.  And probably they're not as good as some other things.
		As far as safety, you know, Mike keeps saying:  Well, we need to know safety.  And we'll know it in 8 weeks or 16 weeks or 24 weeks.  That's just not true.
		What we are experiencing in real life is one drug being ready, one drug being almost ready.  I mean, we see this in real life over and over and over again.  Why can't we do it together?
		Carlton with one CD4, when is he going to get sick?  What does "desperate" mean, that I just finished an OI, that maybe I'll get one in six months, that maybe I won't?  I mean, we do not know the answers to how that really shakes out.
		So we have a more intelligent population that often says:  Well, wait a minute.  I've been ruined re:  resistance by you experimenting on me.  If these two drugs are available and I may have a better chance in 20 hours, as opposed to 20 minutes.  Why can't I have two of them?  Why can't I have a better chance?
		Why can't we think outside the box for a change, instead of promoting what's going to be best for industry, without thinking of the long‑term effects of that?
		ACTING CHAIRMAN GULICK:  Dr. Deeks and Dr. DeMasi.
		DR. DEEKS:  I just want to answer Jeff's question earlier about the factorial design and my problems with that.  My problems are that I just don't see it happening.  There are major practical limitations.
		I have dealt with each of these companies in trying to do similar types of studies before.  I think it can happen.  I just think it's going to take a long time to get three companies with three promising drugs to come together to do an A plus B versus B plus C versus the three‑drug combination.  The more likely factorial design looks at no drug versus one of the two agents versus both.
		For my patients who are not desperate and can basically continue to cruise on whatever they're doing, I would prefer to cruise than to enroll them in a trial where they might get sequentially mono therapy.
		For my other patient population who are desperate, I would definitely want to enroll them in such a factorial design if they had an option of getting one drug, but, again, it's the practical issues that I think will slow down that study.
		My preference for the desperate patient population, CD4 counts less than 50, is for the companies with promising agents to move very quickly to the kind of study that Mike had discussed earlier, which is basically optimize your background therapy plus the new agent versus optimized background therapy with a very quick escape.
		My preference for that study design in the very desperate population is really largely based on the fact that such a study can be done very quickly and is much more practical than these ‑‑
		DR. HAMMERSTROM:  The factorial design doesn't preclude a quick escape.  I mean, in fact, we would assume that.  If you're on background plus A and things go wrong, you get switched to open label background plus A plus B.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi?
		DR. HAMMERSTROM:  It would be the same switch criterion as if you were only doing one trial.  There would be no problem with that.
		DR. MELLORS:  But that presupposes that you can switch in time to make a difference.  And that is a major supposition.
		DR. HAMMERSTROM:  That is not a problem with the design.  No matter how you ‑‑
		DR. MELLORS:  No, but it's a problem with the disease.
		DR. HAMMERSTROM:  Yes, but you don't introduce that problem by using a mild factorial.  It's a problem, no matter what.  You may not be able to identify in time to do anything.  No matter how you're testing the drugs, the disease is what it is.
		DR. MELLORS:  Right, right.
		DR. HAMMERSTROM:  Trial design cannot correct it.
		DR. MELLORS:  But setting up for adding when you have the possibility of two companies who want to get together or three companies and then randomizing somebody to getting only one of those investigational agents.
		DR. HAMMERSTROM:  No.  The only ones we're considering are ‑‑ well, if there is two, you would get one.  And if there are three, you would get at least two.
		DR. MELLORS:  Okay.
		DR. HAMMERSTROM:  I don't think practically that the three‑way drug is going to come about.  I think that, not for statistical but for logistical reasons, is highly unlikely.
		DR. MELLORS:  Well, it's likely to.  And so you're randomizing people to one.  It's likely that two will become available more likely than three.
		DR. HAMMERSTROM:  Right.
		DR. MELLORS:  And you're randomizing people to one with this, quote, "quick bailout."
		DR. HAMMERSTROM:  That's better than randomizing to none.
		DR. MELLORS:  No, it's not, not necessarily.
		ACTING CHAIRMAN GULICK:  Dr. Jolson?
		DR. MELLORS:  You basically don't understand the pathogenesis of the disease.  You only get one shot with the drug if resistance develops.
		DR. JOLSON:  Let me make ‑‑
		ACTING CHAIRMAN GULICK:  Dr. Jolson?
		DR. JOLSON:  ‑‑ just one point of clarification that I think needs to be understood that any time we're talking about optimized background therapy for either a factorial or a straightforward design, we are assuming that those patients have access to other expanded access drugs.  That's implicit.
		So when we say one investigational drug, that's not quite true because they have the opportunity to enroll in other expanded access programs.  I think that's what some of the disagreement was about.
		Let's just assume because we've gone on record as saying this that when we talk about optimized background therapy, we are assuming that it's your best combination of drugs with whatever resistance testing is available to help construct that plus whatever expanded access agents are available that are not the subject of the research question in the study.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi, waiting patiently.
		DR. DeMASI:  I'll just make a point about the role of factorial deigns in potential drug development and, again, distinguishing between a registrational trial and a strategy or three before even Phase II study in which you had a factorial but you were looking at the additive contributions of activities of regimens early in the treatment period, say one to two weeks.
		The second point is that in terms of a modified two‑by‑two factorial, if that was the case where you had AB and AB in the presence, one of the assumptions of the factorial designs is assumption of no treatment interaction.
		So positive or negative interactions may complicate the interpretation of the main effects of drugs A and B.  If this is a pivotal study, how would that be viewed in terms of the individual drugs?
		DR. HAMMERSTROM:   Well, most likely the interaction will be positive.  You get more from A plus B than the sum of what you get from A and B alone, in which case there is no problem at all as long as A plus B beats either A ‑‑ if it beats A, then B is contributing something.  If it beats B, then A is contributing something.  That is all you need for registration.
		ACTING CHAIRMAN GULICK:  Mr. Hogan?
		MR. HOGAN:  I'll try to keep this very brief.  I'm going to throw in a minority viewpoint.  I realize this is very controversial.  We all know that for most of the toxicities, your risk of a toxicity goes up as you progress in the disease.
		Even in this era of sort of the resurgence of OIs, my physician is telling me he is still treating five toxicities for every OI.  Keith Henry went on record as saying he is doing 20 hospitalizations for toxicities for every hospitalization for HIV‑related condition.
		So, to my mind, I think closing the door on that no‑drug factor or that one‑drug factor may be precipitous.  I think that there may be some situations where we may examine whether actually taking drug is harming people.  I think that is an important thing.
		I am not speaking for the Coalition for Salvage Therapy.  This is not their perspective.  But I think it is important to actually look at what the minimum amount of drug it takes is, as opposed to the maximum amount of drug that can be tolerated.
		ACTING CHAIRMAN GULICK:  Dr. Schapiro and then Dr. Pettinelli.
		DR. SCHAPIRO:  I do think we have to make a little bit of a reality check here.  Mike, of the 70 patients who died, how many of those did not have optimized therapy?
		DR. SAAG:  At the time they died?
		DR. SCHAPIRO:  Yes.
		DR. SAAG:  Over half.  I mean, actually probably 80 percent.
		DR. SCHAPIRO:  Were not optimized?
		DR. SAAG:  Yes.  I mean, in other words, those were people who have been through everything.  It depends what you mean by optimize.  They certainly are not below the level of detection.  There were none of them.  Well, I take that back.  There were some who died of toxicities.  So they were below.
		DR. SCHAPIRO:  In these study designs, how would you have optimized?  You know, we're optimizing, then giving all of these things.  We're fooling ourselves.  You were doing, I would assume, as best you could and they were still dying.
		I think most of us ‑‑ and I think we are going to see more and more of it over the next year or two ‑‑ are optimizing therapy.  And, despite the fact that we're optimizing therapy, ‑‑
		DR. SAAG:  Oh, yes.  And they don't respond.
		DR. SCHAPIRO:  ‑‑ resistance assays don't help us if in options.
		DR. SAAG:  Right.
		DR. SCHAPIRO:  So these patients I think probably in Steve's clinic, in my clinic, I try to optimize them.  I can't because they are optimized and they still are in bad shape.
		DR. SAAG:  In which case in those situations, mono therapy may be an option, even though pathogenically it's not what you would want.
		DR. SCHAPIRO:  So I think we have to step one back.  You know, I also have designs on my slide to say:  We'll optimize and so on.  But in real life, when we try to take it, maybe that's what Steve is saying is not going to happen because that's not what's happening.
		The patients are optimized.  We do use, many of us, resistance testing.  And many may use it in the future.  We're doing all of the other techniques we can, and they're still dying.  So these designs look good.  But basically for these heavily pretreated patients, they are optimized.  That's not the issue.
		The other issue is we may not have together three drugs.  And we can't probably wait six months to get three drugs together.  So if we want to get really real about it:  one, the patients are optimized and, two, we don't have two or three agents to combine.  I think that we should take into account.
		I think to get back to Dr. Jolson's question, what do we want to look at for efficacy in these patients, I don't think we will be able to look at it well in these patients.  I don't think you will be able to get an answer in the heavily pretreated patient, which basically are the patients who we're most concerned about I think that Mr. Hogan also mentioned.  You cannot do good studies.
		Now, I think what characterized those patients most ‑‑ and many things characterize them ‑‑ is the fact they have resistance.  I think the one barrier that usually precludes our best management is the resistance.  Adherence and toxicity are important, but I think if I could change one thing in a patient, I would give them a wild‑type virus again.
		I think we may need in some cases in those patients to use the resistance as a surrogate.  So we will not be able to say, "Does this drug work well in heavily pretreated patients?" because we can't do good studies.  You know, there's nothing to optimize and no three drugs to debate because they got them already.
		What we will have to do is say in other patients we're maybe one step back or two steps back.  Try to characterize how those drugs work with specific resistance patterns.
		I would, again, you know, what I always plug, we have to see with which exposures they work.  And then we'll be able to say we don't know specifically how this works in those patients, but if you show me what their resistance profile there is, what fall change there, what mutations they have, from patients who are less experienced, we can tell you that if you give this dose, you will have some response.
		And then we'll be able to say, as Mike and Steve ‑‑ I mean, you'll probably get half a log.  That's good.  I think in reality, for those heavily experienced, we may not be able to do better than that.
		ACTING CHAIRMAN GULICK:  Dr. Pettinelli?
		MR. LEVIN:  Are we going around or not?
		ACTING CHAIRMAN GULICK:  Yes.  I'm keeping a list, Jules.
		MR. LEVIN:  We're not going around?  We're just going by hands?
		ACTING CHAIRMAN GULICK:  That's correct.
		DR. PETTINELLI:  I think, again, the issue is the definition what is the heavily pretreated.  For me, when I'm talking about optimized therapy, at least the patients should have access to two drugs for which the patient has sensitivity.
		They could be new drugs.  They could be old drugs.  It also depends again on what is the viral load of the patient.  A patient with 30,000 copies of virus must feel a very good response from their therapy.
		So, really, I think there is the possibility to study the patient.  We need to define what is the population.  We might need to use probably the modified factorial design because, really, I'm not sure that all the time A plus B is better than A or B.  That's a big issue for us.  Combinations do not always depend.
		Now, again, there may be overlapping toxicity.  And there may be issues there.
		ACTING CHAIRMAN GULICK:  Dr. Mathews?
		DR. MATHEWS:  You know, there was a time in the development of HIV therapeutics where there was considerable reluctance for sponsors to study very late‑stage patients.
		And I remember some presentations at this Committee showing that you could actually measure clinical endpoints in people with less than 50 CD4 cells and show that a drug worked.
		We're beyond that by several years now, but in a sense, when you're faced with a patient who is resistant to everything on the panel and has a very low CD4 count, it's a high‑risk situation, not only for the patients, who might be considering entering a trial, but I would think for a sponsor.
		We have seen some examples where drugs which were not home run drugs that had moderate or modest activity could be severely compromised in their development programs by their performance and some pivotal trials of the nature of which the previous discussion has been focused on.
		I don't for one think that patients should be trapped into enrolling in clinical trials simply to get access to drugs.  And I think if we're realistic about it, both to meet the needs of industry as well as patients and their doctors, we would focus more of our efforts in the treatment‑experienced populations, not to the people who have bars across the page on the resistance profiles for enrolling in salvage trials.
		But I think people more along the line close to the definition that the agency put up who have some resistance have failed some regimens, perhaps some in all classes, but not completely exhausted all therapeutic options.
		I think those patients should be immediately offered access through expanded access programs so that toxicity data can be collected and that the salvage trials should be focused on people where a measurable effect can be easily seen.
		ACTING CHAIRMAN GULICK:  Dr. Saag and then Mr. Levin.
		DR. SAAG:  I wanted to clarify a comment I made.  What I'm saying, you evaluate for safety and activity.  There is a tension between how long do you follow up before you let the drug be approved versus how long do you follow up afterwards.  It's the point Carlton made about holding people's feet to the fire for long‑term follow‑up.
		So what I'm referring to is short‑term safety.  Lynda, I'm not talking about cardiovascular things or lipids necessarily because they may take longer to develop.
		The point is that you have to decide if the drug is active and it's relatively safe, then you get it out.  But then there is an obligation to follow it up.
		The problem in my mind in the follow‑up ‑‑ and I realize I'm a little bit off topic, but I'll be brief.  The problem with the follow‑up is that in my opinion Phase IV studies in HIV are dead.
		You can't do them because by intent to treat, by the heterogeneity, you can't follow from that original new regimen that might last three months.  How do you follow out for two years?
		What you need is cohorts.  You need to follow cohorts carefully, accurately.  In my opinion, that's where money ought to be spent,min capturing real world data on experience and exposure to multiple agents followed over years, hopefully decades.  And then we can have some way of doing that.
		So I think that is where industry ought to work together to establish mechanisms to follow these patients in that way.  That's a whole separate topic, but it is germane because I think we do want the drugs approved quickly and get into expanded access quickly once their profile is determined, as least in the short term, that it's not doing harm and that there is some benefit.
		ACTING CHAIRMAN GULICK:  Mr. Levin?
		MR. LEVIN:  To be honest with you, I'm not sure what we're doing here today and, really, the productivity of this discussion.  I agree.  When we're talking about deep salvage here, people who have very little, if any, options left, I agree.  I agree with Mike and with Steve and particularly ‑‑ is it Dr. Mathews? ‑‑ in his last comment.  We're talking about, really, access to new therapies, no matter how you get it.
		The only reason to do a study for a deep salvage patient to go into a study is to get access.  If we could get it through expanded access, well, that would be fine, but that's not happening.
		Now, having said that, I also feel it's extremely important to try and capture toxicities and side effects.  So I want to try and make a few comments here.
		I think that what we need to do is to try and get ‑‑ the problem is here that you don't have A, B, and C, as already said by several doctors here.  You don't have A, B, and C available.  There is no A, B, and C.
		Next year there will be hopefully DAPD.  Right now we're talking about T‑20.  There's no A, B, and C at the same time.  That's already been repeated by several people.  I said that an hour ago.
		There is no A, B, and C to even do the factorial design.  There are no three new drugs available right now.  Tipranovir is not available.  DAPD is not available right now.  We're talking about next year maybe.
		DR. MURRAY:  It could be.  We're trying to get collaboration together.  We're trying to bring forward drugs together.  I would hate this meeting to end with sort of the companies getting off the hook of working together with drugs that are not available yet on expanded access.
		There are lots of drugs in Phase II development.  There are more than three drugs.  Right now we don't have any expanded access.  So I think if you have a lot of drugs in expanded access, a design like Dr. Mellors', maybe it would be preferable.  But when you don't have expanded access and you want to bring Phase II‑ish drugs out so that they can be studied together, I would think that there would be some benefit to a modified factorial design.
		And companies would each benefit because they would potentially get to use that data to support registration.  If they just have to give a drug to be a co‑drug with another sponsor who is investigating their drug, I mean, what is their incentive?
		What we're trying to do here is given incentive to get drugs out together in combinations in which they might not be used until expanded access.  I think we're trying to do that sooner and we're trying to provide them incentive to do that.
		I hope that we don't go away from the table today with pharmaceutical sponsors not hearing that.  Is that what you want or not?
		MR. LEVIN:  Let me just finish.  I agree completely in a deep salvage situation.  Let me try to answer the question a little bit that is being posed by the FDA.  I want activity identified.
		And then I agree with Dr. Mellors.  I am a person with HIV for 18 years.  I'm in the community.  And my community perspective is that I don't want one new drug.
		I understand there are concerns about toxicity and side effects and so forth.  We have no perfect answer here, and maybe we need several studies.  I don't agree with just adding on one new drug, and I'm not so sure.
		So I think that for a deep salvage situation, we probably need two or three drugs.  And what is available ought to be used by that person once we clearly identify activity, which is important to me.
		ACTING CHAIRMAN GULICK:  Dr. Jolson and then Dr. Pomerantz.
		DR. JOLSON:  I just want to follow up on a comment from Dr. Mathews and also Dr. Schapiro.  It was never our intent in this meeting ‑‑ and, in fact, if you notice, we don't use the word "salvage" therapy.  We're really focusing on drug development for treatment‑experienced patients.
		I just want to make certain that our entire focus today isn't on what has been referred "deep salvage," even though there is no question that those are patients in desperate need, because recall now that we have drug labels.
		We have 15 approved antiretrovirals.  And the kind of data that's in the labels is in treatment‑naive patients or nucleoside‑experienced or first PI failure.  We don't even have the data that would fit the definition of what we're talking about.
		So, even though it is not going to meet the needs of everybody, it would still be an improvement over currently available information to have data on the patient populations that would fall within our definition.
		We really need help to do that because they aren't patients who maybe have exhausted every single option.  They have exhausted, though, many options.  And it's not clear because of the imperfections of resistance testing, particularly for PIs, you know, what are going to be viable drugs.
		So I know everyone has focused on the worst case scenario because it is a desperate need, but we would be happy to see drug development as the next step to just include patients who have three‑drug prior experience.
		ACTING CHAIRMAN GULICK:  Dr. Pomerantz?
		DR. POMERANTZ:  Yes.  Thanks.  I was actually talking to Dr. Stanley.  I thought I would say it into the microphone.
		I saw a couple of hours ago this discussion start digressing into two groups that Mike and Dr. Mellors tried to pull back.  And it came back again with Dr. Mathews now.  People have been discussing at cross purposes there is clearly the group that the FDA had started our discussion with, which are those patients that have gotten two failures of HAART regimen and have seen all three classes of drugs.
		Then there are the ones that are non‑quantitatively described as either deep salvage or someone who has an Andromeda strain bug with diverse mutations that nullifies virtually everything that is available.  Those are different.
		I think that was the problem this morning.  And I agree there was a problem.  This is a very difficult discussion.  It is also a terrible part of the literature to read.  It is scientifically dirty because it is so complex.  And we're just beginning to tease that out.
		I think it is very important that as people discuss how they want to design trials, they discuss whether it is the first group that the FDA started with or the last group that we digress to at times.
		Those patients usually get what I call the end group that have nothing available to them, have any profoundly low CD4 count, and have a pretty high, whatever you want to define that, RNA load.  They get a "Throw the kitchen sink at them" philosophy.
		And that is no one is going to enroll those patients in the real world for a study if they think they have the advent of a horrible opportunistic infection or death within a certain period of time.
		I think you have to decide how you want to treat the first group, which are those that are more amenable to study design.  I like to see John shaking his head because the other group is going to be very difficult to study and will be studied later down the line when you know more about the toxicities if they're studied at all.
		Now, the other point I wanted to make is why I think this is an interesting, yet scientifically dirty subject.  And that is some of the stuff that Dr. Deeks has taught us has been really profoundly interesting.  And that is the patients in this group that have failed a couple of times that then get a half a log effect on viral RNA but do well or the discordance that you see at times, even long‑term, between CD4 and RNA levels.
		I think about this like the Committee might have thought about resistance testing five or six years ago.  Now we're dealing with possible different viral quasi‑species, different strains.
		No one has mentioned the bugaboo term of "fitness," but that has started to be developed as an indication of why certain of these people may do better than others at the same viral load.
		Dr. Mellors does some of this work.  Dr. Dequilla has had a nice study.  And fitness is not just replication, but it should better be defined as virulence.
		So I think that what you should try to dissect out of these studies is those that you can really study.  Right now I think it is where the FDA put those terms at the beginning, which is going to be hard enough.  At the same time, try to dissect out the scientific meaning for the dirtiness of the findings in this complex group.
		ACTING CHAIRMAN GULICK:   I'm going to take two more comments:  Ms. Delph and then Dr. Mellors.
		DR. DELPH:  Thanks.  I won't reiterate Dr. Pomerantz's point, which was going to be my first, that drug companies are not going to enroll patients who have no options left.  It doesn't make sense, and they just won't do it.  It is not going to be to their benefit.
		My other point is that while I think it will be difficult to get companies to work together, I think we are here to discuss scientific issues and scientific validity.  I think we are here to give the FDA advice on how to proceed, our best scientific advice, and to ask the FDA to take that scientific advice and try and get the companies to follow that scientific advice in their registrational studies and not simply to start off by saying, "Oh, well.  The companies won't get together.  They won't do it.  So let's throw factorial designs out the window."
		From what I have heard, factorial designs seem to be one of the better scientific options in my opinion, probably the best that I have heard, the modified factorial.
		I think we would be failing in our duty if we simply threw it out the window, as scientifically sound as it is, because we don't think we can get the companies to work together.
		ACTING CHAIRMAN GULICK:  Dr. Mellors?
		DR. MELLORS:  In an attempt to ‑‑ I mean, it's good to break apart and have differences of an opinion.  In an attempt to form a better union between this side of the table and that, let me say that the factorial design ‑‑ Roger said this nicely.  My comments about the factorial design were directed towards patients who have a limited life span and desperately need more than one investigational agent.  Okay?
		I don't want to see the agency say, "Well, you have to do factorial designs in this population."  In the less advanced, less desperate population, the factorial design does provide some efficiencies, particularly the modified factorial design.
		And I would just like to throw it back at the agency.  Are you totally comfortable with a modified design that excludes the, quote, "double" placebo arm or control arm that you can tease out the individual toxicity of each component in the trial if there is an interaction and the gating interaction potentially between toxicities in the A plus B cell?
		DR. MURRAY:  It's no different from looking at something that might include low dose or ritonavir.  Who knows what that is going to do to the PK and the toxicity or any other drug, for that matter, a delavirdine or efavirenz, which might, you know, induce?
		The problem is not unique to factorial design.  It's a problem of combination studies.  There is a risk of not being able to tease out.  There is a risk of any study failing.  But I don't think it is more in the factorial than in any other combination study.
