UNITED STATES OF AMERICA

P-R-O-C-E-E-D-I-N-G-S

(8:32 a.m.)

CHAIR BOEHLERT: Good morning. It's 8:30. I call this meeting to order and welcome members of the committee and all other participants that are going to be presenting in this two-day session. We have an interesting program, updates on a lot of topics we've addressed in the past. One that I'm particularly interested in is finally hearing, you know, some discussion on Bayesian statistics. We've touched on it many times in our discussions, so Nozer, I'm looking forward to that. You finally get your chance.

DR. SINGPURWALLA: You'll be tested.

CHAIR BOEHLERT: That's what I was afraid of. It's not a topic that's in my area of expertise but I expect to learn a lot today. With that, I'd like to turn the meeting over to Hilda for the conflict of interest statement.

MS. SCHAREN: The following announcement addresses the issue of conflict of interest with respect to this meeting and is made a part of the record to preclude even the appearance of such at this meeting. Based on the agenda, it has been determined that the topics of today's meetings are issues of broad applicability and there are no products being approved at this meeting. Unlike issues before a committee in which a particular product it discussed, issues of broader applicability involve many industrial sponsors and academic institutions. All special government employees have been screened for their financial interest as they may apply to the general topics at hand. To determine if any conflict of interest existed, the agency has reviewed the agenda and all relevant financial interests have been reported by the meeting participants.

The Food and Drug Administration has granted general matters waivers to the special government employees participating in this meeting who meet prior waiver under Title 18 United States Code, Section 208. A copy of the waiver statements may be obtained by submitting a written request to the Agency's Freedom of Information Office, Room 12-A-30 of the Parklawn Building. Because general topics impact so many entities, it is not prudent to recite all potential conflicts of interest as they apply to each member and consultant and guest speaker.

FDA acknowledges that there may be potential conflicts of interest but because of the general nature of the discussion before the meeting, these potential conflicts are mitigated. With respect to FDA's invited industry representatives, we would like to disclose that Gerald Migliaccio is participating in this meeting as an industry representative acting on behalf of regulated industry. Mr. Migliaccio is employed by Pfizer.

Dr. Paul Fackler is participating in this meeting as an acting industry representative. Dr. Fackler is employed by Teva Pharmaceuticals. In the event that the discussions involve any other products or firms not already on the agenda for which FDA participants have a financial interest, the participant's 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 product they may wish to comment upon. Thank you.

CHAIR BOEHLERT: Thank you, Hilda. To get the meeting started, Ajaz -- if I turn on the mike and you can actually hear me. To get the meeting started, Ajaz will provide an introduction.

DR. HUSSAIN: Good morning, and welcome to Rockville. The Manufacturing Subcommittee for the Advisory Committee for Pharmaceutical Science, I think this is the third meeting after the key subcommittee ended and we have discussed many of the developments with this committee and we'd like to sort of use this meeting to bring forward the concepts that have been developed and the challenges that we are overcoming in trying to implement some of the concepts and seek your input in a number of questions that have been posed to you.

Just to recapitulate, at the Advisory Committee of Pharmaceutical Science in 2001 July, we had used the CGNP initiative and that was the starting point for discussion on manufacturing in a very focused manner that led to the CGNP initiative for the 21st Century and later on we have two other initiatives defined, one on molecular innovation and one on critical path. In some ways I look at all these initiatives as a desire to define a desired state which more efficient, which is more effective in meeting the needs of the customer, that's a patient and so forth. So the desired state that FDA is trying to articulate in a shared manner for the US patient is in many ways very forward and I'll focus many on manufacturing with regards to manufacturing and utilize the six dimensions of our pharmaceutical quality for the 21st Century Initiative as a means to share with you how this meeting agenda was organized.

Although we called our initiative CGNP for the 21st Century, we realized that is was probably a mistake to just call it the CGNP initiative, because it is an initiative which is dealing with all aspects of pharmaceutical quality. It applies to CMC Review Process as well as the CGNP inspection. So often we refer to that as the Pharmaceutical Quality for the 21st Century initiative instead of just CGNP Initiative.

The six dimensions for this initiative are foremost, strong public health protection. We want to maintain that and strengthen that function of FDA. We want to bring an integrated quality systems orientation to our activities and our programs that could simply mean better communication between different organizations within the agencies, the industry and so forth but also a more systematic approach to pharmaceutical quality and more integration and collaboration between different parts of the organizations that deal in pharmaceutical quality.

Science based policies and standards, risk based orientation and international cooperation. Those are the five pillars of this initiative. The sixth dimension is time and the time we decided was for two years. We will work on this initiative trying to define the desired state, trying to define the issues to be addressed in the two years. The two years time comes to an end next month, but that doesn't mean the initiative ends. It means that you would now move into a regular routine of trying to implement all these activities.

And in September we hope to announce how this process will become a more permanent model within the agency. So the initiative was for two years to define the issues to be addressed and identify issues to be addressed and come up with a way to address those but that doesn't mean that we will have completed all the objectives.

If you look at what we have been engaged in, I call those directional vectors, we would like to insure regular review and inspection policies based on state of the art pharmaceutical science and create new technological advances and create risk based approaches that focus both industry and agency attention on critical areas, facilitate modern quality management techniques, including implementation of quality systems from within the agency as well as outside the agency and industry, and have the consistency and coordination of FDA's quality review programs, in part by integrating enhanced systems approaches into the agency's business processes and regulatory policies concerning review and inspection activities.