		DR. HAMMERSTROM:  All of the designs we've been doing since the first two or three drugs came on have always been new drug A plus X where X is a collection of drugs that have already been approved versus X alone or versus X plus Y, where Y is a known active agent, whether you're doing superiority or equivalence.
		So it has been a long, long time since we have ever had an ability to look at only what new drug A does in the absence of anything else.  There is always something.
		Everybody for the last four or five years, all the trials, drug A has always been added onto other drugs, most of which are known to have toxicities and have contributions.  And, in fact, the inference we're making is that, let's say, if you add nelfinavir to 3TC plus AZT and you get a benefit relative to what AZT and 3TC alone would give you, then when you add nelfinavir to other combinations that may not include either AZT or 3TC, we expect you will probably get a benefit.  But that inference is not based on observational data.
		Certainly the FDA does not require the study of every conceivable one of the ‑‑ there is now 215 power with 15 agents ‑‑ actually more of that because the number of different two, three, four‑drug combinations you can make now with approved agents is somewhere like a million.  So we don't study all of them.
		DR. JOLSON:  Just as a final point, it would be rare for us to look at a study in isolation.  We're going to look at it kind of in the collective database.
		For many drugs, there may be other study designs that would be more straightforward that could provide additional safety data.  This would just be one more piece.
		ACTING CHAIRMAN GULICK:  Let me try to summarize the discussion briefly.  There was a consensus around the table that treatment options in this particular patient population are very much needed.
		We recognize that this is a heterogeneous population.  It is an advanced population in some cases, quite challenging, critically ill, and in some cases with a high risk of mortality and few options for treatment.
		Several people noted that there are subsets of patients within this patient population ranging from people who do have options to those who have no options at all.  It is worth pointing out that often the group with no options is the one that needs the options the most.
		As an objective for our studies, we want to identify drugs or strategies which result in virologic and immunologic improvements, but our ultimate goal is really to improve clinical endpoints; that is, survival and health.  Another objective is maximal access to agents which could have these positive effects on virologic, immunologic, and clinical endpoints.
		Testing in this population is challenging.  And there is a basic conflict which I think came out in the discussion between trying to show the individual drugs' efficacy and safety versus coming up with a strategy which will actually have benefits in this challenging patient population.
		I think we agreed around the table that you need to start by optimizing the background antiretrovirals as much as that is possible using resistance testing and allowing access to all available agents, both approved and expanded.
		There was a feeling that it may be reasonable to tolerate a higher incidence of toxicities in this patient population.  And it was pointed out more than once that weighting for new drugs may not be an option for some members of this population.
		In terms of a conventional registrational, people agreed that we still wanted to see antiviral efficacy.  Some suggested as short as 10 to 14 days with a drug would be sufficient as mono therapy to try to decrease the emergence of resistance.
		Safety.  People felt that longer data was needed, 24 weeks being standard or even more.  Along with registrational development, people felt a comprehensive approach was appropriate, that some of the supportive data that we would like to see is increasing doses in this patient population, a frank dose‑responses curve using PK enhancements to try to overcome resistance, defining drug‑drug interactions earlier in drug development, particularly with these patients who are on multiple other agents, and assessing viral fitness in this particular patient population.
		Some of the novel designs that we talked about today:  single arm, with or without historical controls; an early versus delayed introduction of a new agent; using a crossover design with the same early versus delayed; differential randomization, either two to one or three to one, among certain arms.
		An early switch if the drug is shown to be ineffective was another strategy mentioned.  We spent a lot of time talking about factorial and modified factorial designs.  I won't reiterate the points made there.  And, finally, long‑term cohort studies in this patient population were all mentioned.
		Finally, I think there was a consensus around the table that we would like to see some pressure put upon the pharmaceutical companies to work together, particularly in this patient population, that the number of drugs available at any one time may be limiting, although, as was pointed out, there are many in Phase II of development; and, finally, that expanded access may be the only hope for many of these patients and that we should encourage earlier development of these programs.
		With that, I would like to have us break for lunch.  It is 25 of 1:00.  We will reconvene at 1:30.
		(Whereupon, a luncheon recess was taken at 12:36 p.m.)

	A‑F‑T‑E‑R‑N‑O‑O‑N  S‑E‑S‑S‑I‑O‑N
	(1:35 p.m.)
		ACTING CHAIRMAN GULICK:  We'll get started again.  Welcome back from lunch.  We would like to start the afternoon session.  Dr. Jolson would like to make a couple of clarifying remarks based on the discussion this morning.
		DR. JOLSON:  The discussion this morning was fascinating.  It's probably worth mentioning that you all are here at a two‑day meeting.  We realize that there is a lot of material to cover.  We would have even had this as a two‑day meeting except for the fact that there was an NDA that needed to be discussed yesterday.  We thought that three days would be kind of dicey at the beginning of January.  So it doesn't surprise me that it really took several hours to work through and highlight some of these dilemmas.
		I just want to, though, just reorient us because I think we have identified both population differences and differences in clinical needs for different populations and again ask you as you think through the next series of questions to perhaps broaden your discussion to include patients who are treatment‑experienced but who aren't necessarily the very illest patients and because we believe that current drug labels and future drug labels would be greatly improved by inclusion of those clinical trials.  We think that those trials are more likely to be done, particularly for registrational purposes.
		And while we totally acknowledge the need for treatment options for the illest patients, we also agree with some of the comments earlier this morning that it would be extraordinarily difficult to do comparative trials.
		So that isn't necessarily where we as folks who advise on drug development are necessarily putting all of our attention.  There is plenty of room for improvement in current drug labels.  And we ask you all for your thoughts on clinical trials that would provide that sort of information.
		ACTING CHAIRMAN GULICK:  Thank you.
	OPEN PUBLIC HEARING
		ACTING CHAIRMAN GULICK:  We're now going to enter the open public hearing portion of the meeting.  We're going to take the listed speakers somewhat out of order.  The first speaker will be Emmanuel Trenado, who is a member of the Coalition of AIDS Organizations in France.  I just spoke to him.  So I know he is here.  Oh, there he is.
		MR. TRENADO:  Good afternoon to all of you.  I am here only to commend the EMEA proposal on the new points to consider to register new drugs for patients who fail all existing regimens.
		So I only have four slides, and I'm going to be very short and will leave it to Daniel Vittecoq, who is a member of the EMEA, to present you the points to consider.
		The background in Europe is a bit different than what you have been experiencing here in the U.S.  In Europe, expanded access programs because we are so many different countries are run very differently from one country to the other.
		For example, a drug such as Ziogen took a year and a half.  It had a year and a half delay compared to access in the U.S. for countries such as Italy.  France was faster, but some of the European countries, it takes longer to open up those expanded access programs.  And there is this particular situation.
		We all share this common dramatic situation where we are in great need to have access to new drugs.  And this is particularly the case in Europe.
		The new points, the AIDS community in France and in Europe have taken on both the new points to consider as a way to accelerate access to new drugs in the whole of Europe.
		Next slide.  So we have commented on the proposals.  And we made a few remarks.  We have a proposal to make to the EMEA.  The first remark concerns the mono therapy phase trials.
		You will see in the details what the EMEA is proposing, that the community feels that the mono therapy trial should be differentiated according to the drug that is being investigated.  And it should be as short as possible.
		Then you will see that the EMEA has come up with the idea of selecting refractory and non‑refractory patients who are in need of salvage therapy.  And they feel that registration trials should only be run in patients who have treatment options.  So they are called the non‑refractory patient.  And we agreed to that proposal.  We have seen it this morning.  We think it is very difficult to run ethic trials in patients who are in deep salvage situations.
		Next slide, please.  So the proposition we would like to make to the EMEA is that while the industry  might be selecting the patients to enter those Phase III trials, it's like on the resistance testing to do so.  And they are separate, the patients in two groups:  the refractory and the non‑refractory patients.
		We feel that the patient who will be labeled "refractory" should have access if they want to to the drug that is being investigated outside of the clinical trial in an expanded access program.
		And we feel that this should be made compulsory to the industry, and it should be inserted in the registration package, that the drug should be made available in refractory patients who have tried to enter the Phase III trials.  And they couldn't get around saying, "There's no drug.  We could not open up this expanded access," et cetera.  So this is a proposal, the main proposal the community is making to the EMEA.
		The last point is on pharmacovigilance.  We know that in some European countries, pharmacovigilance is not running very well.  And we feel like that it should be an occasion to really rectify and to set up a European plan to improve pharmacovigilance in Europe.
		Thank you very much.
		ACTING CHAIRMAN GULICK:  Thank you.
		Our second speaker is Dr. Otto Ah Ching from Oxo Chemie.  He will be using a remote mike.
		DR. CHING:  I would like to thank the Committee for the opportunity to be able to speak with you.  I don't have slides today.  Basically I would like to address some questions.
		Oxo Chemie now is engaged in a Phase III trial currently with our IND and with the FDA currently.  I have three specific questions I would like to address to the Committee if possible, one being historical data with HAART as standard of care has shown that CD4 and viral loads in these populations with AIDS demonstrates some significance with little sustained changes.  Should the Committee consider a more prognostic measure or marker?  Heaven knows we don't need another surrogate marker.  But would they be open to considering CD38 as a possible prognostic marker in salvage therapy?
		The second question is immune‑based therapy.  In salvage therapy, what standards will determine efficacy and safety if these therapies are not antivirals?  Should we then look to more of the clinical benefit and clinical endpoints weighing heavily more on the clinical benefit for these patients, rather than surrogate markers or lab surrogate markers?
		And the last question is:  In salvage therapy, should these studies be open label and comparative with historical data as standard of care measuring induction period to onset of primary SAE or AIDS‑defining event and resolution?
		I think these are just basically three questions that we as a company wanted to present to the Committee and get some feedback on.  And that's all I have to say.
		ACTING CHAIRMAN GULICK:  Thanks very much.  I hope to address some of your questions in the discussion period later this afternoon.
		The third speaker is Mr. Michael Marco from the Treatment Action Group.
		MR. MARCO:  Good afternoon.  I am Michael Marco from the Treatment Action Group.
		This morning I heard a rumor that Dr. Jolson was going to be leaving the agency.  I wanted to let Dr. Jolson know that TAG has a job opening and that you can see me after the meeting for an application.
		(Laughter.)
		MR. MARCO:  We do like your work.  And TAG thanks you and your division for putting together this meeting.  The last time I was here and talking to this Committee was at the adefovir hearing.  That was a sad day.  As we know, it was the first time that the agency did not approve an HIV drug.
		Today is a much better today.  It's a brighter day because now we will be looking at trial designs and hopefully agree on some trial designs where we can help salvage patients, the ones who most need it.
		Today is also a day where industry can stop saying that the FDA does not give them a clear message.  Time and time again they tell the community "We don't know what the FDA wants.  We get mixed messages."  Hopefully they will hear loud and clear and through more discussion, things in writing that the agency puts out, they will know what to do for trial designs.
		Most of you have the position paper that TAG wrote.  At least I know the Committee does.  Some of you in the audience do.  I have a few extra.
		The position paper will be available on the TAG Web site.  It will be available on Monday.  And the Web site address is basically www.treatmentactiongroup.org.  It's all one word, treatmentactiongroup.org.
		I won't go through the position paper.  It's four pages.  You can all read it.  It's very clear.  I will tell you that we come away with supporting the modified factorial design.  We do believe that it is an excellent design.  I think we will hear a little bit from Dr. DeGruttola, who will explain why it can be so beneficial in this patient population.
		Today we heard that there are not that many drugs or really no drugs or only one drug and so how could we do modified factorial design.  Well, I know of at least four drugs that are around Phase III right now.  We're in Phase III.  We have the three T‑drugs, and we have the BMS protease inhibitor.
		These companies are rapidly developing HIV drugs.  That's why they need to be getting together now or even before they go into Phase III so that we can get them together to agree on a modified factorial design.
		And the FDA will need to give clear incentives.  The FDA will need to help them out and also probably be somewhat gentler in the labeling because we won't be able to tease out all of the various toxicities.
		In the modified factorial design, it is important to note that a lot of patients won't be able to go in the study and a lot of patients won't be able to go into any of the studies that the FDA presented earlier.  Many of these patients, especially the ones that Dr. Deeks talked about, only have ten CD4 cells.  They cannot put together an optimal background regimen.
		Many of the studies now that use the term "optimal background regimen" say you need to be susceptible to at least two drugs.  For these patients, we need to make sure that they are the ones that first get the drugs that are out on expanded access.  And industry needs to be a little more proactive and work more with the community in getting drugs on expanded access earlier, not a month or two months before the drug is approved.
		As far as efficacy is concerned, we do believe that for a drug that shows great activity, shows great promise, possibly a home run, if there is such a thing, that 16 weeks might actually be enough for efficacy compared to the 24 weeks that we use now for accelerated approval.
		We would say that for safety, we definitely want at least 24 weeks of safety for accelerated approval.  And we still want the 48 weeks for full approval.
		Lastly, we do need to make sure that, especially for the modified factorial design, PK studies are done.  And they need to be done ahead of time with a decent amount of patients.  We don't want the debacle that we had with ACTG 359.
		I appreciate you having me speak.  And, again, I thank the agency.  And I hope that the afternoon is just as contentious as the morning was.
		ACTING CHAIRMAN GULICK:  And I think you can count on that.  Thank you, Mr. Marco.
		The last two speakers will be using slides with their presentations.  And that is why we have put them last.  Next is Dr. Vittecoq from the EMEA in France.
		DR. VITTECOQ:  Mr. President of the Advisory Committee, members, Mrs. Jolson, and Jeff, thank you very much to provide the opportunity to the EMEA in Europe to give you the guidelines which have been adopted or will be adopted in the next month by Europe.
		Maybe just before starting, for the CPMP members, you have to know that the research for such drugs, which is very important from a public concern in Europe, is not a national procedure nowadays.  It is in Europe.  This is orchestrated by the European drug agency and a special committee, which is a CPMP.
		So there was a debate at the CPMP last year about the evolution of the AIDS epidemic.  And it was concluded that, despite substantial improvement, there was still an increase in the number of patients who failed the treatment.  And this was where the public was concerned.
		As it was told previously by Emmanuel Trenado and as a problem in Europe is the availability in the early access to drugs in different countries.  France has quite a performance at this time, which is a temporary authorization of use of drugs.  And most countries do not have any access to drugs.  So this is an eventuality which is politically not acceptable.
		Another point which was a matter of debate to the CPMP is the length of the trials.  In 48 weeks, approval for promising new drugs is not ethically acceptable for patients who are failing.
		The last conclusion was that companies are not very inclined to implement clinical trials in advanced patients for various reasons.  It's more difficult to reach endpoints.  And, secondly, the tolerance of the drugs is not very good in these populations.
		So the CPMP asked the French Agency for the Safety of Health Products to address a proposal which has been a matter of discretion six months ago.  And the final paper will be accepted in the next month.
		Next.  So a few considerations before we improve in the evaluation of treatment because we have given a particular place to very different parameters.  And this is a reality that cannot change.
		Antiretroviral drugs are not similar to antiviral drugs.  Antiviral drugs are not even comparable to all other anti‑infective agents, even tuberculous meningitis.  New figures of the development of antiviral agents seems to be more closely similar to antineoplastic agents.
		In our way of thinking, a patient in failure is like a patient with fatal status.  And adding concern, we have to promote the development to reach limited indications in patients with fatal status.  And then indications may become broader later on with the case.
		The situation of the epidemic in Europe is very different nowadays.  This is a perfect relief sentence, but AIDS belongs to the past.  That's not where we come as physicians.  I know AIDS is 20 years.  So some patients are still dying, but the number of patients and the way to die in AIDS is clearly different.
		And I should say as the guy from the CPCRA this morning, I do suggest that we change the term of "salvage therapy," which is not appropriate.
		Salvage therapy in AIDS is not a new faction.  Salvage therapy started as soon as it was registered, delavirdine, which was 15 years ago.  And as soon as patients have failed delavirdine, didanozine was the first salvage therapy.  And as soon as patients had received didanozine, optimal modification had been performed.
		So, really, the situation now is at treated patients, which can be defined as good responders and poor responders.  We have to focus our attention on patients who are poor virological responders.
		I do believe in the next future, that we will have to take into account another picture, which is immunological response.  Some patients with a good virological response are poor immunological responders, and some are not.
		The aim of the proposal is to improve the quality of the registration package, which is not always performance.  And the second point is that we have to anticipate the way the drug will be used.  It is not acceptable nowadays to have a drug like saquinavir, which has been used as a mono therapy of protease inhibitors, as it has never been used without ritonavir.  And I should nearly the same with amprenavir.
		Next.  So, to improve the way to treat the patients in these kinds of failures, we have to start I think from the drug.  We have a new drug.  An applicant is asking the questions, "What can I do if these aren't antiretrovirals?"
		We have to insert the main question, which is:  Is it a major interest in terms of resistance profile or pharmacokinetic parameters, which is in the Phase I and II trials?
		You have two answers, "Yes" or "No."  If the answer is no, there is no modification of the guidelines, which are quite performance.  And that would suggest maybe to enhance the length of evaluations.  Forty‑eight weeks maybe is not enough.  And maybe in the next future, we have to enhance the follow‑up of the patients up to 96 weeks due to a better package for safety.
		If the answer is yes, we have to speed up marketing authorizations in antiretroviral‑experienced patient populations.  New registrational clinical design, such as identification substitutions, and the time of assessments from our point of view ‑‑ I would speak about it ‑‑ is less than four weeks.  And durability is 12 to 16 weeks.
		Next.  Major interest regarding resistance profiles nor of few cross‑resistance with other drugs in the same family and the unique resistance profile, of course, due to new mechanisms of action is quite easy to understand.
		What is important from our point of view is the necessity to test the virological activity on a sufficient number of strains coming from pretreated patients, which is very important and very commonly not enough in the package at time of registrations.
		Next.  Major interest we're getting from communities when there is no activity since profile.  Highly developed plasma and intracellular considerations, of course, may allow to recover in antiviral activity situations.  This has been well‑demonstrated with ABT 378.
		And it's necessary to compare the IC5090 of the antiretroviral to do the other regimens from the same pharmacological class and of the same cell lines, which is not with performing in the package.
		Next.  Phase II studies.  This is very important before you start Phase III studies.  I think you have to have an examination of these points.  Those examinations have to be well‑established in naive patients or even today in uninfected patients and will have to be confirmed in Phase II or III trials through PK monitoring.
		It is necessary to study the slope of the decrease of the viral load in relation to the pharmacokinetics.  We have learned this with the parameters, of course.  Interaction studies, in particular, we found antiviral drugs likely to be combined with the investigational agents.
		Next.  The choice of the target populations in Phase III trials, clearly we need flexibility.  We have to provide guidelines, of course, but we need to be flexible.  We have learned that as soon as we have marketed a drug, it will not be used as we had thought it would be used.
		So the compromise is to be as much as possible as close to the clinical practice and the necessity to clear assess impact of the new antiretroviral drug.  So we have chosen patients having failed at least the first line of a pharmacological class.  And these patients have been treated for a prolonged period with many antiretroviral agents.
		Next.  We have two possibilities.  In early virological failures, we have detectable to moderately increased viral load, less than four logs, or non‑responders, which means viral load higher than four logs.
		Genotyping and phenotyping would be performed at this line.  You have got to perform the loss of ability, of course, for the seven that exist and for the treatment with the other investigational drugs.
		Next.  The other target populations, which is the refractory to all the available therapy, which is, as we have told you, deep salvage, I think this is the sam thing.  We know it is very difficult to perform studies in this population.  So clearly efficacy is probably enough.
		It is difficult to assess the efficacy magnitude of anyone in these populations.  It is difficult for companies to perform studies in these populations with an urgent need of care.  In these populations, clearly it is much more important for the safety than for the efficacy of the drug.
		Next.  The methodology of the Phase III trial is that of superiority, not in equivalence, a superiority.  Design is clear, closer to the current strategy in clinical practice for all treatment‑experienced patients.  There are two strategy substitutions or intensification trials.
		Next.  Inclusion criteria:  patients treated with stable combinations for a significant period of time.  First, we do believe that it is necessary to have a comprehensive failure which is less than four weeks or even less than two weeks but with agents which are likely antiretroviral agents, nucleoside, non‑nucleoside parameters.
		Of course, we need to have NSL before four weeks.  With other drugs, such as different immunovirological agents, maybe longer time can be taken into account.
		For the antiretrovirals that we know, if you have no response at four weeks, the drug is not active.  So we can perform studies in addition of substitution of the investigational agents to the baseline regimen of authorizations.
		And there is an optimization phase which can require 12 or 16 weeks, addition of the other agents in both groups based on registration test and strategic possibilities.  Our strategy is to optimize at baseline.
		Next.  Shortening the time of assessment allows to speed up marketing authorizations to avoid emergence of resistance in patients enrolled in clinical trials.
		It is possible to assess efficacy in less than four weeks, like previously.  And that is the same availability of the virological impact and safety profiles required at around 16 weeks.
		Next.  The endpoints, of course, it's the impact on the viral load, comprehensive percentage of patients that should be presenting at viral load, all demonstrations of an increased viral load between 0.5 or one log between two groups.
		Some other endpoints include:  the maintenance of control of viral load; of course, the assessment of safety profile; the treatment as to be evaluated regarding the baseline viral load, of course; predictive value of genotypic and phenotypic resistance would be taken into account; and correlation between pharmacokinetic parameters and virologic agents has to be analyzed.
		Next.  Some points are very important if we speed up the procedure, of course, and if we limit the duration of authorizations.  It is not acceptable.  This is very important for the applicants, all of you in this room.
		Dropout rate should be very limited.  In particular, a short time is not acceptable at this time.  We have so many patients.  We have lots of follow‑up in clinical trials.  So dropout rate has to be very, very limited.  And explain, please.
		Sensitivity analysis should be performed with facing data, of course.  A PK/PD correlation should be performed to better understand the failure to treatment.
		Next.  About the combination of the investigational agents to other drugs, which is not currently reduced, of course, which is the expanded access drugs, it is not credited.  It is currently performed on a baseline.
		Some drugs are used on a compassionate basis, but you have to ensure from a methodological point of view, of course, that there is no added toxicity, that the integrity of the partner has to be clear, the drug interaction has to be known.  No integrity, there is none to occur, of course.  The partner has to be well‑balanced in both arms.  And, finally, we suggest strongly a stratification.
		Next.  In conclusion, a new approach in the evaluation of anti‑HIV drugs are allowed to increase the number of available drugs in patient populations, of course, to focus the research on antiretroviral‑experienced patients.
		When drugs will be reduced with limited indication at the beginning, one may assume that the indications will become broader later on, of course.  This means close collaborations between companies, research in situations as authorities in patients, of course, implementation of Phase IV trials regimen strategies used, for example, in Phase IV pharmacokinetics monitoring.
		And, to close, we have to have close collaborations, which is, of course, very, very important.  And, of course, if there are close collaborations between Europe and the States, it is probably better.
		Thanks.
		ACTING CHAIRMAN GULICK:  Thank you, Dr. Vittecoq.
		The last person to speak at the open public hearing signed up to speak is Dr. Jim Rooney representing the Intercompany Collaboration, the ICC.
		DR. ROONEY:  Thank you, Dr. Gulick and Committee.
		My name is Jim Rooney.  I'm from Gilead Sciences.  I'm here today representing the Intercompany Collaboration for AIDS Drug Development.  The ICC, as the group is known, is an organization of pharmaceutical companies open to any pharmaceutical company that is involved in the development of new drugs for the treatment of HIV infection.  The current membership is listed on the first slide.
		The ICC has been in operation since about 1993.  It is relatively unique.  I don't think a similar organization exists in any other therapeutic area.  And I think it has fostered a great deal of degree of collaboration on both a medical and scientific level and communication between the member companies involved.
		Next slide, please.  The goal of the ICC is to share information and antiretroviral drugs in an effort to develop improved combination therapies for the treatment of HIV infection.
		Next slide, please.  In discussions with Dr. Struble in preparation for this meeting, she asked us to comment on three points.  The first is the use of multiple experimental agents in registration studies for salvage therapy.  The second was the use of placebos in salvage trials, particularly the sharing of those between companies.  The third is to comment generally on issues in the design and suggestions for the design of clinical trials in salvage therapy.
		Next slide, please.  With respect to combining agents, experimental agents, in salvage therapy, the current approaches, as you are aware, are geared to demonstrating the incremental benefit for each new drug.
		However, the long‑term durability of the response is more likely to reflect the activity of the entire regimen, rather than the activity of a single agent.  Therefore, for salvage therapy, we do believe that it is reasonable to consider combining more than one experimental agent or registrational studies.
		And that is, of course, providing that the regulatory environment is such that it is clear how those agents would be approved and that there would be some incentive for performing studies in this particular patient population, as opposed to other patient populations, where the designs are more clearly established and the benefit more clearly expressed.
		Next slide, please.  The rationale for combining agents is increased potency of the new regimen and to limit the development of resistance to new agents.  And it would be indicated in situations where in vitro data demonstrates synergy or additivity.
		There would be minimal expected drug interactions or one would be able to compensate for those expected interactions.  And there would be minimal overlapping toxicities or toxicities that would be manageable.
		Issues are multiple.  They have been elucidated this morning.  They include isolating the benefit of a single therapy would not be simple given the limitations on study design, a limited number of new agents are available at any given time and they're in different stages of development and there are different amounts of available drug supply for these types of studies.
		New data in any trial, new data, safety or efficacy, emerging during the study can affect the conduct, outcome, and acceptability of the study results.  And certainly in the case when you're combining more than one experimental agent, this is even more so the case.  There are limited data on long‑term safety in agents that are not yet approved.
		The attribution of safety events can be complicated with agents whose safety profile is not completely elucidated.  Unexpected drug interactions can and do occur and can complicate the interpretation of the study results.  And unexpected safety issues with one drug could affect the other drug or the ability to complete the study.  And this has certainly occurred in cases even where there are less than two experimental agents in a single trial.
		Nonetheless, because of the strong rationale for combining agents, there are a variety of settings where the use of more than one experimental agent has already occurred.  These include expanded access registration studies and nonregistration trials.
		In expanded access, the rationale is to allow construction of more potent regimens and to help avoid functional mono therapy, to make better treatments available to thousands of patients before commercial availability of the new products.  And because of this, most of the most recent expanded access programs have indeed allowed the availability of other experimental agents.  And several of them are listed here on this slide.
		Next.  What about the use of more than one experimental agent in registration studies?  This slide lists some of the trials either currently underway or previously conducted that have allowed the use of other experimental agents as part of the treatment design.
		In most instances, these have been included as part of the background regimen in some instances as part of a combined part of the single arm in the study.
		Generally speaking, these are examples of studies to date, but I think there are even different types of designs that we could think of where we could use experimental agents in ways that would be beneficial to patients and perhaps with different regulatory guidelines in a way that could allow for either registration of single or both agents.  I'll discuss those, actually, or some possibilities when we discuss clinical trials in the salvage setting.
		Next.  I would like to turn briefly to the issue of the use of placebos.  Obviously it is an important component of the design of many trials.  This slide outlines the various registration studies that have been conducted where placebos have been obtained from other companies, some of the programs more recent and some more distant.
		In most instances, the patient population has been either antiretroviral‑naive or patients with limited treatment experience.  There are, of course, multiple examples where placebos have been provided by companies for nonregistration of government‑sponsored trials.
		Next slide, please.  But what about the use of placebos in a salvage setting?  In discussions amongst the companies, it was felt that it was unlikely that placebos would be requested frequently in salvage studies, particularly in cases where there would be multiple experimental agents.
		Obviously if a single company is conducting a trial with their own agent, they have their own placebo.  So this is an issue of really more than one experimental agent and the placebos for those.
		There was a concern that it would add pill burden and may decrease compliance.  However, in those settings where it did make sense, I know there has been some discussion of factorial design this morning.  And if it could be agreed upon in a study like that, then certainly the participating companies who do supply the investigational agents could supply the corresponding placebo.
		Turning your attention to issues in clinical trial design in salvage therapy, the issues are multiple.  Most of these have been touched upon this morning.  I won't reiterate them.
		Next.  What are some of the current designs that are currently being used for clinical trial designs by companies in treatment‑experienced patients?  They include superiority designs.  Looking at regimen A, B, C, D and in a salvage setting, this is most commonly an optimized regimen to which you add either drug X or placebo.
		One of the issues with this design in the salvage setting or entirely treatment‑experienced patients is that the incremental drug benefit for a fifth or a sixth drug is often small and difficult to demonstrate.
		Equivalence designs, where you look at fixed regimen A, B, C, D and compare it to, for example, A, B, C, X, where drug X is compared to drug D.  In a salvage setting, there really are no fixed standard of care regimens to serve as the control.  And the contribution of drug X in the regimen, in addition, the corresponding delta, the statistical parameter used to calculate power, difficult to estimate.
		Next.  Before turning to proposals for new study designs, I would like to touch briefly on issues of endpoints.  I know they will be discussed this afternoon.
		As was mentioned this morning, the endpoints commonly used in other registration studies in less experienced patients, such as percent below detectable, is a categorical endpoint.
		Unfortunately, response rates have been low in most studies in treatment‑experienced patients.  It may not be a sensitive endpoint for patient populations with high levels of HIV RNA at baseline and may miss clinically significant changes in HIV RNA.
		Next.  Alternative ways of looking at the endpoint of HIV RNA, such as looking at change from baseline or average area under the curve, DAVG, may be a better primary endpoint because it may be more sensitive to changes that could be clinically relevant.
		This endpoint is currently allowed by both U.S. and European regulatory guidelines and is included in some antiretroviral labels.  And, as you know, meta analyses from studies in patients with advanced disease conducted by the ACTG and FDA have shown clinical benefit associated with about a two and a half‑fold reduction, about a .4 log change in HIV RNA with a degree of benefit increasing proportionately with the degree of reduction in HIV RNA, 72 percent reduction, clinical progression for one‑log reduction in HIV RNA at 24 weeks in the Marshener paper.
		Next, please.  Well, what about some new study designs in this patient population?  There are no easy answers, obviously.  So what we would like to do is review just a few, some of those that have been discussed in the context of this morning's discussion and a couple of other proposals as well.
		With respect to factorial designs ‑‑ and this is the simple factorial.  The optimized would obviously have arm one deleted and just look at two new drugs, A and B, AB and AB.
		Next slide, please.  Advantages would be ideally can answer many questions with one study is one way of including more than one experimental agent in a study deign.  I think certainly those are favorable aspects.  A sample size could be larger or smaller depending upon the numbers of questions asked.
		Next.  However, there are, as was discussed this morning, some limitations of this design.  Included amongst those, if you do believe that adding single agents to optimized therapy is not indeed an optimal regimen, there would be in one type of factorial design, at least, a single agent added to background therapy.
		If three agents were available, then obviously that wouldn't necessarily be the case.  But it's possible that patients may be exposed to less than optimal therapy, a significant number of patients.  The point of combining experimental agents is because single agents have not been optimally suppressive.
		More importantly, however, from a regulatory perspective is that interactions between treatments can undermine study results.  Unfortunately, interactions are not uncommon, treatment interactions.  They can be based on PK, virologic, or metabolic reasons.
		The main effect of the single drugs A or B in this kind of study design could be kind of difficult to estimate in the presence of a significant interaction between A and B.
		It was mentioned this morning that if the interaction is positive, it wouldn't negatively affect the regulatory approval of either agents A or B.  However, if they're not positive, then it could affect the likelihood of regulatory approval of those agents.
		Unfortunately, there is actually regulatory precedent for this where a recent example of a registration study was invalidated, reviewed by this Committee because of a concern regarding a drug interaction in that trial.  And this was Gilead Study 417.
		For all of these reasons and in discussions amongst the companies, I think most companies feel that factorial designs are not an optimum way to develop for regulatory approval drugs in a salvage setting.  However, they could be considered for nonregistration exploratory trials.
		Next.  What are some other approaches?  As was discussed this morning, allowing use of other experimental agents as part of an optimized background regimen is certainly a possibility, a good design option.  It is currently being used in several trials.  And it is possible to include agents, not only in expanded access but also earlier in development.
		In this case, however, although two experimental agents are involved in the regimen, regulatory consideration is only being given for one of those agents.
		An alternative approach, which could be used for single drugs or for combinations, would be very similar to the proposal, the two‑part proposal given by the FDA this morning or the European proposal just presented by Dr. Vittecoq, where short‑term activity was assessed during an early period of mono therapy or add‑on therapy and longer‑term safety was evaluated in combination therapy.
		It makes sense for the reasons that have previously been elucidated, demonstrating antiviral activity in the target patient population, limiting time on mono therapy, development of resistance.  And on a regulatory basis, this method could provide a more efficient way of identifying and making commercially available new agents that could be used for patients most in need.
		Next slide, please.  Very similar to the design just mentioned, here drug X and placebo or no therapy are evaluated over an early period of time.  The duration of mono therapy would be individualized for each drug intended to limit the development of resistance.
		For those agents where development of resistance was especially a concern, it would be possible certainly to add drug X to the failing regimen, instead of being evaluated as mono therapy.  And then all patients would receive drug X plus the optimized background, which could include other experimental agents.
		Period of combination therapy, as alliterated by Dr. Vittecoq, would be customized to maximize benefit for each patient based upon resistance testing, past treatment history, tolerability, potential drug interactions, et cetera.
		Next.  A period of mono therapy would provide evidence of antiviral activity in this patient population and short‑term safety and tolerability.  And it would be assumed that the short‑term antiviral activity should provide evidence of potential long‑term benefit in a fully suppressive regimen.
		There certainly are many examples of other drugs when given in naive patient populations that when given as mono therapy would be quickly associated with the development of resistance but when combined in an optimally suppressive regimen can provide a durable antiretroviral response for years.  So the same principle would be assumed to be applied here and that the durability would be a function of the potency of the regimen, not just the drug.
		Period of combination would provide optimal, potential optimal, therapy to all patients, would examine durability, safety, tolerability.  One could also monitor patients for development of resistance to experimental agent.  There are various variations on this proposal.
		Certainly one is to look at placebo control as part of the period of combination.  Most of the companies in discussing this I think favored a proposal closer to the FDA proposal this morning, where all patients would receive optimized therapy.
		Next slide.  This is a slightly more radical version of the same proposal and in this case attempts to make use of the benefit of using two experimental agents together.  And in this case, drug A and B would really be considered as one experimental therapy and, again, would be compared against either placebo or no therapy and then combined as part of an optimized regimen.
		Here it would be assumed that the benefit of drug A and B if it were indeed effective, that it would be approved essentially as a combination therapy itself but that the individual activity of these agents and how they contributed to the regimen would be worked out as part of studies ongoing in other patient populations; again, the same issues.
		There would be some regulatory issues obviously involved with these suggestions.  Could in the first case of the single agent Drug X based upon this proposal or in the case of the dual combination all experimental agents be approved based upon these types of studies?  Would additional studies in the case of combinations be required to clarify the contribution of each agent to the successful regimen prior to approval?
		Again, there could be implications also for negative study.  These studies are conducted without optimal information about how to use the drugs.  So if there was indeed a negative outcome from the study, could it diminish the likelihood of regulatory approval with a second positive study from a different patient population and would it limit the use of the drug in treatment‑experienced or heavily treatment‑experienced patient populations?
		So, in conclusion, general recommendations.  ICC member companies support the use of multiple experimental agents in salvage therapy.  We do not favor a factorial design for registration studies.  Studies of short‑term mono therapy combined with longer‑term combination for regimen consideration is the basis for regulatory approval.
		We do suggest that a positive study of two experimental drugs could support registration or should support registration of both drugs for an indication limited to that combination in salvage therapy with data from further trials to be used to extend the indication.
		Paramount, given the discussion this morning and the complexity issues, obviously flexibility in approach to all of these issues, study design, use of comparators and choice of endpoints, is very important.  And, really, each registration package should be customized to the drug in a patient population being explored.
		Thank you.
		ACTING CHAIRMAN GULICK:  Thanks, Dr. Rooney.
		That concludes the people who signed up to speak at the open portion of the meeting.  Is there anyone else who would like to make a public statement who did not sign up?
		(No response.)
		ACTING CHAIRMAN GULICK:  Okay.  So we will close the open portion of the meeting.  I return the Committee to our questions.
	CONTINUE QUESTIONS TO THE COMMITTEE
		ACTING CHAIRMAN GULICK:  We have done Question 1.  Question Number 2 is specifically considering some of the study designs.  And I would like to start with the three that Dr. Laessig presented in her presentation this morning.  Would it be possible to get those slides up from Dr. Laessig?  Oh, great.  That's a summary.
		DR. MURRAY:  That's the correct slide.
		ACTING CHAIRMAN GULICK:  Great.  Let's go with that.  All right.  I think I would like to consider them in the order that you presented them this morning.  Let's talk about add‑on, the add‑on, design first, which is number two on this slide.
		So that's optimized background plus drug A versus optimized background plus either a matching placebo to drug A or no treatment.  The charge to the Committee is to identify the strengths and weaknesses of this particular design.
		DR. JOLSON:  I just have one thing to remember.  When you look at optimized background, that's with the assumption that access to drugs available and expanded access is equally accessible to both groups.
		ACTING CHAIRMAN GULICK:  And resistance testing by the same regard.
		Dr. Eron?
		DR. ERON:  One thing we have not talked about with optimized background is actually to have a requirement for people to be sensitive to two drugs, let's say, in addition to the drug being studied.  So in a phenotypic assay or in a genotypic algorithm, you're only eligible if, indeed, you are susceptible to two drugs that are available to you.
		I think that might be somewhat more acceptable than kind of adding study drug A to anyone who qualifies, whether their regimen can be truly optimized or not.  I don't know what other people think of that approach to this design, but ‑‑
		ACTING CHAIRMAN GULICK:  Dr. Mellors?
		DR. MELLORS:  Yes.  I think Joe has hit the nail on the head.  It depends on how optimized optimized really is.  If your phenotypic or genotypic sensitivity score is one and you're looking at an add‑on therapy with a fragile drug, that's an unethical trial.  Okay?
		If the average phenotypic sensitivity score approaches three for the optimized background, then adding another agent is a nice way cleanly to demonstrate efficacy.
		I don't want to go back to the morning.  That was the point I was trying to make.  It's simple.  All of the comments are well‑taken that if you have lousy optimized background, it's a lousy design.  And this is one way to individualize designs for given patient populations.
		DR. ERON:  And having a score of two or three could be an entry criteria.
		DR. MELLORS:  That's correct.
		ACTING CHAIRMAN GULICK:  Dr. Cunningham?
		DR. CUNNINGHAM:  As I have said, the advantage of that is it is clean and easy and it certainly could only be done in people where the optimized background is a reasonable background.
		However, we know that even when the optimized background is a reasonable background, the failure rate is very high.  So there would have to be an early escape mechanism in that kind of trial.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi?
		DR. DeMASI:  Yes.  One of the issues that I would like to bring up for discussion is in this type of design, making the distinction between the activity of the individual drug, the study during the first two weeks, versus the efficacy of the regimen within the trial that is being studied in the trial and beyond that two‑week phases what is needed in order to demonstrate safety and efficacy of the regimen, including this new agent.
		ACTING CHAIRMAN GULICK:  And I think you are reaching towards the next design, actually, which is the two‑part hybrid that ‑‑ let's stick for a minute ‑‑
		DR. DeMASI:  Just to clarify, in the two‑part hybrid, you see that the treatment groups actually come together.  But what I am suggesting is the necessity for an additional randomized phase of the study beyond this two‑week period to further demonstrate or confirm the activity that you would see during the first two weeks of the study.
		ACTING CHAIRMAN GULICK:  Ms. Dee?
		MS. DEE:  I don't know how you would do that.  And that would be interesting to see that because, really, when you talk about switching ‑‑ I think this is right.  Maybe Victor or Dr. Hammerstrom can comment on this.
		Once you're over that eight weeks and then you have an early escape switch point, which I think that appears to be more ethical anyway, don't you really have an eight‑week trial?  I mean, isn't that the result of that?  So the data is eight‑week data.  Is that right or wrong?
		DR. HAMMERSTROM:  I don't think that's exactly right because you would say that at eight weeks, those who have failed on the placebo are allowed to add:  A) open label.  They essentially go into an expanded access program.
		But it need not be the case that everybody will have failed on background plus placebo at eight weeks.  Perhaps 20 percent, perhaps 40 percent of them have not failed and the rest of them would still be going on.  So you would still be collecting data for whatever fraction of them haven't failed out to whenever you make your accelerated approval decision.
		In fact, if people continue out to 36 or 40 weeks on background plus placebo and still haven't failed, you would still be collecting data on them on the comparator arm, even relevant to the traditional approval at 48‑week data.
		So what we would consider an eight‑week trial would be one where everybody stops on the placebo arm at eight weeks and switches to accelerated approval or switches to expanded access.
		As long as you are proceeding on the background plus placebo, you stay on that, at least out to the scheduled end of the trial, which is 48 weeks, then we wouldn't consider it an 8‑week trial.
		And you really are getting a comparator that goes all the way out there.  It shows that on optimum background plus placebo, you get a failure rate that goes down like this and maybe 10 percent of them are left at 48 weeks; whereas, on optimum background plus A, you've got a failure rate that goes down hopefully much less rapidly and 40 percent of them are still succeeding out at 48 weeks.
		ACTING CHAIRMAN GULICK:  Dr. Pettinelli?
		DR. PETTINELLI:  I was just going to say I agree with the statement that is being made.  In all the rest, even if you have like a one or two‑year duration, we have early escape for a single patient, not for a trial.
		I would also like to comment that the add‑on, as was stated by others of my colleagues before, is indeed possible when the patients are defined as being sensitive to drug at least.  So, again, we have to look very carefully to the patient population.
		I don't know how many of those patients would be in that category.  Probably the additional two experimental drugs would be the most common occurrence just because that will increase the sensitivity.
		ACTING CHAIRMAN GULICK:  Dr. Saag?
		DR. SAAG:  Yes.  That's what I was going to say.  Actually, it's probably healthy to have the morning discussion because it seems like we've got a little bit more clarity this afternoon.  And that is that looking at the top one compared to the second, the modified versus add‑on, I think that's exactly right.
		If it's early, which is what our charge is now, to look at people who at an early point failed two HAART regimens, all classes involved, that the add‑on may be the wise choice if, again, you have three drugs that are available and you're simply looking for the fourth and, like John said and others, it's clean.  That's very nice for registration.
		For the little bit more advanced, like, say, you could almost have it in the same study where you do an add‑on if there is a score of three and if the score is two or less than you go to the modified factorial.  And you could actually either have a separate study that runs concurrently, but at least you can cover the waterfront.
		But for those patients who have ‑‑ I was worried about the top one if you had three drugs available for optimum background because then you're comparing three versus five‑drug regimens.  An that's probably too convoluted for somebody who is earlier in the course of failure.  So I think this may be a consensus emerging that's kind of nice to hear.
		ACTING CHAIRMAN GULICK:  Dr. Mathews?
		DR. MATHEWS:  You know, the devil is in the details, particularly I think up front, where we are trying to define inclusion criteria and what exactly is meant by optimized background regimen.
		The notion of a sensitivity score based on the resistance collaborative group I think is very attractive, but obviously you have to assume that the patients that are being screened for the trial are on some therapy that makes the resistance tests at the time they are screened interpretable.
		You can imagine a number of situations where people might have motivations to go off therapy so that they would qualify for a trial.
		So I don't know exactly how that is dealt with.  But, in addition to having a cutoff score of two or whatever, one could further stratify the randomization based on some measure of sensitivity where there is clear uncertainty on what the potential to respond is and the basis of background resistance.
		That should include, actually, whatever is known about the experimental agents because many of these drugs are coming into trial where the resistance profile is not fully characterized, particularly thresholds for sensitivity.
		ACTING CHAIRMAN GULICK:  Mr. Levin?
		MR. LEVIN:  I want to modify what I said this morning.  So I'm glad we had all of the arguments and everything because I have had a chance to think about it and talk to some people.  I do have some concerns, and I want to express them.
		I am concerned about drug interactions, and I am concerned about making sure that every regimen in a salvage study is somewhat equally effective in being able to suppress virus, no matter which arm it is.
		Having said that, ‑‑ and there may be some other concerns ‑‑ I don't want to rule out modified factorials.  So I want to change my opinion on that and go on the record for that.
		It does appear as though next year there will be at least four or five or maybe more new drugs.  And so if you can find combinations that are somewhat equally effective, I think that would be important.
		I don't think I have a problem with 16 weeks.  I think that that's okay as long as there is an adequate antiviral activity, as said before, of at least a half a log.
		One thing I want to add here, though, is that we have not really spent a lot of time, adequate attention to identifying toxicities and side effects, including hepatotoxicity.
		I would like to suggest that all of the companies and the FDA get together and find some way to maybe create a database for all salvage studies where we could collect toxicities, hepatotoxicities, and side effects and maybe come up with some information; in particular, lipodystrophy but also, in particular, what gets very little attention at this point is hepatotoxicity.  We really need some data on people with hepatitis and HIV medications and what is really going on.