If you look at how we are covering these topics, we can visualize this as a three-dimensional aspect, science, risk and system integration concepts, we started with the PAT initiative. We have a draft guidance. That guidance will be finalized in the next month or so. We took some of these concepts to ICH and now we have a number of topics in ICH and that will be a subject for discussion this morning. We wanted to move to a more flexible approach to post-approval changes and move it from change being bad to change being viewed as an improvement, and we struggled with delegating a compatibility protocol that would be user friendly, useful in many ways.

And we're still struggling with that and I think that tomorrow you'll hear some aspects of the struggle with that protocol. Aseptic processing I think is an important guidance that will be finalized soon. Guidance on CFR Part 11, probably this is one of the major accomplishments of this initiative is to address some of the challenges of Part 11, better integration to collaboration and cooperation between inspection and review staff, products specialists and inspection, the PAT model is evolving and this is working nicely and we're trying to expand that beyond the PAT model.

Pharmaceutical inspectorate is another major accomplishment. Over the next several years we will have a core group of pharmaceutical inspectorate staff, in ORA who will spend most of their time or 80 percent of their time inspecting pharmaceutical plants and they will have a high level of training and certification to accomplish that.

Dispute resolution process is also a major aspect of this because in a large system such as our regulatory system, when you start moving towards a different approach for dealing with regulatory aspects, you have to have an efficient dispute resolution process. And clearly pre-approval inspection compliance program was one of those but you will hear tomorrow from David Horowitz and Larry and others a risk based approach to inspection, site selection, where do we inspect, where do we put our resources where the risks are and so forth. So these are some of the activities that sort of cover risk science and system integration approaches that we outlined for us.

But quickly, I'd like to summarize why we felt the time was right to move forward here. There was the scientific opportunity. And this was a sensitive document to sort of bring up and simply stated that pharmaceutical development and manufacturing is evolving from an art form that is now based on science and engineering based. Effectively using this model in regulatory decisions when we establish specifications and we evaluate manufacturing processes can substantially improve that efficiency of manufacturing regular processes. That was the initial hypothesis that we started as a basis in 2001 and hopefully you'll see that some of the activities that will be discussed at this meeting we can move forward and put a conceptual framework around them.

The other dimension was the risk and the risk mitigation and communication opportunity was clearly an opportunity because there are many risk approaches, risk mitigation approaches which have matured, have been utilized within the agency and outside the agency. For example, within the agency, on the food side there is more effective analysis on the devices side have been utilized for a number of years and other industries have utilized some of these. And we sort of brought the concept up and done some designs by quality, by design, again a phrase which is a very old phrase but brought a dimension to this to focus on reliability and risk mitigation and hopefully we can communicate this better, we can find leverages for reducing regulatory but the third dimension of opportunity was the quality systems opportunity. Again, if you look at the evolution of quality, you start with sampling plans, and so forth and GNPs came in there and many of the quality systems are based on other GNPs and what we are hoping to do is to sort of in a jargon free way, adopt the practices in all of these quality systems into our system and we are moving towards a general quality system framework for the agency and hopefully support that for external industry also.

So for the two-year journey, which is coming to an end next month, from the perspective of defining the issues and defining the training and conceptual framework, to what is the destination. I often use this slide, the book by John Guaspari, "I know it when I see it", is to me an excellent reflection of the current state. I often say the person in that picture is our CMC reviewer because they often do not have information that they need to make the decisions with respect to risk and so forth. So often the answer is, if you want to change the site of manufacture, I need three batches of separate data. The only decision they can make is when they see the three batches of separate data. So we can move away from that to a vision 20/20, I can see clearly now, which is part of the desired state. And we define the desired state as follows.

The part quality and performance is achieved by design of effective and efficient manufacturing processes. Correct specifications based on mechanistic understanding of how formulation and process practicing factor on performance, again, that's missing from the current state. We don't have this information in the submissions. And move towards a continuous assurance of quality. The primary motivation for the third bullet was you achieve that only if you gain a high level of process understanding. You cannot achieve that without that and when you achieve that, that brings a more efficiency continuous manufacturing and so forth.

But to facilitate that, our policies, that is regulatory policies need to be tailored to recognize the level of scientific knowledge supporting applications, process qualification and process capability, and we started emphasizing the process capability because product are validated but many are not capable, so there is a missing element. Validation does not insure capability but shows a missing link. So risk base review relates to the level of scientific understanding of how formulation and manufacturing process effect product quality and performance and the capability of process strategies to prevent unmitigated risk of producing a poor quality product. So that was our way of saying, we can facilitate moving toward a desired state by providing regulatory incentives.

So this meeting -- the primary objective of this meeting is to seek input and advice from you and from the public on charting the most efficient part of the desired state and the discussion focuses on review assessment of chemistry, manufacturing and control sections of submissions and I deliberately I sort of wrote the CMC as its written in our regulation, chemistry, manufacturing, and controls. The reason for stating it that way, that's as it's written in our CFR, is we often focus only on the chemistry, the manufacturing controls part is -- doesn't get the attention it deserves. And that is an opportunity, I think, that Q8 and Q9 sort of bring forward.