		ACTING CHAIRMAN GULICK:  Thanks for your comments.  I would like to refocus us on the study design.  Let's people quickly move from the add‑on to the two‑part hybrid study.  Yes, Dr. Eron?
		DR. ERON:  The issue of bias in the use of a placebo in this particular study and just to get, in particular, the add‑on study, to get people's comments because if there is an early pop‑off and the patient knows that they're sensitive to two drugs, ‑‑ let's say that is the cutoff ‑‑ there may be somewhat of a disincentive if it's a no treatment control, as opposed to a placebo control.  I wonder if, Victor, other people have thoughts about that.
		ACTING CHAIRMAN GULICK:  So you're advocating for blinding, it sounds like, to deal with ‑‑
		DR. ERON:  Yes.  I mean, it would make sense to me.
		ACTING CHAIRMAN GULICK:  ‑‑ the bias in that situation.
		DR. HAMMERSTROM:  There is a way or something we do in place of blinding.  It's not as good as blinding, but there are instances where, like an injectable drug, it's basically unethical to inject somebody with saline solution as a placebo.  Well, it's infeasible anyway for something like that.
		What we want to see or at least what has been proposed now is we want very rigorous criteria that say this is what you should look like at week eight to be classified as a non‑responder and to get into the expanded access.
		I was given an example.  It doesn't have to be the right one.  If you have dropped half a log from baseline, if you've done that, you're a responder.  If you haven't done that, you're a non‑responder and you're allowed to go to expanded access.
		If you have dropped half a log or a little bit more than half a log but you want to go to the expanded access anyway, then that kind of thing raises a need for sensitivity analyses.
		That's a sort of a biased differential dropout.  We would not want to see that too much.  We would basically like at the end those kinds of switches shouldn't be occurring frequently enough to be affecting the conclusion.  So, at least up to now, that is the way we compensate for absence of blinding.
		You have a very rigorously defined exit criterion.  And the people who exit, even though they haven't met that criterion, have to be subject to some kind of sensitivity analysis to make sure that their switching isn't the reason you are finally ducting drug A is effective.
		DR. ERON:  Sure.  And the concern that I have there, though, is that there might be differential adherence.  So the people who are on the no treatment arm would maybe not be as adherent to their therapies such that they legitimately make that cutoff.
		I suppose one way around that would be whether potentially at drug levels ‑‑
		DR. HAMMERSTROM:  Yes.  That actually came up on an IND we did.  Did we come up with a solution for that?  The incentive for someone to cheat when they're ‑‑
		DR. JOLSON:  It's a concern.  It's part of the concern of doing an open label study.
		ACTING CHAIRMAN GULICK:  Okay.  Any last thoughts on add‑on before we move?  Ms. Dee?
		MS. DEE:  You know, this would be maybe the most attractive to industry, but it's probably the least attractive to the patient population.  So hopefully somewhere we can both give a little because if you're talking about the patient that the agency described this morning, maybe they won't get in your studies because they do have some other options and they do have some time before they really are "desperate," in quotes.  So maybe they won't get on your study and you won't be able to accrue it.
		ACTING CHAIRMAN GULICK:  Just to be specific ‑‑
		MS. DEE:  The add‑on, in other words, with the placebo, the add‑on plus A versus placebo.
		ACTING CHAIRMAN GULICK:  Would not be encouraging to the patient ‑‑
		MS. DEE:  Right.
		ACTING CHAIRMAN GULICK:  ‑‑ because they may randomize to a placebo?
		MS. DEE:  Right, right.
		ACTING CHAIRMAN GULICK:  Dr. Cunningham?
		DR. CUNNINGHAM:  Just briefly.  I had made a couple of comments about the add‑ons.  And then when Dr. Saag commented, he said he felt that there was a consensus about these being appropriate.
		I guess I didn't want to imply that I thought that that's ‑‑ I was trying to point out some of the pros of the add‑ons.  I think the down side of the add‑ons is that you get less information about drug interactions and you overall get less information than the other types of trial designs.
		So I am not sure that I would say that I agree that there is a consensus that that is what we should do.  I think that in certain circumstances, that is the appropriate trial design but not always.
		ACTING CHAIRMAN GULICK:  Okay.  Yes, Dr. Blackwelder?
		DR. BLACKWELDER:  Another comment on the add‑on.  It sounded like there was a suggestion a few minutes ago that you could continue to follow patients beyond, say, eight weeks if eight weeks was the primary time of evaluating and just keep the placebo group, whoever was left.
		That is kind of problematic because you don't have the randomized study anymore.  You just have a subset of them.
		ACTING CHAIRMAN GULICK:  All right.  Dr. DeGruttola?
		DR. DeGRUTTOLA:  I don't quite understand that because I would think if you define a failure endpoint and you say that as soon as people reach that failure they can get access to the new drug or have some other strategy, then you still have a full randomized comparison between the two groups.
		What you are doing is following patients until they reach failure.  Then they are contributing their endpoint to the study.  They are contributing their endpoint to the randomized comparison.  Then after they reach failure, they can go on to another treatment.  So I believe that this approach can be a full randomized comparison and not require subset analysis.
		I do want to agree with Dr. Cunningham's point that while this may be the best design in some settings, in other settings where you are interested in looking at two new agents, the ability to study them together and allow you to look at interactions, both in terms of toxicity and efficacy I think is important to consider.
		Dr. Rooney mentioned that interactions can sometimes complicate interpretation, but I think if you are concerned about interactions, that is all the more reason to do a study up front, like a factorial or the so‑called modified factorial, that allows you to evaluate those interactions in a structured way if you are talking about two drugs are ultimately going to be used together.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi, the last word here.
		DR. DeMASI:  Yes.  I just wanted to clarify the point about the eight‑week potential switch and then looking at the eight‑week and then subsequent 16‑week, statistical analysis, to compare treatment groups.
		I think that, echoing Dr. DeGruttola's comments that we're looking at an endpoint of cumulative virologic failures up through week 16.  And a virologic failure that would occur prior to that which would allow patients to go on to a new drug would contribute to that week 16 analysis.
		And for a more conventional or a change from baseline type of a metric, if a patient switched at week eight, you could carry that observation forward in terms of the RNA result at week eight to week 16 when you did the week 16 interim analysis.
		ACTING CHAIRMAN GULICK:  Thanks.
		DR. BLACKWELDER:  You might want to do a comparison just of that subgroup with ‑‑
		ACTING CHAIRMAN GULICK:  Okay.  We're moving on to the two‑part hybrid, which many moved on to right away.  Dr. Schapiro?
		DR. SCHAPIRO:  So regarding the two‑part hybrid, by the way, Trip, I think regarding terminology, if "salvage" is based, I think "two‑part hybrid" is a tough deal.  I heard you snickering and saying something about me being a two‑part hybrid when I got up.  I think we should find a better name for that.
		To summarize my comments on it, I think we did hear from some of the speakers.  I would say we are able to get a lot of information from this type of study.
		I think we do have two phases.  Not to go over endlessly, there are differences.  We are looking not only at the ability to get patients undetectable.  We are looking at the ability to get them down.  I think Mike Saag and Steve Deeks made these points at sometimes.  0.7 log can be great.  So we want to differentiate between the two of them.
		I do think that initial number of weeks that we look at the drug itself does give us the opportunity to see:  Is it potent, to what degree it's potent?  And I think to some degree, we get some toxicity adherence also in that short phase.  If a drug really is hard to take, we can sometimes tease that out in that short period of time.
		And then the additional phase, which I'm just calling month or maybe a year here, we get the additional information about going undetectable.  And we get some of the more CD4 adherence.
		I think this is different for different drugs.  I don't think you can give it as a number of weeks necessarily.  I think it depends which drugs you're studying.
		I think the key factor which was brought up earlier is that you don't want resistance to be generated in that time.  I think for an NNRTI, this might not be appropriate.  We have data that one or two doses can be enough.
		So we can't make sweeping suggestions regarding this.  I think the two‑part hybrid, for lack of another word for it, would not be appropriate for an NNRTI.  The way we see them today, it probably would be appropriate for PIs and NRTIs.  And we maybe could slide it between two or three weeks depending on what is being looked at.
		A concept I think that we heard from Professor Vittecoq earlier which is being looked at is the degree of the slope.  We don't have a lot of information on this, and we have to remember this will not predict necessarily long‑term failure.
		I think that John Mellors presented some data that long‑term success is not necessarily dependent on just how potent you want.  We know that there are other factors.  If we want to see how potent the drug will be, the slope may be beneficial.
		There is a study being done now at Stanford and in Holland with Anders DeLoupa being the PI on this where you take frequent measurements over a short period of time and possibly will be able to look at the slope.  It may be that this would suggest a more potent drug than this than this.
		I don't know if ultimately this will work out, but I think if we are going to be doing these type, I would encourage people to try to see if this works or not.
		It may be that there is too much noise.  It may be that it doesn't work out.  But based on the pathophysiology of the disease and the impact that we have seen from some of the dynamic studies, there may be something here.  And that might be something which we can use as another measure.  Again, how potent is the drug?
		Now, I think something we should also use that initial phase for is probably here.  In this phase, we would want to try to delineate again with a specific resistance profile how much kick you get from that drug.
		And I think that by taking a resistance profile at baseline, a genotypic and/or a phenotypic study, and then at the end of this initial stage looking at the drug level and also looking at the virologic impact, be it the reduction, the change, the slope, whatever we have, we can then try to tie in this correlation.
		We will want a drug level which will tell us the exposure.  And then we will want to put together these three parameters and come up with a statement which will tell us that if you have this genotype or phenotype and you obtain this drug level, then this will be your viral load response.  We can then take that and use it in other patients.
		I think, as we discussed earlier, this is something that we can take home and we can use in different patient populations.  When we see that phenotype or that genotype, we will ‑‑ and it doesn't have to be the exact same patient population.  Anyone who has that, we now have data that with this dosage, you should get that response.
		We don't necessarily have to repeat this study to all of the different populations because we have correlated a specific baseline resistance with a virological response.
		True, it's short‑term, but maybe if we look at it in a number of ways, it will be quite robust.  And, again, if we add in here the drug level, we will be able to determine for that dose we can try to quantify how much effect we could get.
		And I think Dr. Jolson made a good point earlier that we have to look at patients that are a little bit less advanced.
		I think it's an excellent point.  Thinking about it, I think the real difference this morning in the discussion, the difference between the deep salvage and I think the very appropriate group determined by the FDA is class resistance versus drug resistance.
		I think deep salvage means patients who have class resistance to all three; whereas, the patients you guys are defining I think in a very nice way are patients who may have resistance to drugs in the three classes but not necessarily class resistance.
		Therefore, they may be appropriate to different degrees to look at this.  We may be able to take this data, then, and look at it, even in the deep salvage.
		ACTING CHAIRMAN GULICK:  Thanks.
		DR. SCHAPIRO:  Thank you.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi, you have another design that's also the two‑phased, can we call it?  How is that?  Bridged phase?
		DR. DeMASI:  Thank you.
		I just wanted to take this opportunity to present this additional design here, which I think summarizes or encompasses many of the points that have been addressed today and discussed this morning and this afternoon.
		Essentially what I have done is I have focused this design in terms of a very specific phase of drug development, namely a Phase II study.  It's a randomized control trial looking at two doses of your drug compared to a placebo or no treatment background.
		Essentially what I have here, I have called it the bridged phased I/III randomized control trial because I do think it contains characteristics of both Phase I, obviously the Phase II, and a Phase III study.
		Essentially the basic study design is that patients are randomized to one of the two doses of the drug plus the optimized background regimen with either a placebo or no treatment.  So everyone is able to get the optimized background regimen with additional investigational agents.
		I think the importance of this study is because in today's discussion, I think there may be some under‑emphasis of the importance of finding a correct dose for your drug to maybe take into a factorial design or a strategy trial or a pivotal Phase III study.  And in doing this type of a design, where you can actually determine the dose, you can bridge some of the information you learn about your drug in Phase I to Phase III.
		So more specifically, I have proposed here, similar to what has been proposed as a two‑part study with a randomized comparison of viral load response in the first one or two weeks.  And the study is actually powered to detect differences in viral load.  That estimate of the number of patients actually comes from your broad‑based, dose‑ranging study in Phase I.
		The second phase is ‑‑ and I have specifically noted activity here in terms of the activity phase.  The second phase is more of a comparative/efficacy phase of the study in which you maintain the randomized feature of the trial through some period; for example, 12, 16, 20 weeks.
		And here in this example, I have noted 16 weeks.  At that point, you could actually based on an interim analysis of the data roll patients into the optimum dose regimen, either A or B, and follow these patients to generate long‑term safety data.  In terms of building your safety database, that would contribute to an NDA submission.
		I think a unique feature of this design because you have patients who are on the new drug plus additional investigational agents is that you can build into the fourth phase a randomized, potentially randomized, withdrawal study in which you randomize patients to either continue or withdraw from the investigational agent and you can look at the delta in terms of an RNA rebound over one or two weeks from the RNA value at the time that he discontinued the investigational agent.
		Just to complete the discussion, I want to summarize some of the points here.  Obviously, also mentioned earlier, in terms of the features for the Phase I, for example, exploratory interim analyses of the two‑week data could be conducted to look at correlation of genotype and phenotype by baseline with initial virologic response and also the PK/PD modeling, as was just mentioned.
		I think in terms of some of the other features, the switch option could be built into the study here, for example.  It's at eight weeks.  So this would allow patients to switch either to the investigational agent or potentially an optimum or good dose of the investigational agent.
		Additionally, I just want to conclude by saying based on this, I think, study, which could be done in a pretty fairly broad population, that additional exploratory and subset analyses could be used to refine the population that could be studied in a more definitive and larger Phase III study, although I believe that if you can demonstrate differences in terms of safety and activity during this phase of the study, the randomized phase, through an intermediate time point, that this could be suitable for submission for a supportive study or a pivotal study.
		ACTING CHAIRMAN GULICK:  Comments?  Dr. Fletcher?
		DR. FLETCHER:  I just want to say that I would be a strong proponent of this design.  I think there are numerous attractive features to it.  In particular, the ability to study early on, the pharmacokinetic characteristics in your Phase I move into two doses so that you can really, then, understand what is going on.
		Certainly a variant, instead of two doses, could also be two concentrations.  So the idea of a concentration‑controlled study has come up.  So, instead of randomizing to two doses, you could randomize to two levels of exposure as well and then from that work into your Phase III, where now that you have an understanding of your concentration‑response relationship, you could then do a refined dose and probably simplify it into Phase III.
		I think in my mind, a particular attractive feature of this is that if we continue a current approach in treatment‑experienced patients of trying to determine virologic characteristics, whether they be genotype or phenotype, but still continue to apply the same dosing strategies that we use in naive patients, we are doomed to failure.
		If potency of a drug is some function of concentration to susceptibility, that ratio in a treatment‑experienced patient is not going to be the same as in a treatment‑naive patient.  And so there has to be a method by which you can use that ratio or some other approximation of potency and learn about what it is in naive and begin to apply that into treatment‑experienced patients.
		One difficulty I have to mention in all of these, which has been brought up numerous times under the heading of drug‑drug interactions, is we can't underestimate what a serious challenge that is going to be to have knowledge of drug‑drug interactions before you launch into these types of studies.
		If you think about, say, an optimized background, maybe it is not even the same among all patients.  So maybe we allow six drugs to be used in an optimized background and then you wanted to add on two more drugs.
		You now have eight drugs that can be taken five at a time, I think, if my math is right.  And the amount of drug‑drug interaction knowledge that you are going to have to have becomes enormous.
		Now, this design, the bridge one, does help in that because in that if you want that two‑week lead‑in phase, if you're committed to it, you could do an awful lot of learning about what drug‑drug interactions are there and use that in a very fast approach to modify anything that is surprising or way out of the realm of what you would want.
		ACTING CHAIRMAN GULICK:  Dr. Mellors?
		DR. MELLORS:  Yes.  Just a couple of points.  I like the two‑week lead‑in phase because it's, again, clean and you can do PK/PD modeling, but there is risk.  Rather than say a given class should or should not be applied to this design, like NNRTI might not be good or fusion might or might not or PI, it really depends on the characteristic of the drug in vitro and what the genetic and pharmacologic benefit is to resistance.
		So you can make some estimations that a drug would or would not be a good candidate for this.  So that is one caution.  The other caution is ‑‑ and, Ralph, it is very ambitious, and it is really kind of pushing the envelope, but that is asking an awful lot of a trial to accomplish all three phases.
		I would be happy if I got two phases completed.  The caution I have is that you want to make absolutely sure after the two‑week mono therapy lead‑in that you haven't done any damage to the response to the drug, namely you want to make sure that you haven't selected resistance and diminished activity.
		So I am in favor of the design, not necessarily for registrational purposes because it is asking an awful lot of a single trial to go from Phase I dose‑ranging mono therapy through Phase III registration because it may be successful if everything goes right, but chances are you will learn some information in the first and second phase that modifies the Phase III design.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi, a response?
		DR. DeMASI:  Just to address a couple of the points, I think in terms of the suitability of the study design, I agree that it does depend on the particular drug that could be used in this type of study.
		In the two‑week lead‑in phase compare an activity was presented as an example.  And that could vary because of the resistance profiles of a particular drug to seven to ten days perhaps.  And in terms of the other coin, I agree that in terms of the logistics of the study, it would be a difficult study to conduct, but I do think it is feasible because if you look at the study design, the additional piece that you're carrying over that's there that's not in the two‑part hybrid is the additional randomized phase beyond the two‑week study period.
		So I do think it is feasible to continue the study beyond two weeks and collect and look at the comparative contribution of the study drug in two different doses versus a background and no placebo.
		ACTING CHAIRMAN GULICK:  I'll take two more comments.  Dr. Eron and then Dr. Falloon.
		DR. ERON:  In the FDA design that was put up, there is no control arm.  Is that correct?  Is that ‑‑
		DR. HAMMERSTROM:  Can we put up the slide that had our three trials up on it again?
		DR. ERON:  The problem with that is I don't understand how you have any certainty that the prolonged effect is not just due to the optimized background.  In fact, Trimeris has already done this study.
		DR. HAMMERSTROM:  This is exactly.  One of the questions that I have with this design is that if the statistical analysis is straightforward, you've got three comparative arms.  It's easy enough to do statistically valid comparisons.
		What is going to happen between day 10 and week 24 is that at the end of week 24, you're going to have one sample.  And you're going to look at that.  You're going to look at change from baseline or change from day ten level and test:  Is that change from baseline less than zero?
		So what this amounts to, if you're going to conclude from that that this is evidence of durability, the effect, it amounts to a historic control data in which the historic control is, in fact, everybody's subjective impression of their case series that had they stayed, we know, everybody knows, without looking at any more data that if you stayed on a failing regimen, what would happen to you after 24 weeks would be that you would go up.  If you get a statistically significant decrease, then that's evidence of effect.
		I would like to know:  Is that convincing to other people?  What else would you need to this trial for that test to be convincing because if anyone does this at the final review, that's the question I'm going to have to or we're going to have to answer?
		DR. JOLSON:  The study that I'm thinking about is the T‑20 study, where they gave exactly ‑‑ you know, it was 28 days of T‑20.  And there was a hiatus, but then people got optimized therapy and T‑20 with no control.
		Certainly every time I have presented that study people have said, "You can't make any conclusions about the impact of T‑20 on that outcome" because I don't think there's any way to know whether the optimized background is what's driving the antiviral response.  And it ends up being, "Well, I know that these patients in my clinic would have never done this well."
		DR. MURRAY:  First of all, I wouldn't envision this for a new class of agent.  I would envision it where because the second part, the hybrid part of it, as you're doing a prospective observation or cohort or are you actually using the heterogeneity of the population in terms of their viral isolate sensitivity to make a conclusion about what was happening at the end, kind of similar to the 957 Kaletra study?
		So it's randomized at the beginning, and you know that at the beginning if the new drug was contributing because if it wasn't contributing anything, you wouldn't see any response at all probably during the first ten days to two weeks.
		You know, the difference between that and maybe the T‑20 study you're talking about is, too, that you're also seeing the initial contribution of optimized background.  So it would be unlikely that a drug which was contributing, let's say, a log in the first two weeks was having absolutely no effect at the end.  Of course, that's a bit of assumption.
		But then I guess I would envision them tightening up the study at the end of 24 weeks with either to do a dose‑response or you could do some ‑‑ at that point it becomes not uncontrolled but not randomized, an observational cohort, where you're using your baseline sensitivity.
		I would agree this is a controversial design.  We have not used it for registration in the past.  We are trying to think of if you couldn't have corroboration, if you didn't feel comfortable about an add‑on ‑‑ and I might add on an add‑on, you do have to worry about using up your optimized backgrounds.
		I mean, how many chances do you get with optimized backgrounds?  So if you failed it, at the time you are ready to have your escape option, then what's your optimized background?
		Anyway, so we're coming with maybe what would be a possible third option?  And then we've gotten these.  I think this is a bit similar, maybe to the EMEA proposal, and then we've seen some other proposals.
		Then we got some I think pretty good information for lopinavir with a design somewhat similar to this, although they didn't have the initial mono therapy period in that trial, but they did in other trials.
		So I realize it is controversial, but if it isn't, if that last part, the second phase of it, does not appear to be strong enough, we would like to hear that.
		ACTING CHAIRMAN GULICK:  Dr. Falloon?
		DR. FALLOON:  In going back to the question of what to do in the early part, there's a piece that all of these trials should define, that is, in essence, a mono therapy piece.  An important piece of information for treating people with the package insert would be:  What can predict who would respond?  That's very hard to do when you have multiple complications.  That makes some lead‑in period attractive.
		When we thought about how to look at slopes and how to look at responses over a short‑term period, the problem is complicated by where people start because they don't start ‑‑ when they start at drug‑naive, they start at some sort of baseline set point.
		When they're starting on therapy, they're starting generally not at some baseline because we're not here.  You're not talking about people who have no drug options.  So they're partially suppressed.
		So what you do with their old regimen and what they have been on at the time you do your resistance testing has a major impact on what happens.  And it's extremely confusing because you get shift, and I don't know how fast shift reverts.
		So if you want to talk about over two weeks, you take somebody that you're going to look at a new NNRTI ‑‑ I don't even want to get into whether two weeks is too long for that, but they have had shift.  They no longer have the 103.
		Is that the question that you want to ask in that population?  We have some plans for these trials, and those are some of the questions that we look at.
		To my mind, they are not answered.  And so a very short lead‑in, while it's extremely appealing, is very difficult to interpret.
		ACTING CHAIRMAN GULICK:  Ms. Delph, the last word.  Then we're going to move on.
		DR. DELPH:  I just wanted to comment on the proposal, what I understand to be Dr. DeMasi's proposal.  I couldn't see it very well from here.  So I may have misinterpreted it.  But I have a lot of concerns about the bridged Phase I/III trial of moving from a situation where you are still trying to do dose finding and come up with an appropriate dose into treating a salvage population.
		I think before we embark on salvage trials, we need to have a good idea of what dose of drug is likely to be effective.  I think we also need to have adequate interaction studies done, drug‑drug interactions and not just two‑way interactions but three‑way and four‑way if necessary drug interactions, so that we have a reasonable idea beforehand of what drug level, what drug dosage, is likely to be effective in these patients.  They have a lot to lose, and they have a narrow therapeutic window.  They are very susceptible to toxicity, and they have highly resistant virus.
		Having said that, a lot of the PK studies and dose‑finding studies are done in very small populations and populations that I think that are unlikely to be typical of salvage patients, who are particularly susceptible to toxicities and who have a number of comorbidities as well often.
		So I do think that these studies should also include some form of drug monitoring.  Now, I don't want to open Pandora's box of whether we're doing Cmax or Cmin or AUC or whatever.  I think we may be able to discuss that sometime later, but I think we need to do some sort of monitoring of drug levels in these patients because we really at the end of the day cannot predict what sorts of drug levels we're going to get with the kind of regimens that we are going to be giving these patients.
		I certainly share Dr. DeMasi's desire to get drugs to patients quickly, but we do want to do that in as safe a way as possible.  I think that the patients who often most need these drugs, who are in deep salvage, I agree totally with Dr. Mathews that we should not be requiring these patients to get into trials to have access to them.
		I think that we need to ensure that expanded access programs are opened up to patients who have no other options available at about a time that we're going into these larger Phase II/III studies.  And that I think is what we need to ensure.
		ACTING CHAIRMAN GULICK:  Thanks.
		Let's go on to consider the modified ‑‑
		DR. WONG:  Could I just make a comment?  I haven't said anything.
		ACTING CHAIRMAN GULICK:  Okay.  Dr. Wong, who hasn't said anything?
		DR. WONG:  I haven't had a chance to answer the question at all.  So I think that one of the things that comes across to me from the whole day's discussion is that in different groups of patients with highly experienced patients with HIV, the question is different.
		And I think that each of these study designs and others that have been proposed really are capable of addressing different kinds of questions.  In those populations, the right design to pick is the one that addresses the clinically relevant question.
		I would just urge that the agency ‑‑ and I think they do this now, but I think I would like to hear them kind of reassert that they would consider approving a drug for a narrow indication if the utility of that drug for that narrow indication was established and not necessarily demand that the studies address all or even multiple possible utilities so that whether or not ‑‑ I mean, clearly all of these designs have advantages and disadvantages, but I think each of them is clearly capable of addressing a clinically relevant question in some population.  And I would suggest that that be the key consideration.
		ACTING CHAIRMAN GULICK:  Okay.  Let's move to the modified factorial design, which is the first one up there.  So we're talking about new therapies A, B, and C with optimized background A plus B versus A plus C versus B plus C versus all three together.  Victor, can you start us off?
		DR. DeGRUTTOLA:  Well, I think that one of the issues here is that:  If you have multiple drugs that you're interested in studying, can you look at combinations of those drugs right from the start?
		The advantage of being able to do that is to be able to investigate interactions between drugs and also perhaps to increase your efficiency in answering multiple questions.
		This so‑called modified factorial is actually not in a factorial layout, but as I understand it, what it allows you to do is use half of your patients who are enrolled to answer each comparison of A versus B, A versus C, or B versus C.  And that provides some of the advantages of a full factorial but not all of the advantages in that you can't study all of the interactions and also you don't have the full efficiency.
		I would say that the kind of design that you would want to use in this context would depend on what treatment options were acceptable to patients.
		Let's say you had two new drugs, just A and B.  If the layout of a randomization of A to placebo and B to placebo led to treatments that were acceptable, clinically acceptable, to patients, that would have an obvious advantage, full power to look at each one of the comparisons, and reasonable power to look at interactions, or at least the best power you could get to look at interactions.  But obviously that's only appropriate in settings where it leads to treatments that are acceptable to patients and physicians.
		In cases where it would not lead to acceptable treatments because giving patients only one new drug would be inappropriate for reasons that John Mellors mentioned, then I think that this design does offer some advantages, ability to look at some interactions in the start and some improvement in efficiency in terms of doing the comparisons of A versus B, A versus C, and so on, even though not the full efficiency of a factorial design.
		So I think it would be very specific to the setting and the particular treatments whether they could lead to acceptable regimens for patients and physicians.
		ACTING CHAIRMAN GULICK:  Dr. Saag?
		DR. SAAG:  This is what I was saying earlier.  I think in keeping with what Victor just said, that it really depends on the population.  Keeping with the definition that the group wanted to use, two HAART regimen is an all three class exposure at a minimum.  Then you can go to a resistance test.
		This doesn't all have to be one study, but it could be where you take patients who meet that criteria, you do resistance analysis.  It could be with or without PK, et cetera.  You can make it fancy if you want.  But if there are three reasonable options or more, then you do the A, B, C versus placebo.
		This is the clean study we have been talking about.  This is where drug companies can collaborate and you can have three different companies with each of their agents, A, B, and C, and get something done that has a lot of meaning.
		In that same population, if you have fewer than three options, then the optimized background therapy is not satisfactory.  Just add a single agent.  That's what we have been talking about.  And that's where you go to the two drugs or maybe even three together.
		And so the point is that, no matter what, the patients are getting three or four drugs that should work based on at least reasonable activity.  And this is something you could use, I would think, as a registrational study.
		I mean, the big picture, throwing it all together in one trial, feasible maybe.  Maybe you want to split.  That's with the blue line.  Maybe you have one study like this and one like that, but the attractive thing from a clinical perspective is that when I'm recruiting for studies, more times than not it's really getting frustrating as an investigator because we have a lot of studies on the board.
		If somebody comes in and with the new requirements, if there are no exemptions for anything, a lot of patients we sell the study concept to.  And we find there is one part that kicks them out.
		So the notion of having a large study that can attract a lot of patients, you don't have to worry about that.  You let the entry criteria define them into their arms, rather than out of the study.  That would be attractive as an investigator.
		The other part because we're talking about industry collaboration, ‑‑ and this is maybe where the ICC comes into play ‑‑ another limitation we have as in aside that will help speed this study to completion is that some of our folks, believe it or not, still can't get access to optimized background therapy, at least easily.
		And so while it is difficult to have a whole pharmacy's worth of drugs for the study to complete, if we could find a way to provide the entire regimen, rather than just the investigational part, that would speed accrual and get the answers faster in certain populations of patients.
		ACTING CHAIRMAN GULICK:  Other points on factorial?  Mr. Hogan?
		MR. HOGAN:  With regards to what Victor was saying about it not being a true factorial, that's true.  What we are calling it in the Coalition for Salvage Therapy is a minimum number of factors factorial because we basically have just taken out all of the smaller cells.
		It strikes me listening to this whole discussion that the biggest challenge all of us face in the room, collectively and individually, is there are gray areas in two specific places.  One is the tension between public health and drug approval.  And the other tension is between drug access and research.
		Unfortunately, I keep hearing the conversation flip back and forth where people are talking about what is the best care for their patient, as opposed to what is the best research.
		I am certainly not advocating Dr. Mengele's solutions where we do the best research at the cost of care to patients.  I think it is very important to separate out those issues.
		In particular, one place where I think there was a confusion with the other respect is when people mention if there is interaction, a factorial study is not viable.
		I believe it was either Victor or Courtney who pointed out:  Well, yes, that's true if you want a scientifically rigorous examination of the components, but if you want to know which drug strategy is worthwhile, then it doesn't really matter.  Whichever is the winner is the winner.  So there is that public health/regulatory tension.
		So I guess, really, what I am saying is I think it is very important that we pay attention as we have discussion to discriminating on both of those fronts because I do think that all of these issues are getting mixed together.
		I know when I discuss these issues, I mix them together all the time:  patient care, research.  Public health/regulatory is a very hard discussion to have.
		DR. SCHAPIRO:  But it is mixed together, but that is exactly the issue.  I think what Mike is saying is we are investigators and we are doctors and there is a true tension there.  If there wasn't, I mean that that's a real issue.  It's not separated because it is not separable.
		MR. HOGAN:  But the discussion needs to acknowledge that.
		DR. SCHAPIRO:  I think we all accept that that if we could ‑‑ leaving Mengele out of this, I think we all realize that there is a tension in each one of us to do research for the benefit of all but not do harm to our patient.  And that is why this continually gets mixed up because it actually is.  You have one patient to make a decision on, and each patient is one patient.
		ACTING CHAIRMAN GULICK:  Dr. Mellors, then Dr. DeGruttola.
		DR. MELLORS:  I don't spend my day contemplating clinical trial design, but we have taken an eight‑cell factorial and conveniently removed what appear to be unattractive arms.
		I am not convinced in looking at this design whether we have the same ability to discern individual drugs' contribution to toxicity when we don't have an arm without drugs in it.  Still, I would like some clarification from the people who do spend their day thinking about these issues whether we lose anything by lopping off half of the cells.
		ACTING CHAIRMAN GULICK:  Dr. DeGruttola?
		DR. DeGRUTTOLA:  Yes.  You clearly do lose something by lopping off the cells.  It is exactly the clarity of being able to examine all of the interactions.
		The simple basic factorial design of A versus placebo, B versus placebo if it is acceptable to patient is the best way I think to investigate interactions, both in terms of toxicity and efficacy.  You can examine all of the effects, the main effects as well as the interaction.
		In this design, which is four of the eight cells from a full factorial design ‑‑ it's not a fractional factorial.  There is a way of taking four of the eight cells in something that is called a fractional factorial that would maintain many of the benefits of the full factorial.
		This is not a fractional factorial, but it still does allow you to investigate some interactions.  So it still may be useful as a structure design, even though it is not optimal.  It is not optimal in terms of power, and it is not optimal in terms of studying interactions.
		But, for example, if that design were AB; AC; BC; and A, B, and C, supposing that you saw toxicity whenever A was combined with B, so you saw toxicity in the AB and the A, B, and C but you didn't see toxicity in the AC or the BC arm, then you might be able to make some investigation of the fact that your toxicities don't seem to be associated just with A, just with B because you do have those two arms alone but only in arms that have A and B occurring together.
		If, on the other hand, you saw the toxicity whenever you had B, whether or not A was there, then that might give you more reason to believe that it was B that was contributing to that effect.  But the fact that you don't have the full factorial, just as John Mellors states, does mean that you don't have the full power to investigate all of the interactions.
		There is certainly a trade‑off.  The only reason for doing this design, less desirable statistically, is if it were the only one that came up with acceptable treatment options, you could still learn a lot from it.
		MR. HOGAN:  Just one point of clarification.  Every drug is absent in a least one arm.
		DR. DeGRUTTOLA:  Well, that's different from the design.  I was referring to this design here, which is the AB; AC; BC; or A, B, C.  So I think you may be talking about a different ‑‑
		MR. HOGAN:  AB; BC; A, B, C; correct?
		DR. DeGRUTTOLA:  And AC.
		MR. HOGAN:  Right.  So every drug is absent from at least one arm.
		DR. DeGRUTTOLA:  What is absent from the A, B, C arm?
		MR. HOGAN:  No, no.  I am saying there is at least one arm from which every drug is absent.
		DR. DeGRUTTOLA:  Yes.  That's right.  That's right.
		MR. HOGAN:  So that, admittedly, you're not in a great power situation, but you always have a comparator to an arm that does not have that drug present.
		DR. MELLORS:  But if there are disease‑related symptoms or signs that have nothing to do with the drug, you won't be able to discriminate that from drug toxicity.
		ACTING CHAIRMAN GULICK:  Okay.  I think the points have been made.  I think I would like to stop the discussion at this point.  With apologies to a couple of other people who wanted to present other designs, I think we need to move on.
		Just to summarize what we have said, as a group, we struggled once again with the population that we are considering, what constitutes experience, what to do about people with some options versus no options.
		A very important point about viral and CD4 setpoints and how that is influenced by people taking their regimens going into one of our salvage studies.
		In terms of optimizing background, some important practical points about access to therapies, how resistance tests are done, access to resistance tests, how they're interpreted, and then the important suggestion that possibly stratifying by options that are identified by resistance testing might be an appropriate thing to do at baseline.
		Also, we heard a plea again that before launching into any of these studies, that drug‑drug interactions have to be known, particularly with the optimized background design given that multiple drugs may be used.
		In terms of the simple add‑on design, people were impressed that that's the simple, cleanest way to demonstrate efficacy and perhaps would be most attractive to industry.  Also, it was noted that drug interactions would be relatively straightforward to define.
		In terms of the negatives, essentially this is a design of functional mono therapy, which is of obvious concern, may predispose to early failure.  And having a placebo control may be a relative negative for patient participation.
		The second design we thought about was the two‑part, two‑phased, bridged, dimorphic, two‑bit design.
		(Laughter.)
		ACTING CHAIRMAN GULICK:  That's the compromised title.
		In terms of the pros, people once again felt that this was a design which could cleanly demonstrate efficacy over the short term, also had the opportunity to do dose ranging, and to identify important pharmacokinetic properties.  In addition, the second phase helps us to define longer‑term safety in a larger number of patients.
		In terms of negatives, the logistics was probably the top one that came up; also, the risk of resistance in the first phase of the study.  And it was recognized that that would differ depending on the specific agent that was used.
		In terms of the factorial design or the modified factorial design, the big plus here is using combinations of therapies which would be attractive to patients.  That interactions between these drugs could be defined earlier on was another big plus.
		In terms of the negatives, teasing out the specific activity of individual drugs and the specific safety issues of individual drugs, at least from a combination deign, might be challenging; finally, the very practical point about the number of drugs available for this kind of design.
		And then some other interesting suggestions that came up in the discussion, we had a discussion of blinding, whether that's appropriate or not.  The nice option of an early escape or an early switch for predefined failure would be an attractive strategy to use.  Concentration‑controlled was another novel approach that came up; and, finally, a second randomization in a two‑phased design, also a novel way of doing it.
		I think I would like us to take a ten‑minute break.  And we will reconvene for the afternoon.  Thanks.
		(Whereupon, the foregoing matter went off the record at 3:28 p.m. and went back on the record at 3:38 p.m.)
		ACTING CHAIRMAN GULICK:  In conferring with the agency, they have assured me that they know the answers to Questions 3 and 4.  And so we don't have to dwell on those.  So we will move into the second part of the discussion today, which is a discussion on endpoint issues.
		Our first speaker is someone whose career I have watched for a very long time.  It is actually me.
		Thank you, Mr. Chairman.
		(Laughter.)
	II.  ENDPOINT ISSUES
	RESPONSE RATES IN HEAVILY PRETREATED
	HIV INFECTED PATIENTS
		ACTING CHAIRMAN GULICK:  I would like to speak about the response rates in heavily pretreated patients.  This slide summarizes results from five clinical cohort studies, all of which were published in 1999.  They're from throughout the U.S. and western Europe, cohorts from Amsterdam, Cleveland, Johns Hopkins in Baltimore, the Swiss cohort study, and UCSF.
		What these cohorts have in common is that they are all taken from clinics, rather than clinical trials.  In most cases, these were nucleoside‑experienced patients who began their first so‑called HAART regimen, usually defined as adding a protease inhibitor.
		You can see that the numbers of patients involved are quite high.  I have simply summarized what the percent of patients who started this so‑called HAART regimen was above the limits of detection, which varied from cohort to cohort and the times in follow‑up.
		Just to make a long story short, what you see are clinical failure rates between 38 percent and as high as 63 percent in clinical cohorts over a period of one to 2 years on our best first line therapies.
		In looking at these five studies as examples of clinical cohort studies, there are predictors of virologic failure that jump out from study to study.  And many have identified the same predictors of virologic failure.
		Prior antiretroviral treatment, a small percentage, approximately 20 percent in each cohort, were antiretroviral‑naive.  That was an important predictor of virologic success.
		The viral load level looking at either a higher baseline or a higher peak level was often predictive.  Looking at the CD4 cell count, either a lower baseline or a lower nadir was predictive of virologic failure.
		From study to study, the specific antiretroviral regimen used was important.  In one study using a new nucleoside was a factor associated with a better response; in another, using a non‑nucleoside in a naive population.  And in a third study, the use of the protease inhibitor saquinavir was associated with a hither virologic failure rate.
		Finally, in two of the five studies, more missed clinic appointments as a surrogate for adherence was a predictor of virologic failure.
		Moving to the two prospective studies of genotypic resistance testing, we can add several more factors that predict virologic response.  From the GART study recently published in AIDS in 2000, we see that the number of active drugs picked in a salvage regimen as you move from four drugs is associated with a higher virologic response rate in terms of measuring change in HIV RNA over the course of the study.
		Secondarily, what is noted is that more patients who had genotypic testing were able to come with a regimen with three or four new drugs, as opposed to patients who did not have the benefit of genotypic testing.
		In a similar study, the VIRADAPT study, not only did they look at the use of genotypic resistance testing, but in a subset of patients, they also began to define drug concentration as an important predictor for virologic response.
		They took three specimens at random clinic visits and simply measured the concentration of protease inhibitor in those three visits.  They classified patients according to a dichotomous variable.  Either they had SOC suboptimal concentration of their protease inhibitor or they had an optimal concentration and then using a factorial design, really, patients, of course, who had been randomized either to genotypic testing or what was standard care at the time, which was no genotypic testing.
		Breaking the patients down into four groups and relating these two factors to the change in viral load, you can see that the group that does the best in terms of the biggest decrease in viral load level is the group with optimal concentrations of their protease inhibitor and genotypic testing.
		The group that does the second best is the group that simply had optimal concentrations of their protease inhibitor.  And then the two groups with suboptimal concentrations, either with or without genotypic testing, had relatively less virologic suppression.
		Now, there are limitations to looking at clinical cohort studies, particularly the ones that I have just considered.  One thing is an issue that we have been struggling with all morning.  That is heterogeneous patient populations.  Some patients are naive.  Some patients have taken nucleosides.  Other cohort studies combine many different types of patients.  And that makes it difficult to tease out the most important factors in predicting virologic response.
		The studies I have just shown you really reflect antiretroviral use in the years 1996 to 1998.  So there is really a time bias already because in the last two years, things have changed, even since the mid to late '90s.
		For instance, in that time, there were fewer antiretrovirals available.  More complex regimens were routinely used, perhaps involving 12 to 15 pills a day and using Q‑8 drugs routinely.  And then sequential mono therapy was quite a common way to use the drugs as they were approved one at a time.
		Another issue that I think came out with these initial studies was the fact that people were saying there are high virologic rates in the clinic.  And that often led people to say that treatment failure rates are quite high in the clinic.
		I think that simplifies what's really a relatively complicated concept.  That is, is virologic failure, which is what is measured in those cohort studies, really the same or related to immunologic failure or ultimately clinical failure?  And what do you really mean when you're saying "treatment failure," which one of the three of these?  And, really, that is what we are considering in this section of the panel discussion, the endpoint choice.
		Well, of course, over the last several years, we have come to conclude that virologic failure does not necessarily mean either immunologic or clinical failure.  This is work from Steve Deeks published in Journal of Infectious Disease.  Looking at a cohort of 380 patients in San Francisco, they were classified according to their virologic response rates into one of four groups on therapy.
		A responder group had consistent viral load levels less than 500.  A partial responder group had levels above 500 but greater than a one‑log decrease from baseline.
		A transient transponder had at least a one‑log decrease in viral load but then a rebound in viral load levels.  And, finally, a fourth group, non‑responders, essentially didn't meet any of those criteria, had no measurable change or no significant change in viral load levels.
		What Dr. Deeks did is to relate in each of the four groups the virologic response to the change in CD4 cell count over the course of two years and follow‑up.
		What you can see is that three of the groups, both the full responders, the partial responders, and even the transient responders, have significant increases in CD4 cell counts from 100 to 200 cells over baseline through the end of 2 years.  The only group that didn't really have a significant rise was the complete non‑responders.
		So, even in the presence of transient or partial virologic response, there was an immunologic response, at least in terms of CD4 cell count change, from baseline demonstrated out to two years and follow‑up.
		The French cohort looked at a very much larger group of patients, over 2,000 patients, and began to relate both virologic and immunologic responses to clinical responses.  So looking at all three endpoints, they classified the patients into one of four groups based on their response to their antiretroviral regimens at six months of time.
		I should say that, once again, as in Dr. Deeks' cohort, about 80 percent of these patients were nucleoside‑experienced upon starting their new so‑called HAART regimen.
		So they classified patients either with a virologic response, which in the case of the French study was either a viral load level less than 1,000 or at least a one‑log drop from baseline.  That's considered a virologic response and then an immunologic response, which was considered to be a CD4 cell count, at least 50 over what their baseline levels are.
		They divided people into four quadrants, basically either an immunologic response or a virologic response, positive or negative.  And those are the four groups here.
		In terms of patient numbers, of these roughly 2,000 patients, half were both immunologic and virologically responsive.  And the other half were divided between the other three categories roughly more or less equally, so about a sixth of the population falling into each.  That's at six months.  What we are relating that to here is the percent alive and AIDS‑free, so a composite definition in terms of clinical progression or death.
		What you can see once again here is that the three groups who have either both an immunologic and a virologic response or one or the other have a better clinical response in toto than the patients who have neither an immunologic or a virologic response.
		One of the largest cohorts to date to look at this issue and really tease out virologic response and other immunologic and clinical endpoints is the EuroSIDA cohort.  This was presented at the third Salvage Workshop earlier in the year 2000.
		The EuroSIDA cohort studies well over 8,000 patients and now has described what their responses are.  In terms of the cohorts, one group began their first HAART regimen, their second, and a third.
		And what you need to know about this is how they define that.  Moving from first HAART to second HAART does not necessarily mean failure of the regimen, but it means a change in therapy after at least one month on the first regimen.  So that could be from failure of the regimen.  It could also be from either adherence or toxicity, but it's a real world look at how successive HAART regimens do in terms of response.
		In terms of virologic failure, which they define as a viral load documented at over 500 copies per mill, in terms of the first HAART regimen, 40 percent experienced virologic failure; the second HAART, 50 percent.  And on the third HAART regimen, 67 percent experienced virologic failure on their regimen.  And I should say this is at the two‑year time point.
		Looking at a combined endpoint using both an immune criteria, which was a return in CD4 cell to baseline levels, or a clinical failure, which in this case was an AIDS‑defining illness or death, you can see the percentages, fewer than virologic failure but still increasing with successive regimens, going from 20 percent to 30 to 40 percent in the third HAART group.