Risk-based procedure inspections, you will hear a pilot program on selection of manufacturing site inspections. There are elements of risk which says if a process is well, well controlled, there is a way to reduce the risk for those sites and so forth. So you'll hear the discussion tomorrow. You will also hear updates on a number of topics but I just wanted sort of put up the Q8. What do we wish to accomplish with Q8?

As an example, we hope that Q8 will facilitate movement towards the desired state that we have articulated. We believe this is important because this will help us better understand the proposed product and process design and its relation to independent review. Improved process of establishing regulatory specifications, this is the heart of the key here. This is the voice of the customer. FDA is the customer defining the voice, making sure the quality is there because the GNPs then have posted so if you don't get the specifications right, the problems linger on.

And four, we could identify and understand critical product and process practice, again, this is not well understood today in the part of the type of information we've seen in the submissions. Allow us to do a risk-based approaches and recognize good science and facilitate improvement, improve communication and system thinking and be a advocate for public health, regular and industry.

I'll skip this. John Berridge graciously agreed to come and talk to you about how we are approaching Q8, but there is a question that we have posed to you and this is the reason I'm showing this slide. One of the concept that has evolved in a harmonized way to move forward is the concept of continuous improvement and the concept for design space. And this is a part of the question that I think, we have asked you to address. The key factor here or key concept here is that if you have understood the critical formulation basis, the critical process basis and you have charted your design space, within that design space movement is not a change any more and I think that's an important point.

So how do we define this design space is a key element. It is a multi-dimensional space that will be defined by critical vector of product in performance. One of the examples of such critical vectors, vectors that define robust manufacturing processes, consistent ability of meeting its specifications, different manufacturing options. Here is a graphical presentation of what this design space might be. Currently, much of this is a black box, especially with respect to raw material properties, processing conditions, and so forth. So we have very limited information about what are the critical factors and so forth.

We hope the future will be sharing of pharmaceutical knowledge and that shows us where things are critical and not critical and therefore, be more rational in moving through different things and improving model. We are very confident that many companies already have this information. We have met with several companies. They've come and met with us, shared with us this information and we believe it's already there. So for many companies this is not any additional work. It is simply sharing this information at the right time, in the right way, and for us to move forward.

So in many ways you'll see the discussion. We're hoping Q8 brings a level of understanding which is not there today and the key aspect here is the company has its own quality system. We have post-approval changes and the current system says changes is bad because it's uncertain or risky. We don't know what that change might be, that if fact, if that is true, additional testing. Yet you have the CMC regulatory oversight, you have the CGNP regulatory oversight, you have a perceived or real risk out there and all of our activities are focused addressing all of this and aligning this in such a way that we move forward to serve the patients in a more efficient manner.

The process of understanding, you align all of this together, you have an opportunity that would say post-approval changes is not bad, it's actually good, it's a continuous improvement and that leads to significant risk reduction on a continuous basis. So that's what you're going to accomplish and I see it Q8, Q9 and the proposed Q10 are graphically in my mind, going together this way and you will hear presentations on this. So the meeting today in many ways, I look at that as moving towards a desired state. We seek your input on how best to do this. Day one, you will hear updates on our current efforts on ICH Q8, Q9 and the proposed Q10. We are moving forward with ASTM in a significant way, especially for the PAT standards and in aspects, which I think ASTM is a paradigm shift because we believe that to do it right, you have to bring this standards and the umbrella of understanding.

For example, if you have a chapter in the USP that lacks the process understanding dimension, so that's a live base mentality to those standards. Those standards are not yet useful as when they are within the framework of understanding. So the ASTM model is a basis for moving forward in that direction. I think the awareness topic that we are introducing today is to fill some of the gaps that we think exist even in spite of all the work that we have done and some research planning. Bayesian approaches in chemistry manufacturing control, I think is a significant topic. It's a topic that has been discussed recently at an FDA John Hopkins University co-sponsored workshop but more on the clinical side. We would like to start the discussion on how we can bring some of these concepts to bear on CMC decisions. Professor Nozer is an expert on reliability, Bayesian approaches and so forth, so we requested him to give us a talk. This is simply an awareness topic at this point but I think you want to build on this. There a critical path initiative that we talked to you about but then we move on to some more significant discussion. It's how do we start moving toward implementing the concepts that we have developed in the Office of New Drug Chemistry and Office of Generic Drugs.

Moheb Nasr and Gary Buehler can share some of the parts. Our focus mainly has been on Office of New Drug Chemistry right now to bring all of these concepts to bear over time of the Office of Generic Drugs and all of these offices we have will come together in this. But it's going to take some time. But to set the stage for this discussion, what we have is two introductory lectures or presentations. One on the manufacturing science and knowledge. G.K. Raju will do that, and to share some thoughts on quality of design and setting specifications. Then we'll have Moheb Nasr and Gary Buehler share some of their thoughts and then we have invited Ken Morris. Ken Morris has been working with our CMC leadership at the agency in moving towards the question of the CMC review process and we asked him to share some of his thoughts with you after Moheb and Gary have shared their thoughts.