		And, finally, teasing out the specific clinical events, which are in some cases, of course, what we are most concerned about, what you see is only 5 percent over 2 years experienced a clinical event with their first HAART regimen, but this jumps up to about 25 percent in the second and third regimens.
		So this is illustrative of the fact that many patients are experiencing failure, whether it is virologic, immunologic, or clinical, but the timing for the failure differs between the three cohorts as you progress in the number of HAART regimens that you have taken.
		I think it is useful in thinking about so‑called salvage treatment ‑‑ I, too, don't like the term, but we use it as shorthand ‑‑ to look at some examples of salvage studies that have been done and in some cases even published over the last couple of years.  This is a short list.  What these trials have in common is they are not for the heavily treatment‑experienced group but for first failures.
		Next.  Arguably, the first salvage study ever done was ACTG 333.  This looks specifically at a saquinavir‑experienced population.  Patients that had taken at least 48 weeks of saquinavir hard gel, no other protease inhibitor.  And, importantly, where we are in antiretroviral therapy for the design of the study, they were not allowed to change their background therapy two months prior to coming onto the study.  Obviously we wouldn't design it that way today.
		Seventy‑two patients were enrolled and randomized either to continue the saquinavir hard gel, switch to the saquinavir soft gel, or switch to indinavir.
		This particular study underwent interim analysis at eight weeks and looked at three different endpoints:  change in viral load, the percent of patients less than 200, and the CD4 change.
		Basically the two saquinavir arms showed no significant difference.  With the exception of a 37‑cell CD4 rise, the indinavir arm showed a .6‑log drop in viral load change and a 37 percent drop in less than 200 copies, which was the limit of detection on this study, but that was felt to be a blunted response.
		In subsequent analyses, they related the pre‑existence of resistance mutations to saquinavir and indinavir as being highly predictive of virologic outcome.
		ACTG 372B is a good example of a salvage study in that it was designed when the parent study, which was ACTG 320, was still in progress.  This study is notable because of the fact that people realize that salvage therapy options for patients failing first line regimens were going to be important to identify.
		So patients were on ACTG 320.  They received either AZT or d4T in combination with 3TC and indinavir and had virologic failure, defined here as a viral load level greater than 500 copies.  You can see 84 patients participated.
		In this salvage study, patients were given what at the time were all investigational agents, efavirenz, adefovir, and then they were randomized using a factorial design to receive either abacavir or a new nucleoside and then plus/minus nelfinavir, so several different questions trying to be answered simultaneously in this salvage study.
		The bottom line ‑‑ and I should say this study focused on the percent below detection, which again was state‑of‑the‑art for therapy in naive patients and, thus, at least in the beginning, for salvage therapy trials, too.  Overall a disappointing only 35 percent had HIV RNA levels less than 500 at the week 16, relatively short‑term, time point.
		Using the factorial analysis, this study showed no difference between adding abacavir or one to two nucleosides but did show a benefit of using nelfinavir in the salvage regimen over a matching placebo, 45 percent versus 24 percent, which was statistically significant.
		Recently published by our group is ACTG 359, which was probably the first large salvage study, which sought to look at a particular patient population, the indinavir‑experienced group.  Patients were required to have taken 6 months of indinavir, had a limited viral load level between 2 and 200,000 were naive to other protease inhibitors and, importantly, non‑nucleosides, nearly 300 patients were randomized into the study.
		They were randomized to receive saquinavir soft gel in combination with either ritonavir or nelfinavir.  So this will be the first salvage study to really look at double PI combinations and then again in a factorial analysis, either the non‑nuc to delavirdine, the nucleotide to adefovir, or both drugs together.
		Bottom line and once again focusing in this trial on the percent below detection as being the primary endpoint, a disappointing 30 percent of patients reached less than 500 copies per mill at the primary study endpoint time, which was week 16.
		In factorial analysis, there was no significant difference between the use of saquinavir‑ritonavir or saquinavir‑nelfinavir.  However, patients who received delavirdine or delavirdine and adefovir had better virologic response rates than those who received adefovir by themselves.
		In terms of longer follow‑up, I can tell you that we will be presenting a poster at the upcoming antiretroviral meeting looking at the long‑term changes in both viral load and CD4 cell counts on this salvage study.
		Lastly in this group of studies is the Abbott 765 study, one of the first to really look at not just a specific protease inhibitor but any protease inhibitor experience.  This is also an example of a study that takes a new agent and seeks to look at its activity in a salvage‑type population.  They did this by being very exclusive about the entry criteria.
		Patients could only fail one protease inhibitor, needed to be non‑nucleoside‑naive, and have viral load levels between 1,000 and 100,000.  So this was really a pilot Phase II‑type design.
		Patients swapped lopinavir‑ritonavir at one of two doses for the current protease inhibitor they were taking while keeping their background antiretrovirals constant for two weeks and then at the two‑week time point all added novirapine and they were all NNRTI‑naive and optimized their nucleosides; that is, they got to choose one or two new nucleosides.  And they were followed for up to 96 weeks.
		Next slide.  So this led to a chance to look in the first two weeks at what the switch from the protease inhibitor that they had failed according to criteria to the new protease inhibitor, lopinavir‑ritonavir.  And what we were seeing over the first two weeks was over a log drop simply with that change.
		So, in keeping with what we were discussing earlier, here is a design which looked at the activity of switching one agent in the regimen for two weeks and showed significant antiretroviral activity.  Then when the other changes were made, novirapine added, nucleosides changed, patients had a persistent suppression of viral load levels.
		And, next slide, that translated to a significant proportion of patients dropping their viral load levels less than 400 in an intent‑to‑treat missing‑equals‑failure analysis.  This is both doses, but they have very similar activity with roughly 60 to 65 percent reducing viral loads below the level of detection for up to 96 weeks of follow‑up.
		The next step from the first failure studies was to look at patients who had failed more than one protease inhibitor.  And just because it has a very similar design to the study I just showed you, the Abbott 957 is similar in many ways except that it allowed at least two or more than two protease inhibitor experience with virologic failure as evidenced by a viral load level greater than 1,000.
		Importantly in this study, once again, patients were required to be non‑nucleoside‑naive.  Once again, they added lopinavir‑ritonavir.  And here is a good example of a drug‑drug interaction, which was described while the study was going on and then dose adjustments were made, a significant interaction between efavirenz lowering the concentrations of lopinavir in the presence of ritonavir and a boosting of the dose of lopinavir‑ritonavir while the study was going on.
		Once again, with all of those innovations, a significant number of patients dropping viral load levels, again, important to remember that they added efavirenz and were all non‑nucleoside‑naive but at the higher dose, in particular, shown in pink, 70 percent of patients reducing their viral load levels below 400 for up to 48 weeks.
		Okay.  But all of these patients don't really meet the definition that we have been considering.  These are the first iterations of trials, but what we have been considering most of the day are heavily pretreated patients.
		The definition which we have talked about earlier today is having a loss or lack of virologic response on at least two HAART regimens and being three‑class‑experienced.  So what is the data for this particular group?
		While we go back to the EuroSIDA cohort, the first thing to know is that in 1996 in this cohort, there were no patients who had three‑class experience.  In the year 2000, 35 percent of the EuroSIDA cohort are patients who have had three‑class experience with the current drugs.
		This is looking at a subset of those, 266 patients who had 3‑class experience and began another new salvage regimen.  So this is addressing the fact in a clinical cohort:  How do these three‑class experience patients do?
		Forty percent decreased their viral loads less than 1,000.  And 30 percent maintained that decrease for as long as 6 months.  Fifty‑five percent had at least a one‑log decrease and most of them, 45 percent, maintained this decrease at 6 months.  Looking at it another way, 55 to 70 percent of these 3‑class‑experienced patients had virologic failure by the end of 6 months.
		What about other endpoints?  Over half, 55, decreased their CD4 below baseline.  So if you use that as an immunologic criteria, you would say that they had immunologic failure and that was at the ten‑month time point.  But only five percent had a new AIDS event or death; that is, experienced a new clinical endpoint over the ten months of the study.  That gives us some idea of how this patient group does in terms of those three endpoints:  virologic, immunologic, and clinical.
		What were the predictors in the EuroSIDA cohort?  In terms of virologic response, any prior viral load less than 500 was predictive of virologic response, less prior treatment, a higher latest CD4 cell count, and, for reasons that aren't clear to me, being a resident of Central Europe was predictive of a virologic response.  Perhaps our European colleagues could comment on that.
		In terms of predictors of immunologic and clinical response, having female gender was a predictor.  A lower latest viral load, and fewer prior antiretrovirals were all predictive in this three‑class experience group.
		What about clinical trials in this group?  There are two notable studies that have looked at highly treatment‑experienced patients.  The first was CNNA 2007.  This has been presented nationally both by Drs. Eron and Falloon.  It looked at patients who had at least 20 weeks of combination therapy with a protease inhibitor and a viral load level of at least 500.  And there were 99 patients.
		This is one of the most treatment‑experienced populations ever enrolled into a clinical trial.  Three‑quarters had experience with 4 to 5 nucs, 44 percent with a non‑nuc, and 60 percent had taken 3 to 4 protease inhibitors prior to going on to the study.
		They received what at the time again were three investigational meds, now all approved, both in label, abacavir, efavirenz, and amprenavir.  The primary endpoint for this study was antiviral effect at week 16.
		Overall, once again, a disappointing result with only 26 percent, dropping viral load levels less than 400 at week 16.  Also, a significant drug interaction was identified between efavirenz and amprenavir on the study, which may have contributed to that somewhat disappointing result.
		And then in a subgroup analysis looking at NNRTI experience and viral load levels, not surprisingly, it was found that the subgroup that did the best were those who were NNRTI‑naive.  Recall that they got efavirenz and those with the lowest baseline viral load levels.
		Probably the largest salvage study done to date is ACTG 398 presented by both Dr. Hammerstrom and Dr. Mellors at various meetings.  This looked at people who had taken at least four months of up to three prior PIs, viral loads over 1,000.
		They could have taken NNRTIs, although it wasn't mandated that they take them and nearly 500 patients enrolled in the ACTG.  Once again, the approach here was to give all new drugs.  Every one received open label amprenavir, abacavir, efavirenz, and adefovir together with in three out of four groups a second protease inhibitor, either saquinavir soft gel, indinavir‑nelfinavir, or a matching placebo.  And the primary endpoint looked at was week 24.
		Overall, once again, a very similar and disappointing 31 percent dropped their viral load levels below 200 at week 24.  And then using subgroups, NNRTI‑naive subjects did better.
		Patients who took two protease inhibitors did better than those who took amprenavir alone.  And, surprisingly, patients who had experience with just one or more than two protease inhibitors did about the same.
		Importantly also for ACTG 398 ‑‑ and I don't have the slide to illustrate it ‑‑ is that they focus not just on the percent below detectable but the change in viral load levels.
		At the end of week 24, all groups had approximately at least a one‑log decrease in viral load levels from baseline.  That's important.  Particularly if you focus on this number, overly focus on that number, you might miss that important point.
		Well, there are examples of just what we have been considering today.  How do you test a new drug in a treatment‑experienced population?  I'm going to show you three examples.
		The first is using the investigational nucleoside analog DAPD.  These are results, once again, that Dr. Eron has presented.  It looked at a study population who failed either ZDV or d4T plus 3TC, had specific viral load levels and a CD4 count above 50.
		This is really on the pilot study level.  It's a sample size of 24; however, once again, a very treatment‑experienced group.  Average number of antiviral is six, length of treatment four years.  A hundred percent had taken nuc, 60 percent or more non‑nucs, and over 80 percent had taken protease inhibitors.
		They were randomized to receive DAPD at one of three doses.  Three groups actually washed out of their antiretroviral seven days prior to going on.
		One group added DAPD onto the regimen that they were already taking, so short‑term virologic effect being demonstrated in a group of highly treatment‑experienced patients.  And that is what is shown for you here.
		So three doses in the patients that washed out.  You could see at a higher dose, about a one‑log drop.  Surprising to investigators was the fact that the group that added on, as opposed to experiencing a seven‑day washout, had a much more profound drop in viral load, about two logs below baseline, by the end of two weeks.
		The next example is the investigational nucleotide analog tenofovir.  This is the Gilead 902 study.  This is an example of the add‑on design that we discussed earlier, patients on stable antivirals with a viral load of at least 5,000.
		Nearly 200 patients enrolled; once again, a very treatment‑experienced group.  Baseline mutations in nearly all for nucleosides, a third for non‑nucs, and about 60 percent for protease inhibitors.  They were randomized to add one of three doses of tenofavir or a matching placebo.
		Here is a nice dose‑response curve.  Placebo is in blue with very little change through 24 weeks, the greatest change is at the highest dose of tenofavir.  This is sustained at about .7 logs by the end of 24 weeks.  At this point, the placebo group is also offered in a crossover design the highest dose of tenofavir demonstrated.
		The other endpoint looked at was CD4 cell count, for reasons that aren't completely clear, relatively low CD4 response by the end of 48 weeks.
		The last example of using an investigational agent in a highly treatment‑experienced group is the investigational fusion inhibitor T‑20.  This is the T‑20 205 study.
		This is actually a very novel design.  The studied population was those who had T‑20 experience in one of the earlier studies that the drug company had sponsored.  So they were offered this study as a rollover study.
		Seventy‑one patients entered.  Again, incredibly treatment‑experienced, 80 percent were this specific patient group we have been considering 3‑drug class‑experienced.
		They underwent baseline genotyping and were allowed to add T‑20, 50 milligrams twice daily subQ plus the other antiretrovirals, which were chosen by their practitioners on the basis of history and the genotyping or what you might call optimized baseline regimen and then followed for 48 weeks.
		In terms of results, 20 percent had less than a .5‑log reduction, so were essentially virologic non‑responders.  However, a third had at least a one‑log reduction or reduced their viral load levels to less than 400 using this strategy.
		This is actually an on‑treatment analysis of change in viral load, rather than an intent‑to‑treat.  It goes out to week 32 presented at the Durban AIDS conference.  You can see significant virologic suppression sustained in this highly treatment‑experienced group with this novel design.
		In summary, in terms of salvage therapy, what we have been saying all day, virologic failure occurs commonly.  Immunologic and clinical failure also occur at probably different rates and different times.  And all need to be evaluated potentially as endpoints.
		Predictors of response:  not surprisingly, adherence, levels of viral load and CD4, resistance profile, number of active drugs and drug levels all may come into play.
		Importantly, newer drugs with novel resistance patterns or mechanisms can and do demonstrate an activity, even in the heavily treatment‑experienced patient population.  And novel study design may demonstrate this activity and at the same time provide benefit for the subjects, the conflict we have been talking about all day.  And further clinical research is necessary.  I'll stop there.
		Thank you, Dr. Gulick, although you did run on a bit long.
		(Laughter.)
		ACTING CHAIRMAN GULICK:  I would like to introduce Dr. DeGruttola from the Harvard School of Public Health to talk about statistical considerations.
STATISTICAL CONSIDERATIONS FOR ENDPOINTS IN
HEAVILY PRETREATED PATIENTS
		DR. DeGRUTTOLA:  Well, given this morning's discussion and in the spirit of full disclosure, I want to let everyone know that I am myself a two‑part hybrid because, in addition to working in AIDS research, I also teach statistical design for graduate students in my department.
		I would be happy to report to them that the phrase "factorial design" has had almost as much impact here as "pregnant Chad" has in Florida.  If anyone says this is just a narrow technical area, I think I will have a good rejoinder.
		I'm going to talk a little bit about choice of endpoints for salvage studies.  And, just to review quickly the endpoints that have been used, as everyone is aware, there are clinical endpoints which we used earlier on in the epidemic, may make a comeback, AIDS‑defining events, survival, quality of life; marker‑based endpoints, like HIV RNA and CD4.
		Endpoints, of course, for toxicity can be time to treatment discontinuation or targeted adverse events.  Finally, there are composite endpoints that combine information across different endpoint categories; for example, time to treatment discontinuation, whether for virologic failure or intolerance.
		We look first at the HIV RNA endpoints.  Even within that group, there is quite a range.  There are quantitative endpoints, change from baseline to week X; time to virologic failure variously defined; or we have binary endpoints.  We could have one that is just cross‑sectional, like either above or below a threshold at week X, or a more cumulative one:  Have you failed by week X?
		So if we look first at the cross‑sectional endpoint, it is a snapshot.  It is not affected by to‑be‑transient changes in HIV levels and frequent monitoring is not required.  So those are advantages, but a problem is that missing data at the time point where you're doing the measurement is especially problematic because you can't make use of the other information unless you carry values forward.  And I will say a little bit more about that, as Dr. DeMasi mentioned.
		Failure endpoints, of course, require assessments over time.  They may be affected by transient changes in HIV RNA levels, and frequent monitoring is required.
		Although you need to define your missing data strategies, you can more easily make use of partial information if you use a failure endpoint and also if after patients fail they can go on to some other treatment, that doesn't complicate an analysis in a time to failure because you have already got your endpoint; whereas, if you had a snapshot change by a certain period of time, then that would be a complicating failure.
		Now, within the failure group, you can either do a time to failure or a cumulative proportion analysis.  The time to failure, some of the concerns are the pattern of failure depends on the failure time.
		In other words, we have definitions of failure for people who fail within the first four or eight weeks of not having declined enough or later on perhaps of having a rise above nadir or rise above detection and so on.
		What we mean by "failure" is different at different times.  There are some inherent assumptions there, but the advantage of time to failure is it accommodates differential follow‑up.  And it is very useful if you are doing an interim analysis to be able to make use of the partial follow‑up as well as, of course, at the end of the study.
		The cumulative proportion has the advantage that you don't have to worry so much about the definitions of failure at each individual time point because you can sort of make use of the whole trajectory in making that consideration.
		So, although you need failure definition whether you do cumulative proportion or time to failure, the cumulative proportion is not quite as sensitive to the exact failure definition as the time to failure might be.
		The problem is that evaluation within an interim analysis is complicated.  There are also some power advantages of time to event.  Especially if the pooled failure rate between the arms is greater than 50 percent, time to event has appreciable advantages.
		Just focus on the bottom line.  If you had a study with a one‑year accrual, six months of additional follow‑up and a two‑arm trial, then look at the bottom line with a 70 percent pooled failure rate.  You get a 25 percent savings in sample size, which is considerable.  So there are real power advantages of time to event if the events are quite frequent.
		Some analysis issues.  If you have moderate study withdrawal, time‑to‑event endpoint advantages increase further.  These sample size advantages are even greater at interim analyses.  You're much more likely to stop in an interim if you use time to event because you make better use of your information.  There are also advantages for co‑variate, evaluating co‑variate, effects or flexibility in ending the study.
		So the only real down side is that you are a little more sensitive compared to cumulative proportion on the precise definition of your failure.
		And if we compare a purely virologic versus a composite endpoint, a purely virologic focuses only on the virologic response and allows tolerability and safety to be assessed separately.  But, of course, you have to follow up for viral load after treatment continuation.
		A composite, which hasn't really been discussed a lot here ‑‑ so I am going to go through this quickly.  A composite endpoint might combine virologic efficacy, tolerability, and safety.  And, of course, it could differ substantially from the purely virologic if the toxicity rate is high and if you use that endpoint, you would at least want to do the virologic, pure virologic, as a secondary endpoint.
		Some definitions, the issues in defining virologic failure, obviously you have to define an early failure, whether you're talking about insufficient decline, rise above nadir, the amount of time allowed before patients go below threshold, the choice of the threshold for suppression/loss of suppression.
		Of course, what do you do about fluctuations due to treatment holes into current illness and so on?  Patient stops drug, virus comes back, restarts, and they're doing well.  Was that a failure or not, all those kinds of issues?
		If you use a regimen completion endpoint, then you have all of the same issues, plus you have to worry about how many drugs need to be changed or added before you declare it was a failure?  And are you going to call all discontinuations failures or just those related to toxicity?
		One of the factors that are going to affect the choice of endpoint is:  What are the underlying clinical beliefs?  In purely virologic endpoint, you believe that the effective therapies on RNA capture the essential information to define the role of the therapy.  For the regimen completion, you believe the necessity to change regimens more closely measures tangible benefit.  And the choices are obviously going to depend on the clinical beliefs.
		The next slide just shows some of the types of endpoints that have been used in studies within the AIDS Clinical Trials Group.  There have been, as you can see, a variety of choices, including the time to failure, regimen completion, the cumulative proportion failed by week X, and whether patients have gone below a threshold by a certain time point, and so on.  There have been a range of different endpoints.
		Now, a little bit more about the composite endpoints.  They are going to be more numerous than a purely virologic endpoint, but they can dilute the effect of a treatment and especially concern if treatment discontinuation might be unrelated to the treatment, for example, of pregnancy, imprisonment, and so on.
		The next slide.  This slide just shows that if you have treatment discontinuation that is unrelated to the treatment if it happens kind of equally with equal trends in both treatment arms and you are going to dilute your effect, then you will end up with lower power than if you used the virologic failure alone.  Even though you get more endpoints from the composite, you end up with less power, in this particular example reducing from 80 to 60 percent.
		I will skip the next slide, which is just illustrating that point, and go on to the factorial design of 359, which Trip Gulick just mentioned.  He was the chair of that study.  He described the randomization factorial between ritonavir and nelfinavir and then between delavirdine, adefovir, or delavirdine plus adefovir.
		The results graphed in this way showing the proportion below detection for the different arms.  And, as John Mellors noted earlier, your power to compare any individual cell with any other cell is much lower than if you had just done a two‑arm study, but you can look at the different factors in the next slide.  This is for comparing ritonavir and nelfinavir.  And in the next slide, the comparisons between delavirdine, adefovir, and delavirdine and adefovir alone.
		Next slide.  You can also, of course, look at the mean HIV RNA change from baseline in this slide displaying all of the arms.  One of the interesting questions is:  How much more power do you get from using change in HIV RNA compared to proportion below detection?  Obviously the change should give you more information.  There should be more power.
		Next slide.  This slide just shows that there were actually more than 90 percent of patients that have 16‑week data.  The messiness was scattered over the arms a little bit more in the ritonavir.
		Next slide.  This comparison, as I think Trip has already shown, shows once again that when you compare ritonavir and nelfinavir, you don't see a difference, but comparing over the arms in the other factor, you do see a significant difference.
		Then in the next slide, if you do the same tests on the median change from baseline, it was interesting.  You get pretty much the same message.  Of course, ritonavir versus nelfinavir is not significant.
		And here the group gets slightly different comparisons.  Rather than comparing across each of the comparing across all of the three levels of the delavirdine‑adefovir factor, they did the comparisons individually.
		What was interesting is that you do see the significant difference between delavirdine and adefovir, not significant difference for the other ones.  Overall there didn't seem to be a lot of difference in the message; in fact, none at all, that you would get between looking at a proportion below detection or a change from baseline.  So I think it would be very useful, in fact, to be able to look at both of those and just look for consistency.
		This study shows results of AIDS Clinical Trials Group Study 364, in which patients received two nucleosides and randomized to nelfinavir alone, efavirenz alone, or the combination.
		This slide shows the results with the time to virologic failure.  And, interestingly, all of the comparisons, both the three‑way comparisons across all the arms in each individual comparison, showed a statistically significant difference.
		In the next slide, if you looked at a time to virologic failure or stopping the step one treatment, that was not an endpoint in the study.  We just did this analysis to try and investigate what would happen if you used different kinds of endpoints.
		What is interesting here is that you see the same ordering of the arms, but the comparison of efavirenz versus nelfinavir plus efavirenz, that's the comparison that's at the bottom here.  I don't know if folks can see that.  It is non‑significant in this case.
		So it is interesting that, once again, you get more endpoints with the time to virologic failure or stopping the treatment, but you end up with actually a nonsignificant comparison, which was in the other endpoint.
		The next slide gives some illustration why.  The curve that is in red there refers to the patients that got nelfinavir plus efavirenz.  And, although 12 of those patients actually stopped treatment ‑‑ that was the highest number that stopped treatment, only 2 of them actually experienced virologic failure.  The curve drops more because of the number of people in the risk set.
		So I think that these kinds of investigations can be useful in looking at salvage trials or any trial.  If virologic failure is the primary endpoint, it is probably the most informative, but it may be interesting to look at the time to stopping the treatment or virologic failure and then investigate what happened to the people who stopped treatment.
		Now, a big issue that has come up frequently in this and other settings is:  What do you do about losses to follow‑up?  Well, the first point that you need a policy for handling them is pretty obvious.
		If you treat a dropout as either censored or treat it as failured, either result can be biased.  So one of the approaches is to do both of them and see whether it makes a difference.
		And then I think it is also going to be increasingly important to do sensitivity analyses to try to investigate the robustness of the results that you get to different assumptions about how and why patients dropped out.
		The next slide.  This is just hypothetical data that Camlon Tierny generated and just showed an example, a hypothetical study, where you get a treatment effect comparing A to B.
		Then in the next slide, what we see is the same study where half of the patients had equal risk of dropping out at any time point in the study.  And what you see, of course, is you lost power.  There is no significant effect.
		And then in the next slide, the next slide shows the case where ‑‑ well, in the previous slide, we had independent censoring.  It had nothing to do with the treatment assignment.  In this case, for the curve that is in red, we have an example where one arm experienced more loss to follow‑up than did the other arm.  So the treatment did lead to a difference in losses to follow‑up.  And obviously you can get a strongly biased effect in this case and p‑value of .9 that is not at all significant.
		Then, to show an example of a study in which different approaches to missing this were actually ‑‑ to handling missing this and dropping out were actually taken and what impact it had to protocol 398 that Trip Gulick already introduced.
		In this arm, all of the patients received amprenavir, abacavir, efavirenz, or adefovir.  And then patients were randomized to receiving on top of that either saquinavir, indinavir, or nelfinavir.
		And in the next slide, the design of the study.  These are the actual numbers that enrolled, the patients, but the kind of ideal that was proposed at the start.
		The randomizations depended on the experience, the prior experience, that the patient had.  So, for example, patients who had already been exposed to saquinavir were not randomized to saquinavir again but only to either indinavir, nelfinavir, or placebo.  And, of course, if it were a new drug you were investigating, you could have, instead of the placebo, put the new drug in that particular slot.
		Then the next slide, I think Trip has already shown some of the results from protocol 398.  It appears as though in this slide, which looks at the median changes from baseline, the placebo arm had the least median change from baseline.
		Next slide.  This slide looked at two different ways of handling the missing data.  The column on the left is a missing equals failure analysis.  The column on the right is missing at random assumption, MAR, treating the missing as censored observation.  And this was the estimated virologic failure rate at week 24.
		And, as you can see, that rate was quite high across all the arms.  But if you look separately at the group that did not have NNRTI experience, the group that was getting their first NNRTI, the failure rates were in general lower.
		What was reassuring about this analysis is it showed that, although the missing equals failure has higher failure rates than the missing at random assumption leads to, in fact, the patterns of failure are very, very close between these two analyses.  So the inference is very much the same.
		In the next slide, the study also did a primary comparison of the proportion of the patients whose RNA values were less than 200 at week 24, showing kind of similar results.
		And the final slide for 398, this slide showed the p‑values for two different analyses.  One was whether or not patients had a confirmed virologic failure at or before week 24, the analysis on top.  The analysis on the bottom is for the time to confirmed virologic failure.  We don't see a lot of difference.  In fact, those two analyses are very consistent.
		Also, comparing missing equals failure and missing at random were done.  Once again, you get a reassuring agreement in these analyses that if you look at the left column, receiving a new protease compared to placebo was a significant difference.  And also the nelfinavir versus placebo was significant.
		I should point out that there ended up being a lot more patients randomized to nelfinavir because of the patient population that entered.  So there was more power for that comparison than the other ones.
		In the next slide, we want to get back briefly to the question of:  If you're looking at a change endpoint, a change from week 24, let's say, to baseline and some patients either drop out in the middle or they switch to another treatment in the middle, how do you handle this situation?
		One of the things you can do is carry the last observation forward, but if the RNA curve, schematically drawn in yellow here, is not flat but, in fact, has this characteristic dip and rise, then when you dropped out, it is going to make a big difference.
		So one of the ways of addressing this issue is you might want to consider carrying the last rank forward, rather than the last observation itself.
		So, for example, if a patient dropped out at one, two, or three in that case, although their levels would be very different, the rank might not change quite as much.
		Then in the next slide, so, finally, some discussion points.  Should we count study withdrawal as failure censored?  Each one is likely to be analysis.  Recommend carrying out both and doing some sensitivity analysis.
		And then, the final slide, what are the criteria for selecting the primary endpoint?  Well, obviously you want to select an endpoint that addresses the primary objective, taking into account patient population of the study drugs.
		It is going to be very different across different populations or it may well be different.  And within the possible pool of surrogate markers, try and pick one that we believe to be the best possible replacement for a true clinical endpoint, but I want to strongly endorse what Mike Saag and others have said today that we need cohorts, long‑term follow‑up to find out how well these surrogates are really doing.
		I would add to what Mike said that including in those cohorts longer‑term follow‑up of people who have participated in a randomization would be helpful as well.
		ACTING CHAIRMAN GULICK:  Thanks, Dr. DeGruttola.
		Are there clarifying questions for either Dr. DeGruttola or me?
		(No response.)
	QUESTIONS TO THE COMMITTEE
		ACTING CHAIRMAN GULICK:  Okay.  So our last task this afternoon is to address two last questions to the Committee, both concerning endpoints.  The first is:  What are the most appropriate study endpoints for trials in heavily pretreated patients, comments on the strengths and weaknesses of virologic, immunologic, and clinical endpoints?  And, in addition, discuss the relevance of virologic endpoint metrics other than below the level of detection.
		So let's stick to the first question, What are the most appropriate study endpoints?  Dr. Mathews?
		DR. MATHEWS:  Bearing in mind we are talking about pretreated patients, I think in my own mind that we somehow need to include in the endpoint both CD4 and viral load response.  The reason I say that is because of the accumulating data that people are still experiencing clinical benefit.
		You know, at one extreme, if the trigger were rebound from baseline viral load or becoming detectable again, in practice many people would not change the regimen, even if there were potential options available for those patients, because they might want to wait a while.
		So if the real goal of the therapeutic analysis is to determine clinical benefit and not some arbitrary virological endpoint, perhaps we should grapple a bit with:  How do you integrate both CD4 and viral load response?  Do you have multiple endpoints or sequential endpoints so that if a person met a virological endpoint but had not yet met an immunologic endpoint and had few options, they would continue on therapy?
		Another angle on this is if you're going to look at binary responses, failure or not failure, if you were going to integrate CD4 and viral loads, it would not simply be binary.  There would be perhaps three or four categories of responses that would be taken into account.  And they could be ranked by their prognostic value, which we're seeing accumulating evidence from natural history studies that, in fact, you do learn something from looking at these so‑called discordant responses.
		ACTING CHAIRMAN GULICK:  Dr. Eron?
		DR. ERON:  This is kind of more of a question to Mike and Victor and others.  We frequently say things like "a half log change in viral load connotates a clinical benefit" or "is likely to result in a clinical benefit."
		Of course, that has to be a half log change at some time.  I mean, two weeks it probably isn't important.  At 16 weeks, maybe it is.  Do we have a better handle on that?  Are there algorithms for both change in viral load and change in CD4 to try to capture the clinical benefit, particularly from some of the older studies?
		DR. DeGRUTTOLA:  I think that someone alluded to one of the studies by Ian Marshener and a group of us within the eighth Clinical Trials Group.  As I recall, that was looking at HIV RNA at the exchange point, but it was in the era of the nucleosides.  I think it did show that a half log drop was associated with better outcomes.
		We haven't gone back and redone those analyses in the modern era.  So I think we should be a little cautious about assuming that the same relationships will hold with the currently available drugs.
		I think that those analyses should be repeated.  Maybe they have been, but I think we need to see more of that.
		ACTING CHAIRMAN GULICK:  Dr. Murray and then Mr. Hogan.
		DR. MURRAY:  I think the only data that would illustrate when you should cut an endpoint, at what time, would be maybe the Pharmacia, an Upjohn endpoint that was presented at a 1997 committee, and where a response was a half a log at least and that they looked at days of response of a half a log at least correlating with clinical benefit.
		I think you really didn't get a significant correlation until it was about greater than eight weeks or so.  So probably something less than eight weeks.
		In fact, in one of those studies, 017, I guess, ‑‑ it was delavirdine added on to ddI ‑‑ there was about a half a log difference between the arms, but it only extended to maybe six to eight weeks.  And there was no difference in clinical benefit in the treatment of raw.
		When the studies were analyzed according to days of response, something less than two months didn't ‑‑ there's lots of data showing that 16 and 24‑week changes of anywhere from .3 to .5 logs for the group did correlate with some clinical benefit.  And we went through that data about three or four years ago but only one really analysis looking at the time effect.
		I guess I would like to probe the combination CD4‑HIV RNA endpoint because I guess in my mind if I were interested in a drug to treat patients who had been heavily treated, I would really be looking for a drug that would have an antiviral effect.  If it didn't have an antiviral effect, then how different is that than maintaining the status quo?
		I mean, presumably the people who are doing well on drugs who still have viral replication are doing so because maybe they're maintaining mutations and they're maintaining a less fit virus.  But do we need another drug just to maintain mutations or less virus?  Are we really looking for hopefully a drug that would be a little bit more novel?
		I would think, I would hope to have, drugs that would be developed that would have an antiviral effect in patients who had already received treatment.  And I think it would be pretty murky to interpret a combination if there was no antiviral effect, to just look at CD4.
		ACTING CHAIRMAN GULICK:  Mr. Hogan and then Dr. Saag.
		MR. HOGAN:  Well, I think it's important to recognize that a half log change in viral RNA is sort of to cut off what's significant in an individual, but in aggregate groups, much smaller changes actually are meaningful.  So as you have a larger group of people, you get more precision in that.  And you've got a greater sensitivity.
		I would love to be as optimistic to believe that we're going to have therapies that are going to have dramatic virologic effects in this population.  It's not clear to me, at least based on what we in the lay community see coming down the pipeline, that that is extraordinarily likely.
		I do agree that trying to figure out how to combine CD4 and viral load in a meaningful way would be a Herculean task.  I mean, just weighting the two against each other, I wouldn't know where to begin, but, as I said in my presentation, I do think preservation of CD4 count may be possibly the most relevant and the most achievable surrogate endpoint that one could hope for.  And certainly if you look at the data, CD4 count is so much more predictive than viral load.
		Now, the caveat to that is in very low CD4 count people, that's not as true, but for your short, intermediate‑term risks, CD4 tells you so much more than viral load.
		Lastly, I guess, I hate to stir up controversy, but we don't really have a good grasp on what the course of disease is in these, quote, unquote, "deep salvage" patients yet.  And, as people are noting, they are seeing research in allies, and it may be realistic to talk about clinical endpoint trials.
		ACTING CHAIRMAN GULICK:  Dr. Saag?
		DR. SAAG:  I would like to go back to maybe Jeff's point and sort of remind ourselves that these are antiviral drugs and for the most part are retroviral.  So I think we ought to look at the virologic activity.
		What's interesting to me is that the 0.4, 0.5 log reduction is a factor or is a value that keeps coming up over and over again, which sort of hints to me that it might be important.
		Let me be precise that 0.3 oftentimes is just considered to be the variability in the assay, at least in the old days.  And so for us to have looked at any drug early on, back when these drugs were first being developed and viral load became available, 0.3 is what we wanted as a minimum to say that this is different than just placebo or just some random effect.  So the 0.5 is a minimal effect that you would like to see.
		The second thing is the Ian Marshener study that Victor referred to.  While I think there is a possibility that it is class‑specific, biologically it's hard for me to understand why that would be.
		So I think we ought to explore that, but in the meantime I don't think it's such an unreasonable assumption to say that biology is biology and why should it be different based on the type of drugs.  You just get more of it.  You get more of a drop than .5.  But it's possible that you might not see the effect.  It needs to be explored, but at least that's a hint that that number might be important.
		The third thing is work that Steve's group has done as well as our group to maybe a more limited degree that just looks at the sustaining of CD4 effect, even among people who have rising viral loads coming back up, that the CD4 count does not seem to drop until you cross that magical threshold of about .4 to .5 log as you come back to the original baseline.  So I think that's a reasonable number just to pick one.  That's one I would put out.
		And I think your point is right.  If you look at a population, that may be different, but I would flip it around and say I would take each individual patient and say:  Look at the time to failure.  And look at it from a Kaplan‑Meier survival‑type thing in terms of time to failure.  And that's how you would define.
		If at eight weeks you look and they're not where you need them to be, they're a failure.  They're categorized as a failure.  They move on to whatever else, and that's the endpoint for that study.  And if they are below it, you just follow them out and see how long they are out and then at the end of the day what proportion of patients are below that target or not for this population.
		I think maybe the final point is one that Judith Falloon said.  I think this is exactly right, and I don't know how to deal with this exactly.  We have to remember the people are coming into the study on something usually.  So, really, the .5 below baseline, the baseline in my mind is really off therapy.  And if we could go back and find out what their set point was, then you've got something that you can hang your hat on.
		Maybe it's worth a run‑in off therapy.  I think it's a little bit hazardous.  Somehow we're going to be stuck with a decision of requiring in a study that we know what their set point was off of therapy or determine it versus let that go and just take whatever they are if we're defining them as, quote, "failing" and hope that we can get .5 reduction further from whatever they were on before.
		If we're simply adding the drug, the new agent, to the failing regimen, that's a legitimate thing to look for .5 in a short period of time, like that 10‑day double hybrid monster thing we were talking about, but for start changing the entire regimen and adding or not, then it becomes a little bit more problematic.  And I think that is something that we have to wrestle with.
		ACTING CHAIRMAN GULICK:  Dr. Schapiro?
		MR. HOGAN:  One clarification.  One thing which I don't think I expressed clearly was that that .5 log is the variation in the individual and that as you get larger groups, the variation becomes much smaller.  So that's what I'm saying.  When I'm saying need, what I meant was that variation.
		The final thought which I didn't say before I'll shoehorn in, I think it's very important to recognize the increase in power in using non‑binary outcomes.  And I think below quantification may not only be unrealistic, but it's also less power than using something continuous.
		ACTING CHAIRMAN GULICK:  Dr. Schapiro and then Dr. Mathews.
		DR. SCHAPIRO:  To specifically address the question of Dr. Murray regarding combining CD4 and viral load and taking into consideration what we heard from Victor, I think combining is dangerous because we do have a dilution effect.  We're working very hard to get our numbers up as high as possible, and then we're doing things which are going to reduce our power.
		What was not shown in many of these presentations, for good reason, is the CD4 response.  VIRADAPT, GART, all of these studies, VIRA 301 many of these, don't show any difference in CD4 cell.
		When we do a comparative study, when we do the descriptive studies, we love to show CD4s because we show something.  When you do these kinds of presentations, myself and all of us, we tend to show the viral load because they're more informed but, actually, because there wasn't any difference in the CD4s.
		And the virology of this has I think been described in many studies.  It appears that any reduction in viral load, I think, as Mike said, below 0.5, whether it's an 0.6 and 0.9 might not show over the same time period of CD4.
		There's some suggestion from Steve's data that might manifest way out there, but it's not going to give a change here.  If we add CD4 on, we're going to get dilution of our viral load.  So I would say that in this population, I would say not to combine.
		A second issue I would address is the cutoffs.  I think we made mistakes in the past.  Looking at some of these data, I think in Trip's presentation, we saw that often there were very disappointing results because we were using probably the wrong endpoint.
		Using cutoffs in general I think is a less good idea.  I also think that we should probably be less trying to prove something than show our data.  Change in viral load is good, and we can later do a lot of things with that.
		My gut feeling would be that we should show the change in viral load.  That should always be an endpoint.  We can do other things with that later.
		I would say splitting it, as opposed to combining it.  It is good to see as many endpoints as we can to get the differences and not to get too sophisticated with combining.  I think we will get in trouble there.  I think we should try to keep it simple.  And I think we should look at multiple.
		And just one last thing.  We should keep in mind that all of these are regarding our standard antiviral therapies.  I think, for example, when we started looking at maybe hydroxy area and I think we're going to have other novel types of interventions, we have to reconsider what we're looking at.  They may be working.
		We would like to always know what is a good surrogate for clinical endpoints.  I think viral load is very good with our standard drugs.  When we look at others, we should keep that in mind.
		ACTING CHAIRMAN GULICK:  Dr. Mathews?
		DR. MATHEWS:  Well, I don't want to see the final nail put in the coffin of something other than viral load as an endpoint.  You know, this morning already several other potential endpoints were talked about which are virologic endpoints but aren't viral load endpoints, such as resistance and fitness.
		My major point on this is that if you're talking about treating a particular population of patients, the goal should be to find out what treatments confer clinical benefit.
		Clinical benefit certainly is not completely summarized by a viral load response.  I mean, we have seen lots of data, both from natural history studies as well as clinical trials, to that effect.
		So I don't think that we're wise to just say the only thing worth looking at as a clinical endpoint is some kind of a virologic response, whether it's binary or continuous, but that we ought to look at the evolving natural history data that's clearly already useful for prognosis and see if that data can be used as a part of a clinical endpoint.
		You would end up with an absurd situation of taking a heavily pretreated population into a clinical trial, deciding that they had met some virologic endpoint.  Maybe they were within .3 or whatever or their baseline viral load but their CD4 counts were still rising and they had few, if any, other treatment options.  You would declare them a failure and take them off study.
		I think it's a legitimate scientific question to study:  How long does the benefit last in a controlled setting, and what do you do with the patients who are in that intermediate zone of having met an approximate virologic endpoint but have not met an immunologic or clinical endpoint?
		ACTING CHAIRMAN GULICK:  Dr. DeMasi and then Dr. Pettinelli.
		DR. DeMASI:  Just a couple of comments about the composite endpoint and then potentially multiple metrics of a viral load response or CD4 clinical endpoints to use as efficacy endpoints in clinical trials.
		I think that there is some data if the surrogate markers work looking at the correlation between CD4 and RNA in clinical disease progression.  Most of those analyses did show the independent prognostic value of CD4 and RNA in terms of predicting clinical disease progression or death.
		And some of the analysis did rank the endpoints in terms of decrease or increase in RNA and a decrease or increase in CD4 count.  In looking at the discordant responses, the intermediate response, obviously patients doing better in viral load and better in CD4 are the best responses.  And the patients doing worse relative to baseline would be the last category.  So you could have a ranked endpoint including both CD4 and RNA in that fashion.
		The second point regarding the multiple metrics of viral load response and/or CD4 count or clinical endpoints is such that the protocol study could be designed to look at as a primary analysis differences in any one of the endpoints and an additional secondary step‑down procedure could be looked to see what endpoint is statistically, not only statistically, significant but clinically meaningful.
		ACTING CHAIRMAN GULICK:  Dr. Pettinelli and then Dr. Cunningham.
		DR. PETTINELLI:  My only comment is maybe even in this case of having an endpoint, we might want to consider the population we are dealing with.
		For example, for patients who have an option from whom we would expect a somewhat boost virologic response, then we might go back and look in percent of patients undetectable and so on.  For more advanced patients in this situation, it may be different.  So somehow I think we need to tailor.
		Also I think we should not forget toxicity.  If that uses a primary endpoint or secondary endpoint, I think it's very important to be able to discern what is the toxicity vis‑a‑vis the activity of the compounds.
		ACTING CHAIRMAN GULICK:  Dr. Cunningham?
		DR. CUNNINGHAM:  I've been remiss in my job to continually remind everybody about children, but that's because, really, I thought you guys were talking about pediatric trials all day.
		ACTING CHAIRMAN GULICK:  We were.
		DR. CUNNINGHAM:  In actual fact, every single discussion that's occurred today, including the CD4 and RNA discussion and endpoint discussion and all of the discussions this morning about trial design are really the same issues for pediatric patients.  In, really, almost all of the trial design options that were discussed this morning, there are sufficient pediatric patients to entertain.
		I think regarding the issue of the CD4 and the RNA endpoints, in pediatrics, we would still primarily like to see an antiviral effect and would expect to see that as a primary endpoint in all treatment trials but also agree that you have to look at CD4s as well because there are patients with the discordant response.
		It's funny.  I haven't felt compelled to say, "You're leaving out children" because, in actual fact, there is not a single discussion that has occurred today where children do not have the same issues with access to drugs and access to trials and needing that information.
		Actually, every time you guys put up a study, I was just picturing 5‑year‑olds.  You guys were just picturing 30‑year‑olds.
		ACTING CHAIRMAN GULICK:  Ms. Delph and then Dr. Deeks.
		DR. DELPH:  Dr. Delph.
		ACTING CHAIRMAN GULICK:  Dr. Delph.  Excuse me.
		DR. DELPH:  It doesn't matter.
		I think that it's important to look at the metabolic toxicity endpoints, including the cardiovascular metabolic CNS GI and toxicities.  But I would also like to make a point which doesn't quite fit into the endpoints, strictly speaking, but I think it probably best fits here.  And that is the importance of monitoring adherence and in designing these trials to ensure that there are interventions to improve adherence.