Day two will focus on risk based CGNP inspections. You will hear about the study being conducted on industrial practices. Then we'll have a significant discussion on pilot model or selection of manufacturing sites for inspection, how do we identify the risk factors but also I think an important topic which is -- will be a substantial topic, Joe and Moheb will talk about this, CGNPs production IMBs. I think this is going to be a significant topic but mostly a wellness topic. Then I think we'll sort of wrap up this discussion is trying to sort of identify some of the challenges that remain and some of the things that are working well as well as some fascinating continuous improvements and reduction in the need for product food supplements. They use the PAT as an example of how we are bringing the review and inspection people together, the staff together, to make decisions without having to have supplements, compare the quality topic that we discussed and John will also discuss some of his parts on this but they're challenges because some of the concepts are within the old system and some of the concepts are happening with the new system.

So with that, sort of that's a broad discussion on the meeting. What we have tried to do is to share with you or ask you some questions. For example, you agree that current activities within ICH and the ASTM has been to move toward the desired state. We also seek your recommendation on how to insure these activities are synergistic and simply on risk basis recommendation in the new paradigm. We have a number of questions. The flexibility for you to address your discussion around these question will help. I'm not sure whether the committee would like to come together to sort of address this in brief summary if they could but the topics that we have for day one, the questions apply to all the topics, so towards the end if you could summarize some of the parts, that would be very useful for us. And you already have this, I won't spend more time on that, with that I'll give it back to you.

CHAIR BOEHLERT: Thank you, Ajaz. Is there comments or questions from committee members?

Okay, before we go on with the next speaker, there's one thing I neglected this morning and that's to have our committee members introduce themselves. I think this is important for the benefit of committee members who may be new. So we'll start with Dr. Fackler, introduce yourself and your affiliation, please.

DR. FACKLER: Paul Fackler with Teva Pharmaceuticals, representing the generic drug industry.

MR. MIGLIACCIO: Gerry Migliaccio, with Pfizer representing PhRMA.

DR. SINGPURWALLA: Nozer Singpurwalla, George Washington University.

MR. PHILLIPS: Joe Phillips, Regulatory Affairs Advisor, International Society of Pharmaceutical Engineers.

DR. RAJU: G.K. Raju, MIT Pharmaceutical Manufacturing Industry.

DR. DeLUCA: Pat DeLuca, University of Kentucky.

DR. MORRIS: Ken Morris, Purdue University.

CHAIR BOEHLERT: Judy Boehlert, Consultant to the Pharmaceutical Industry.

MS. SCHAREN: Hilda Scharen, FDA.

DR. PECK: Garnet Peck, Purdue University.

DR. GOLD: I'm Dan Gold, D.H. Gold Associates.

DR. HUSSAIN: Ajaz Hussain, Deputy Director Office of Pharmaceutical Science, CDER.

MS. WINKLE: Helen Winkle, Director, Office Pharmaceutical Science, CDER.

CHAIR BOEHLERT: Okay, thank you, everyone. Our next speaker is going to discuss ICH Q8. Ajax has introduced us to these topics, and John Berridge, Dr. John Berridge, will make the presentation.

DR. BERRIDGE: Thank you, Judy. Good morning, ladies and gentlemen and thank you for the opportunity to present to you today on the topic of Q8, Pharmaceutical Development on behalf of the expert working group and some additional thoughts, of course. What I would like to do today is to give you a little bit of background to the topic and address the opportunity for change. Look too, at the progress that we've made so far and then to round off by considering some of the implications, implications for the future as a consequence of this guideline.

So at the very highest level, the purpose of the ICH Q8 topic is simply to provide guidance, that is harmonized guidance, on the section P.2 which is entitled "Policy for Development" of the comment technical document format. And its scope is very clearly outlined in the concept paper and it is all the products that are pertinent to the CTD. Of course the CTD is not mandated in the US but I think it's true to say that the majority of applications for new entities are actually using the CTD format today.

So that's the very highest purpose but I think it's pertinent to actually look deeper, look underneath and to say what are actually the drivers, why would we really want to do this? So if we go back and think about life as it is now, life before we actually get to the Q8 state. In the United States the amount of information that industry submits in its NDAs is variable partly because some of that information may have been submitted through the IND process. Some companies go to a different extreme and actually submit the report that they would present in Europe.

Others, the information is distributed around the new drug application in various places, but even so, there is variable information that is presented and part of is driven by industry concerns. If we provide a lot of information, we get a lot of questions. So there is sometimes reluctance to provide information that would give a full understanding. It's slightly different in Europe where there is the -- there has been traditionally and still is the development of pharmaceutics concept which describes how formulations are designed and the manufacturing process is put together all in one sanction and the home for that in the CTD is P.2.

Japan, there are very limited expectations. So we can see that there is a varying degree of expectation and a varying degree of implementation around the world. Is there anything wrong with that? Well, I think there is because right now there's a lot of focus in an NDA on the future regulatory commitments, a reluctance to describe how the product was truly designed. When you put those things together with the worry about the future and the regulatory commitments, it creates what are called a "check-list" mentality. E go around providing and reviewing submissions in a ticking the box process. Where a development report is written it tends to focus on successful preapproval inspection.