		Many of these patients are at this stage because of difficulties with adherence and staying on very complex regimens.  And I think that it is particularly important as one embarks on trials in heavily treatment‑experienced patients who have very limited options to ensure that good interventions are done at the beginning and during the trial to ensure that adherence is optimal.
		ACTING CHAIRMAN GULICK:  Thanks.
		Dr. Deeks?
		DR. DEEKS:  I just want to back up a little bit.  I think that the endpoint really is going to be determined by the goal of therapy.  I think the goal of therapy sort of varies depending again on the patient populations.
		Implicit in the entire discussion about the factorial design of wanting to combine two and three drugs at once is that, at least in that study, the specific therapy is complete viral suppression.  That's why we're obsessed about combining all of these new drugs together.
		So I think if that relatively early patient population with some options in which we're trying to combine two or three new agents, the reason for doing all of that is complete suppression and the endpoints should be the proportion undetectable.
		I do believe, however, that we are moving toward a different goal of therapy, particularly with the more heavily appreciated population, in which that really isn't an option.
		If that no longer is an option, then it's really delta viral load.  And if it's delta viral load, we don't have to worry so much about combining drugs anymore.  And that's part of why I was in support of the add‑on study design, at least for some patients.
		I think in that situation, ‑‑ Mike was talking about this earlier ‑‑ there is a very strong relationship between delta viral load and delta CD4 and that maintenance of at least a half log drop in viral load appears to be associated with the ability to maintain a CD4 count above a pre‑therapy baseline.  And I do believe that that is a very reasonable goal of therapy and, therefore, would be a very reasonable endpoint in that specific setting.
		I'm just going to take it to the next step.  If that is the goal of therapy and we're basically going for partial suppression, then I think what we need to know and what needs to be studied in clinical trials is not the baseline predictors of success but the treatment predictors of failure.
		Therein lies the need to study the evolution of resistance and relate the emergence of mutations to loss of antiviral effect.  And also involved in those types of studies would be a careful evaluation between the relationship between drug resistance and virus fitness and their impact on viral load and CD4 counts.
		ACTING CHAIRMAN GULICK:  Dr. Eron?
		DR. ERON:  I think one service the ACTG could do is to take the data from our three or four advanced studies, like 398, 359, 372B, and see what is the relationship in an individual between change in RNA and change in CD4 and see if what Steve says actually does hold up because my sense, anyway, was that in the nucleoside‑only era, they were kind of mirror images of each other.
		The RNA would go down.  The CD4 would go up.  And then the RNA would come up and the CD4 go down.  You didn't quite see as much of this discordance.  I don't know if that is true or false, but one could imagine if that were the case and with our triple combination or other regimens, where there actually seems to be more of a CD4 effect, that, actually, you get more clinical benefit from a smaller change in viral load potentially.  So it would be nice to know what that relationship is, and we certainly have a ton of data to figure that out.
		ACTING CHAIRMAN GULICK:  Doctor?
		DR. DEEKS:  Mike talked about this.  One concern, though, is in the study that you referred to, we don't have a good feeling of those patients' sort of off‑therapy set point because I think that's the delta viral load that's important.
		There's a chain in viral load from wherever that virus goes in the absence of therapy.  And with 359 and so forth, we might not actually have that since we have data going back to before 320.
		But that is the analysis that needs to happen, the relationship between the degree of viral suppression relative to what the viral load was long before therapy and how that impacts on CD4 changes.  I don't think that type of analysis ‑‑
		DR. ERON:  Certainly 320 would be the place to get that.  You wouldn't quite get it because many of the 320 patients were AZT‑experienced.  But it would be pretty close.
		ACTING CHAIRMAN GULICK:  Dr. Falloon?
		DR. FALLOON:  I would argue against the composite endpoint in part because I don't think we know how to define it.  If you go back to the original trials and you look at the CD4 elevations in AZT load or ddI, ‑‑ I mean, my memory is at 11 cells ‑‑ we're talking about something given the variance of the measure.
		To power those studies, I think we would have to have larger numbers.  We don't know how to do it, and it's also different across the spectrum of CD4 counts, a total number.
		If your CD4 count is 400, it is completely different in change than if it's 10, where you have to look at percent.  So all of those things would have to be taken into account.
		Now, perhaps the statisticians could think about it.  None of us is easily thinking of a composite measure that works.  And that makes me think we should simply go back to viral load.
		ACTING CHAIRMAN GULICK:  Okay.  Let me try to summarize here, then.  In considering what the best endpoints are, we once again touched on who the population is and once again recognized the heterogeneity.  Once again, the set point and the possible effects of washout of therapy and what the pre‑treatment therapy was are all important factors.
		I guess our overall goal in terms of endpoints is to pick agents which promote clinical, positive clinical, effects, but the feeling was that we go back to the old standbys.  These are antiretroviral agents.  And viral load levels become probably the most important, although not the exclusively important, endpoint.
		Whether our goal is complete virologic suppression for some patients, looking at the percent below detection, or partial virologic suppression, looking at a change in viral load ‑‑ and I guess the consensus was that a .4 to .5 log change over 8 weeks is about the minimum that people felt would be correlated with a positive clinical outcome.
		Other things that people mentioned:  an AUCMB approach to viral load change; time to failure; and then not forgetting other properties, virologic properties, like resistance and fitness.
		The relationship between the viral load and the CD4 is very intriguing to people, probably an independent predictive relationship, but what's the interaction of those two endpoints?  Not well‑defined right now.
		People pointed out that CD4 certainly has predictive value for sure and intermediate risk of clinical events and the well‑known discordance response data important to keep in mind.
		Other important endpoints that people mentioned, toxicity, adherence.  It wasn't voiced but quality of life endpoint is all important to think about in this population.
		There was some disagreement about the usefulness or the feasibility of using a composite endpoint of CD4 and viral load.  How do you define that?  People thought certainly looking at both was appropriate, whether you could really combine them, some differences of opinion.
		Using sequential endpoints was another novel concept that came up.  There was some voiced approval for trying to use continuous, rather than binary, outcome variables.
		Other interesting points that people made, most of our discussion has been about antiretrovirals, but certainly other types of agents may be used and other endpoints might be appropriate; for instance, immune‑based therapies.  Lastly, there was an interest in identifying predictors of failure, either at baseline or while people are on treatment.
		In our last minutes, let's consider the last question:  Please discuss the role of shorter‑term trials; that is, 16 weeks, in assessing safety and efficacy.  Importantly, please consider the needs to establish longer‑term safety.  So we have been focusing on activity endpoints.  And now we're shifting to time periods and safety endpoints.
		Dr. Pettinelli?
		DR. PETTINELLI:  It was mentioned earlier today that we should study drug in the condition in which it will be used in the clinic.  Hopefully that use will be longer than 16 or 24 weeks.  Why for access purposes, I understand that for accelerated approval, we might need to look at 24 weeks data.
		I think it's really a requirement, very important, that we continue to follow up with these patients over time, only up to 48 weeks.  By those same terms, if those patients have other options, how this particular regimen is going to influence the future options.
		So long‑term follow‑up, both in terms of efficacy and safety, for me is a very, very important part of the development of the new compound.
		ACTING CHAIRMAN GULICK:  Dr. Fletcher?
		DR. FLETCHER:  In terms of antiviral effect, I think a short period has already been talked about, 8 weeks to 16 weeks, certainly should be able to tell us whether a compound has the ability to reduce viral load.
		As Carla pointed out, we still may want to know and probably need to know longer‑term as well, but if the primary question is "Is this drug behaving as an antiretroviral?" then a short‑term assessment can answer that question.
		I think in terms of safety, the other issue that we have to look at in evaluating how far we have to go comes back to the issue of exposure if we're now using the drug in a manner in the heavily pretreated patient in which we don't use it in the naive; so, for example, in a boosted regimen, levels 10‑20‑fold higher than what is done, for example, in naive.
		You have I think an obligation to study that drug for probably a longer period of time for safety purposes than you might have studied it for use in naive patients simply because the drug exposure is so much different.
		The same issue could hold with the combinations.  If you're now using the drug with other agents that you would otherwise never use it with, again, this heavily pretreated group of patients, then, again, you may have a different length, a longer length, of time to assess safety than you would in a naive population.
		ACTING CHAIRMAN GULICK:  Dr. Mellors?
		DR. MELLORS:  You know, I think this is an incredibly difficult issue.  And it's a risk/benefit assessment.  If the situation is high‑risk for disease progression, then you're going to be satisfied with a lot shorter‑term safety data and make your decision largely based on virologic and immunologic effect.
		To get longer‑term good safety data, you have to maintain a comparison.  The longer you maintain the comparison, the longer you delay the completion of the trial and approval.  So I think that it is a very difficult tension between safety and efficacy.
		I see it as when we're dealing with an advanced population with limited treatment options, if we're dealing with those who are near clinical events and we're trying to have an impact on that group, we may sacrifice the duration of safety observations to allow access to the drug.  If we're dealing with a group that is less at risk for clinical events, then we can maintain the comparisons longer and get better safety.
		Again, it depends on what the drug is being developed for.  If it is being developed for heavily treatment‑experienced patients, for that group, I'm willing to compromise the duration of safety assessment and accelerate approval, recognizing that when I do that, I take a risk at not fully defining the long‑term safety trial.  But I'm more willing to do that in that situation.
		ACTING CHAIRMAN GULICK:  Dr. Fletcher, a follow‑up; and then Ms. Dee.
		DR. FLETCHER:  I don't disagree, John, and I think we can go back to what the agency has talked about in terms of accelerated approval and the tools that they have to grant a drug an early accelerated approval but require additional studies.
		So certainly if you have an agent that looks fantastic for use in the heavily pretreated patients and good evidence of an antiviral effect in safety at 16, 20, or 24 weeks, an accelerated approval could be very appropriate, but it could be a wonderful setting in for requirements for longer‑term evaluations as well.
		So I don't disagree with you.  I in my comments didn't mean to imply at all it had to all come together, but I think it probably all does need to be done.
		ACTING CHAIRMAN GULICK:  Ms. Dee?
		MS. DEE:  Yes, thanks.  My concern here is that we have a problem now in that we have 24‑week and 48‑week data as far as long‑term safety is concerned.  If we approve drugs now at 16 weeks, then they're off‑label uses of these drugs.  So you will have other people besides the deep salvage patients using these drugs.
		You know, if I felt like or if I were sure, I guess, that some of these other studies would get done or that we would get long‑term safety data, eventually somehow I think I would feel much more comfortable in saying, "Well, maybe 16 weeks is okay, even if patients that are not deep salvage patients would try this."
		We're talking about this tension all day long.  I think we have to be realistic that once a drug is approved, it's approved.  How do we make sure this other stuff gets done?
		ACTING CHAIRMAN GULICK:  Dr. Delph?
		DR. DELPH:  I want to reiterate what Lynda was saying.  She did make some of the points that I wanted to make, but, in addition, I think we can do interim analyses for efficacy at 16 weeks.  But I don't think we should be looking at approving drugs at 16‑week safety data.
		If the objective is to get patients who have few options available to them to be able to get access to these drugs as early as possible, then the answer is to open up expanded access earlier.  These are patients who are willing to take a risk but who should not be required to enter trials simply to get drug.
		I share in this concern very much about approving drugs before getting at least 24 weeks data for accelerated approval and 48 for standard approval because of the possibility of off‑label use.
		The difficulty is that once the cat is out of the bag, the drug can be used in a variety of ways for which it is not intended or there is not adequate data.  And, secondly, the record on being able to get adequate safety data once approval has occurred is dismal.
		ACTING CHAIRMAN GULICK:  Dr. Saag?
		DR. SAAG:  I think those are points that are well‑made.  My struggle is that I'm not sure that 24 weeks is that much better than 16 or 48 is much better than 24.
		I mean, most of the problems that we have encountered in the longer‑term, a 48‑week study wouldn't have predicted.  It was really two and three years into it that we started noticing fat redistribution and diabetes and things.  So I think we're sort of beating ourselves up in a way that maybe isn't going to solve the problem.  That's on one side.
		On the other side, I mean, again, I don't know how different my population is, but I'm looking every day at people who have run out of options.  If there is a new drug in a new class or a new drug in an old class that has new, unique activity, expanded access is okay, but there's a cost that goes with that that's hidden.
		That's a hidden cost to the site, where we processed 100, for efavirenz, we processed 100, applications and had to renew them monthly.  That took an enormous amount of effort.  So there is cost on the other end, too, to the site.  We don't get reimbursed for that.  We have to hire new people to do that.  And it's a loss to us.  We do it for the sake of helping the patients.
		So I think what we're saying here is that we would like to provide the access.  The question is, the concern is, that if we provide it, quote, "too early," that we don't hold industry accountable to an obligation.  So let's get it out early and find another way of holding accountability for getting the data.  That's what I think we should do.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi and then Dr. Fletcher.
		DR. DeMASI:  I just wanted to bring up a couple of points with respect to this and based on the comments made this morning about the complexity of the populations we're dealing with, the drugs involved, the difficulty in demonstrating safety and activity and efficacy in this population, that there needs to be I think a flexibility in terms of the packages and approaches to drug development in this setting and that it's not a one size fits all, it's not a 16 and a 48 or a 24 and a 48‑week type of submission.
		I would just offer for discussion the possibility of a particular week, 16, efficacy and safety type of submission for accelerated approval and then following that up with some other interim time point before week 48 in terms of more traditional approval to generate additional safety data.
		ACTING CHAIRMAN GULICK:  I'm sorry.  Dr. Delph, did you have a direct response to Dr. Saag?  Okay.
		DR. DELPH:  I really don't like to respond to people in their absence, but I'll do it.  I think that certainly I take his point about the fact that the toxicities that we noticed, the major toxicities, lipodystric enzyme, came on much later than 24‑48 weeks.  So we noticed them much later.  But moving from 24 to 16 weeks is decreasing that time by a third.
		I understand the cost that occurs with trial sites in terms of having to process all of these papers.  We have been trying to work with companies to move that from every month to every three months and so on.  But I think that that kind of financial and administrative cost is far less of a price to pay than that of patient safety.  That's one.
		Two, I think that we need to do it the other way around, that companies need to demonstrate that they are prepared to provide that long‑term safety data and that data that extends beyond 48 weeks before we'll turn around and say, "Fine.  We'll approve drugs at 16 weeks."
		I don't think we should be saying "Let's approve drugs at 16 weeks" in the hope that they will be providing that data long‑term.  I think they need to demonstrate that that is something that they are committed to doing.
		ACTING CHAIRMAN GULICK:  Dr. Fletcher and then Mr. Levin.
		DR. FLETCHER:  Mike Saag really ended up on the expanded access where I was, that you have that balance you have to struggle with between a drug that looks very promising that you want to get out to individual that can't access clinical trials.
		But at the same side, an expanded access is not a substitute for an unambiguous answer in terms of whether this drug has antiviral activity and is safe.  So it is that balance that I think has to be kept in mind.
		I agree with the comment about obtaining clear commitments for longer‑term safety evaluations of these compounds when they are approved on a more accelerated schedule.
		ACTING CHAIRMAN GULICK:  Mr. Levin?
		MR. LEVIN:  I agree with Yvette and Lynda.  I am all for 16 weeks.  That's okay.  The FDA and the community and the researchers are sitting here at the table today.  Where is the industry?
		I need a commitment from the industry that they will do the follow‑up.  That's why I mentioned I think the important ‑‑ how I feel it's important to set up maybe a cross‑salvage or experienced person studied across all studies, some sort of a database to collect information and to continue collecting information across all of these studies over a period of time.
		I don't think one year is enough.  It takes two years for lipodystrophy.  What about again, for the third time, hepatotoxicity?  Why can't we make it?  I don't know what the law is, but why can't we speak to the industry to make a commitment on this, and it's a deal?
		ACTING CHAIRMAN GULICK:  Dr. DeMasi?
		DR. DeMASI:  Yes.  Just with respect to some of the time points for the particular analyses, 16, 32, 48 weeks, I think because of the staggering enrollment of the studies that you do have additional data beyond those time points that is included or should be included in the analyses that would, for example, support a week 16 submission or submission based on week 16 data or week 24, whatever the time point is.
		Because of the staggering enrollment, we do have patients that are out to 48 weeks, that are out to 72 weeks, 2 years.  And that data I agree should be presented as part of the package and data continue to be collected.
		ACTING CHAIRMAN GULICK:  Dr. Schapiro?
		DR. SCHAPIRO:  I would agree with what Mike and Corny were saying regarding you really have to be able to get the drug out quickly.  We're saying that.
		We really can't sort of tell the agency, on the one hand, these patients need these drugs desperately and then say "But we require two years of safety."  It doesn't work both ways.
		I also think that technically expanded access is good, but to make that the general policy of how we're going to approve all of these agents, I don't think it will work when we try to implement it.  Although it's a good idea, it will be very difficult to do that large‑scale.
		I think what Jules was saying is true, but I think we can probably help industry with some guidance how that has to be done.  The concepts earlier today were brought up of a database.  I think they're realistic.
		I think John made a good point that you can't just follow patients.  There has to be a comparator.  I think we can probably ‑‑ it's probably beyond the scope of this meeting, but we could come up with some ideas how that could be done.
		Patients who are on these drugs can be entered and followed in some way and a comparator group can be found of comparable patients who are not getting the drug.
		There can be a committee, and this could be the financial burden of the sponsor.  But I think as far as running this, it could be done also by the community, academia, under the guidance of the agency.  And then we wouldn't do a final 48‑week.  This would be an ongoing process for drugs that are approved.
		We accept that due to this patient population, they're going to get out early.  But we would set up a mechanism by which these patients receiving the drug are followed for toxicity.  We probably couldn't do it at every time point, but we have large databases that are setting up.
		The idea is we have databases for resistance.  We have some very large databases which have given us wonderful information.  We can do something similar here with a comparator group and to continue to look.  I think, as Mike said earlier, there's nothing magical about week 48.  We would probably have to look beyond that as well.
		ACTING CHAIRMAN GULICK:  Dr. Jolson?
		DR. JOLSON:  I would concur with many of the previous speakers.  I think we're becoming increasingly aware of the importance of longer‑term data.  We have been trying to reflect that data and package labeling as an incentive to sponsors to continue to collect data beyond the one‑year mark or a year and a half‑mark and trying to include as much of that information as possible because we think it's extremely important.
		I think we would also agree that there need to be more collective efforts in terms of how we're going to approach that and collect the data and follow patients long term.  It's not an easy thing to do.
		In terms of how much safety data would we need to approve a new drug, I would have to share some of the sentiments that the community raised that I would be concerned about not having at least some cohort of patient out beyond 16 weeks in terms of predicting the safety.
		You know, when you work at FDA, the pendulum in public sentiment swings back and forth in terms of how quickly drugs should be approved.  When we have in our mind a drug that is very, very effective, it's impossible not to say, "Well, let's get it out as quickly as possible."
		But you have recently lived through as an agency experiences where drugs are marketed and then there is some sort of adverse event that happens, it is very hard to justify it in hindsight.  It is particularly harder to justify it if the databases isn't as robust as would have been necessary.
		Data.  There is always some risk there, but I think it would be enormously difficult to conceive of a situation where we wouldn't want some data beyond 16 weeks.  It doesn't have to be in the same group of patients as in the Phase III studies.  And my message to industry would be to strongly encourage following your patients from earlier studies as long as possible.
		If you look at, again, the Kaletra label, you will see longer‑term data reflected from studies that were started earlier in development.  It was enormously useful.  And it is a time saver.  It's the sort of data that would enable us to make decisions based on shorter‑term efficacy data.
		ACTING CHAIRMAN GULICK:  Ms. Dee?
		MS. DEE:  You know, the expanded access programs are to give people access to the drugs, not to approve the drugs.  I'm not sure why we would mix that up.
		You have the expanded access program to give people access to it while you're studying it to find out if it really does do what you hope it does and to see the toxicities, which you could see with controlled trials and the other, and the expanded access program.
		But I'm from Missouri.  It's funny.  Yvette just commented that the patients' representatives are saying that we want more restrictions, and the doctors are saying, "Let's get it out there."
		We want to first do no harm.  I mean, let's see from industry how they're going to address these situations before we open the floodgates again to say, "Okay.  Let's approve a drug at 16 weeks and hope that something will happen past 48 weeks, when there's no statutory authority to make that happen."
		So I don't know if anybody from industry wants to comment on that about how we might be able to ‑‑ what their plans are for that in the future, but us saying that, "Yeah, they should do that" is just not enough for me or them saying they're just going to do that without some firm plans, demonstration, or some sort of demonstrative evidence.
		ACTING CHAIRMAN GULICK:  Dr. DeMasi?
		DR. DeMASI:  Yes.  I think just to clarify, in the discussion, the mention of the week 16 analysis, I believe what we're talking about is:  What is the duration of a particular interim analysis of an ongoing study that could be used as a basis for an accelerated approval filing, particularly for efficacy data?
		And that's not to say that no other data would be collected beyond 16 weeks, but that defines I think what is sufficient for a submission and that we do support the collection of data, as mentioned before, in that study, additional follow‑up data to a later time point as well as additional follow‑up, for example, of earlier Phase II studies, in which you do have patients out to week 48, 72, and 96, as was mentioned in the Kaletra label.
		ACTING CHAIRMAN GULICK:  Okay.  I think I would like to stop us there.  Just to summarize, I think we began consideration of safety endpoints much the way we began the consideration of all of the other questions.  That was to consider the specific patient population.
		As was pointed out, higher doses may be used in this population or PK enhancement.  Therefore, exposures to drugs may be higher in this population than naive patients.  We also pointed out that concomitant medications are likely to be many more used in this patient population.
		It was pointed out that we might be much more tolerable of risk in this population and accept greater toxicity and/or shorter follow‑up data.  However, there was a general feeling that a significant amount of safety information should be in place.
		There was some debate about the actual number of weeks, but it was really stressed that we needed a commitment from the sponsors to have longer‑term follow‑up of safety endpoints.
		There were some novel suggestions once again, that long‑term cohort studies or database‑type data may be helpful in looking at longer terms.
		Then, once again, we really identified the conflict of access to agents that may show viral activity versus safety and how do you resolve that conflict, not something we did today.
		Lastly, importantly, pointed out by the agency that safety data can come from other places.  Other studies of the same drugs can often provide safety data that can help support this, too.
		With that, I would like to thank the presenters for today.  I would like to thank the Committee themselves for an extremely lively conversation, thank members of the agency and members of the audience.  Thanks very much.  We will close.
		(Whereupon, the foregoing matter was concluded at 5:30 p.m.)