And the other major driver, I think, is we've heard in the earlier presentation from Ajaz a desire for international cooperation. So we have disharmony. There is a P.2 section in the CTD but we don't have any guidance on exactly what we would put there. When we look at the regional implications where development of pharmaceuticals is the cornerstone of the European submission, I think there is some missed opportunities. And this all tends to result in the very limited regulator incentive to truly understand how products and processes to describe that understanding and then to move into a process of their optimization.

Q8 brings with it an opportunity for a significant change, a change that moves us from simply providing huge amounts of data and what happens when you get huge amounts of data? It tends to get checked and boxes get ticked or they don't get ticked because there's a mistake. So let's move from that, move from these huge boxes of data to a situation of information and knowledge. And we can express that in a different way which is basically a manufacturing sciences based approach to submission and approval.

And if we agree to that, then we see the creation of a significant new paradigm. It's a new paradigm for both parties. It's a new paradigm for industry and a new paradigm for the regulators and a significant set of positive opportunities. You've seen this slide almost. The first two points are as age asset. Some people discuss the word "mechanistic". We could substitute the word "scientific", but we're certainly talking about a true understanding of our products and processes. And we're trying, through Q8, with the full support of the expert working group, to get to that state which allows us to effect continuous improvement and opens the door to continuous real time quality assurance.

So if we look at the guideline itself and the mechanics, the processes underlying the development of the guideline, the topic was actually adopted back in October 2003 and the expert working group has met three times since then, have produced at the meeting in Washington just a few weeks ago, a third version of the guideline. This is under consideration by the experts themselves with input from their various associations, but we're aiming to get the document out for public consultation, this is ICH Spec 2, after our November 2004 expert working group meeting in Yokohama, in Japan.

I think we're cautiously optimistic that that timeline will be met. Q8 itself is a guideline that's being conceived in two parts. Part 1, the core document, describes baseline expectations and optional information. I'll come onto this a little bit more in a moment but describes a concept of regulatory flexibility. Again, I will discuss that a little more in just a moment. And as I've indicated, we hope to get to Step 2 later this year.

The second part, which has not been started yet and which is still subject to discussion, relates to annexes of specific dosage forms and the possibility to include in it appropriate examples of risk management. And in that sense, the Q9 guideline that provides a toolbox of risk management examples, provides useful input into the QA guideline. I think we can stick to our intended time line. Then we should be able to start back in November of this year.

So I've talked about baseline, other expectations, and it is clear in the guideline that not all the information is mandatory. But the guideline is carefully constructed to insure that this doesn't create any misunderstanding. What it does is describe one system with different levels of focus. And there's a complex phrase here "process understanding and predictive ability" that actually is intended to describe this continuum, not a two state system but a continuum. What we mean is that the more that the process is described and understood, the more one provides for the future regulatory flexibility.

The less you give, the more rigid the subsequent approach is. And so it doesn't actually describe a mandated content, it describes an opportunity. So if we look at that in the context of quality by design, which has also been mentioned as a concept today, we're looking at on the left-hand side, understanding that we have a well-characterized product. We understand the process. We've looked at the risk, and taken appropriate mitigating actions and we understand how we're going to monitor our process in the future.

If we put those four components together, it drives the framework for continuous improvement. In fact, you can put together the sum, if you like, the product and process knowledge together with appropriate risk management and that can comprise the manufacturing sciences. Well, if we drive towards that framework of continuous improvement with the knowledge as indicated, on top of that, so I should say that the first three are part of the Q8 topic, so the first three are critical elements of the ICH Q8 topic. If we put those together, then we can build on top of that this concept of regulatory flexibility. So Q8 is really a major engine driving towards the opportunity for regulatory flexibility. If you look at this in the context of the variable space, you can take a couple of hypothetical vectors and Ajaz earlier talked about what some of those might be. Traditionally, industry has focused on a very narrow understanding or at least described a narrow understanding, even if it knew more, intended to do that three batch validation and any move away from this situation created a post-approval change.

What we're saying now is if we consider the overall boundary and we have a good understanding of the impact of these variables on product and process quality, and we can look at elements of risk, that we should be able to move within the space that's described by this rectangle and optimize our processes and this is not a change because it's within a pre-agreed and described variable space. We understand the implications. So we can now move to this new paradigm of continuous improvement. We don't need to keep submitting post-approval supplements.

So it creates a kind of if and then process for the future. If industry can provide and regulators agree that there is a appropriate relevant scientific understanding and earlier a couple of concepts were put forward such as stability and availability, if we can show that is understood, if we can show the ability to predict the impact of movement within our defined vector space to predict the impact on quality and performance, if we're confident that we understand the control of product and process critical variables with an ability to be able to assess the impact of change, if we can show a degree of high competence in the value of our specifications and the validity and reliability and reproducibility of our processes, then we get to a new state where first cycle CNC approval is much more likely.

We can continue to optimize our processes without seeking prior approval and we can work to improve the dialogue and assist the risk based inspection process because we understand what the critical quality parameters are. Of course, this carries some implications for the future. Both industry and the agency will need to think differently. Industry submissions will need to change and the agency reactions and behaviors for both submissions will also need to change. There are some issues that we need to resolve as we move the guideline forward, of course. Industry, what do we put exactly in P.2. What is the depth of the discussion that we would put? Well, we said it could be a continuum. Looking at it in terms of the agency, how do we construct a consistent review of the section. Because the amount of information is going to vary, it's not in Section P.2 going to be a compliance document. It's an information and understanding document. We want the reaction that gives flexibility and an incentive, not a reaction that is ticking the box.

We've said that this document can have utility for both review and inspections, so we need to define exactly what the separation overlap of roles and responsibilities is likely to be. And we need to think about how we might update this document. What would trigger an update to this particular section? Why would we do it, how would it be submitted. Now, if we can get these resolved and I think we can, we get to a future state vision which demands change on both parts. Hopefully with an agency perspective, we get the more open communication about our understanding. We're able to work with the reviewers in an engaged way looking at the science and the agency accepts a change of content of applications which encourages this knowledge sharing and encourages elimination of simply providing data. We would encourage that agency to move to science and risk based evaluations and that will, of course, reduce post-approval change in regulatory matters. The quid pro quo of course is that industry needs to be transparent. It needs to share the information. Sometimes we have the information, sometimes it needs to be generated.

We need to understand that our regulatory agencies have needs and we need to provide them with those needs. If the agency is willing to accept a different content, we have to provide a different content, a content which shares the knowledge, a content which focuses on the science and our understanding of products and processes and a content which actually talks about assessment of risk and its mitigation.

Putting that all together means that we need to provide an insight into our manufacturing processes if we want to achieve that regulatory flexibility. But I think if we drive Q8 to a successful conclusion, it does, indeed, open that door to the new state and it compliments the other initiatives that have been talked about here today. Thank you for your attention.

(Applause)

CHAIR BOEHLERT: Thank you, John. Are there any questions or comments from committee members?

DR. GOLD: Judy, may I?

CHAIR BOEHLERT: Yes, Dan, please.

DR. GOLD: First, I'm very much in support of inter-group knowledge in the development of processes. I've long felt that we too often rush our processes because of commercial considerations and do not explore members' base sufficiently, so I'm very much in favor of this, but I am confused about a few issues as explained here. I will get your slide 12, which is parameter space, variable X, variable Y and you show a small explore space in the upper right-hand -- left-hand quadrant showing a rather narrow evaluation of the parameters and then you show a rather large space to the right, parameter space to the right. Is it your thinking that this second parameter space would be explored and defined in the initial filing? And if that were the case, why would we not have enlarged the total allowed parameter space in the initial filing?

DR. BERRIDGE: Well, I think each one builds -- it depends on the scale of your understanding because I could have drawn this with a little rectangle around what's in the right-hand area.

DR. GOLD: Of course, of course. What I'm really asking is, if you -- in this development, in this enlarged -- am I getting feedback?

DR. BERRIDGE: No, it's okay.

DR. GOLD: If in this enlarged development of parameter space, you already know the efficiency of the variables and the variables are acceptable to produce a product that will be fit for use, why would you not include it in the original definition of the allowed parameters?

DR. BERRIDGE: Well, I think that you would include in your original submission a description of the impact of let's say the extremes of this parameter space. You might not have explored every increment within this parameter space but you will know that moving around the extremes does not have an adverse impact on product quality attributes. You might then move instead of let's say the upper left-hand quadrant, your consent is one where let's take a blending operation as an example. In the upper left-hand quadrant of this picture it really represents a process that says, "Blend for 10 minutes". Now, as you move to the future state, you change that time based concept to an -- actually, to a material attribute concept and you talk about blend to uniformity.

And you then move within this parameter space, to a blend to uniformity criteria. Now the exact space -- the exact point you're going to be on here is one that you can -- that you monitor and control in real time. And for example, you may include process analysis tools to actually monitor that attribute and you could be moving around in this space on a batch by batch basis, depending upon your material inputs for example.

But you can't define exactly where you're going to be at any particular point because you've moved now to a different paradigm, not one that is rigorously controlled, but one which moves within a bounded space that you is not a problem provided you are within it.

DR. GOLD: I understand, but then why would you not include that in the additional filing?

DR. BERRIDGE: You could include the boundary in the --

DR. GOLD: In the initial filing.

DR. BERRIDGE: -- initial filing but not necessarily the exact point that you're going to be on a batch by batch basis.

DR. GOLD: As a manufacturer won't you be -- won't you have an advantage if you included this larger parameter space in the initial filing --

DR. BERRIDGE: Well, as I say --

DR. GOLD: Excuse me, and obtain approval for this larger space and use POT to define when an acceptable end point would be reached?

DR. BERRIDGE: Exactly. That opportunity is there to describe this boundary absolutely. That's what we're trying to encourage, a description of the boundary and an ability for you to move within that space without having to go to the agency and say I want to move three points to the right because it's actually not a change. It's within the agreed process and product parameters that have been submitted in that original application.

DR. GOLD: I'm fully in favor of this but I believe that what you're describing may be a rather trivial example. A more pertinent example, perhaps, would be where you have explored different particle sizes for excipients and have shown that when you have a change in excipient particle size, and that occurs to many of us at various times, you can still achieve a successful blend by modifying the conditions appropriately and upon your knowledge of the particle size and how it interacts with the blending circumstance. Perhaps that's a more significant approach to exploring parameter space in a beneficial way.

DR. BERRIDGE: I absolutely agree with you. In the time I was here today, I couldn't give you a set of illustrations of all the things but absolutely. So as I said, you could move within this space and it may be that one of these axes is particle size and excipient dense and another axis could be lubricity of magnesium stearate.

DR. GOLD: Correct, correct.

DR. BERRIDGE: And then based on the input material attributes, you then as you're monitoring their impact on the process, your actual process itself, the timing or whatever you do with the process, is actually moderated by your assessment of the input attributes and I could have used that as an alternative example.

DR. GOLD: Yes. If I may have one more minute, Judy.

CHAIR BOEHLERT: Okay, one minute, because we have another question.

DR. GOLD: Okay. And that is if we are going to allow enlargement of Section 3 of the CTD, there's no mention in any of this yet of enlargement of the expert report that accompanies the CTD. Is that visualized as part of the extension of Section 3?

DR. BERRIDGE: Well, I would have to somewhat disagree with you. We're actually thinking that the body of data of the CTD could change, not necessarily enlarge, but it changes because its focus becomes different. It's information not simply huge amounts of data. In terms of what you call the expert report, there is no longer an expert report. What we do have is a quality overall summary.

DR. GOLD: I'm sorry, I'm misusing the term, correct.

DR. BERRIDGE: And I think there is an opportunity and FDA itself has been describing the potential for an opportunity to look at how that quality overall summary can act as a good distillation of both manufacturing sciences so it's concisely embodied in that single document. Now, what that looks like has not been discussed within the framework of the CTD group but I think it provides an opportunity that we're beholden to look at.

DR. GOLD: And that is one of the objectives that will be coming forth?

DR. BERRIDGE: Certainly, it's one of the topics that we should be considering.

DR. GOLD: Thank you very much.

CHAIR BOEHLERT: Ken, did you have a question or a comment?

DR. MORRIS: Yeah, a little of both, actually. Following on Dan's point, I think part of the issue with respect to margining space to use your example, Dan, is the fact that when you're in development, you may not have the range of raw material characteristics in order to define that fully. So you may not have the opportunity to file against the whole range would be one comment.

Which certainly leads into the question or to the thought is that one of the things we are always struggling with in the new -- in your new paradigm is now the three batches and out is the rule which we all agree has flaws. How do we define it so that there are criteria that will let industry know when their product is ready to file, I think is the question. I'm not sure. Do we have the answer to that?

DR. BERRIDGE: Sure, I want to delve into the answer to that but yes, that's a pertinent question.

DR. MORRIS: But I think that's something that we have to discuss as we are discussing, of course, outside this meeting as well, but it's something to be taking an issue, I'm assuming that Q8 will --

DR. BERRIDGE: I'm not sure that Q8 will actually attempt to define what product set validation should look like.

DR. MORRIS: Yeah, I wasn't thinking so much of validation in the strict sense as I was just the scientific basis for a decision. Somebody else may have a comment.

CHAIR BOEHLERT: G.K., did you have a comment?

DR. RAJU: Sure. I have a question, actually, John, reflecting on Ajaz's comment earlier today on what you're going to put in this section. To what extent is your thought process and maybe all thought ICH about generating new science and data knowledge as opposed to simply taking what you already have and putting it into a submission? To what extent is the about putting what you have in, in a different way or generating a new kind of knowledge, a new kind of understanding?

DR. BERRIDGE: Well, I think there will always be elements of both, but I think a good start would be to provide in the initial submission what is already there. I think there could well be more that's available that's not necessarily being encouraged to be shared. I think we need to also, to come back to Dr. Morris' point, think too about the state of knowledge at a particular phase. So I think there will be an amount of knowledge that exists in the initial submission, which is fit the purpose and then as the product moves into the commercial manufacturing phase, a whole new set of information and understanding can then be generated and I think there's an opportunity then to build on the initial R&B knowledge with the knowledge that's acquired through the manufacturing of scale to describe a still greater understanding of the manufacturing sciences and it's probably -- could well be at that second stage that we really get to a more stable situation where we described what we call the band width within which we can truly effect that ongoing continuous improvement.

CHAIR BOEHLERT: Okay, Garnet, then Ajaz.

DR. PECK: In reflecting through your slides, there is the element of what is done in Europe and the complete understanding of the formulation. What is the objective of a particular product and going back to Slide 12 and flexibility, I still see and I like this, is the material science of the material that we're bringing together into a particular dosage form. That's highly significant and will aid us and we're approaching a better field and you've already mentioned excipients and particle size, that's one element of it.

The second part of what's in the flexibility is the understanding of the processing of what we're trying to do and I look at your diagram as an extreme vertices type of thought and you have in the center of the extreme what you want but you do have limits and that guides you and I think we can look towards that kind of guiding rather than just the simple three-batch concept. It gives us space.

DR. BERRIDGE: Yes.

DR. PECK: And I think you've also emphasized the space part. I think that's important.

CHAIR BOEHLERT: Ajaz?

DR. HUSSAIN: I think this discussion is very helpful but at the same time the comments consider different ways of defining the space. For example, the aspect of how much information we have on expedients and their functionality at the time of new product development. Some might be limited but you can bring that know how to bear on that because I think we have established a way to say all right, the physics might not be different, so the use of prior knowledge, better use of prior knowledge, I think, is a key opportunity and I think -- so that the company has made 300 different formulations of a drug. The chemistry of the drug might be different but the physics of the powders are not that different. So how can you bring that to leverage an opportunity?

CHAIR BOEHLERT: Okay, any last brief comments? If not, John, thank you very much.

Our next speaker is Fred Razzaghi, and he's going to provide an update on ICH Q9.

MR. RAZZAGHI: Good morning, Dr. Boehlert and good morning, Committee. I'm here to give you an update on the status of the Quality Risk Management Doctrine developed at ICH called Q9. I've been talking to you about what quality risk management is. I'll give you some background. Initial steps in guide development, development of the guideline. The guideline starts off as to the scope, the process and the tools and how it's integrated into operations and what the next steps are.

This team is defining progress management as a process in assisting of well defined steps which when taken in sequence support their decision making by contributing to a greater insight into risks and their impacts. And the steps in the process could include identification of risks assessment, education, elimination and communication of risks. There's some understanding in the committee, in the group, that risk is a combination of property of occurrence and severity of the harm that this caused.

Here's some background for you. Last October you were presented with three presentations. One, use of management from simple manufacturing, then you provided with a process risk assessment model and then the relationship between risk and knowledge and how to apply them pre and post-approval, e.g. scrutiny and post-approval changes and the variety of GMP areas. IN April at the OPS meeting, one of the objectives that were stated was that OPS will implement a review quality system and procedures that will recognize the level of scientific knowledge, supporting private complications, plus process capability, apply a risk base rate to scrutiny that will relate to level of scientific understanding of how formulations from manufacturing processes factors besides product performance and then the capability of process control strategies to prevent or mitigate risk of poor product performance.

Some background in the ICH process to date; there was a meeting in July in Brussels where groups came together to discuss whether or not there were merits to moving ahead. Following that, there was a meeting in Osaka, Japan in November of last year where the concept was developed and approved by the steering committee. In between November and June we snuck another meeting in there in March in London, where we drafted an outline and had a discussion for two or three days about what is the general approach to actually making this happen.

And then we had some significant progress made in Washington in June where a first draft of a guideline was issued by the team and it's been distributed to the constituents for review. A few words on the approach here; in July of last year, this statement was agreed upon by all parties, "To develop a harmonized pharmaceutical quality system applicable across the life cycle of the product emphasizing an integrated approach to risk management and science".

The ICH process is unique in that it requires consensus by all the parties and it has its own varying process because of that. We also agreed in March that we would keep a few things in mind. We want to approach this with a process oriented thinking in mind. We want to be practical about it. We want to find where we can use available risk tools and apply them appropriately. We want the product that they exercise to give us some predictability. We want to approach it in a flexible manner because we want it to apply to as many places as possible.

We expect it to be consistent and integrated. Initially the goal was to come up with a risk based approach here and we sat down and went through a list of why are some of the reasons we need to have a risk based approach here. The document -- these are some of the reasons and I won't go through them. I will kind of run down the benefits for you. We thought that enhanced patient confidence in this to assure quality is a benefit. We expect to promote more effective use of regulatory agency and industry resources. Establish a systemic and well-informed thorough method of decision making which leads to greater transparency and predictability. Increased knowledge of exposure to risk, and as Ajaz mentioned, we expect this to foster quality by design, continuance improvement in the technology embracement.

The scope of this document is as follows; this provides the framework that may be applied to all aspects of pharmaceutical quality, including GMP and submission of new processes throughout the life cycle. It applies to APIs, drugs, biologics, vaccines and excipients of packaging material. It does not include pharmacovigilance.

The process is as follows. First, the process will be initiated, assessed, risk has to be confirmed, communicated and then follow-on review. Some guiding principles here are the evaluation of the risks should ultimately impact on the potential risk to the patient. The extent of the risk management process should be commensurate with the level of risk associated with a decision. The more robust dissent would be to lower a certainty. It is essential to have a clear delineation of the risk question. Risk management should be a iterative process. People who apply risk management should be trained and use it appropriately. A risk management process should be appropriately evaluated and verifiable.

Now, once we embark upon starting a process like this, this is some of the thoughts to keep in mind. Define a specific risk management problem or question including the assumptions leading to the question. Assembling background information and data under hazard where human health impact relevant to the assessment. Defining how the assessment information and conclusions will be used by the decision makers. Identify the necessary resources. Members of the team will have the appropriate expertise with a leader clearly identified.

The idea here to do a good job of risk assessment you need a team of experts that can bring knowledge and information but there's a need for someone who can exercise a tool, that's aside from the experts on the specific scientific topics. Ask and direct life risk assessment questions. State clearly the assumptions in the risk assessment. Assessing the quality and sufficiency of relevant data and specifically a tie line of deliverables for the risk assessment.

Now, I'm going to go through the process. The first is risk assessment and three questions are posed. What can go wrong, what is the likelihood, which links back to the original relationship and what are the consequences? It breaks down into two pieces. Risk analysis is a suspended use of information to identify specific sources of harm and to estimate the risk. Risk evaluation compares the estimated risk against given risk criteria using a quantitative and qualitative scale to determine the significance of the risk.

The next step is risk control. It describes the actions of the risk managements decisions. The questions here might be what could be done to mitigate and reduce risk? What options for controlling risks are available? What are the impacts of current risk management decisions on future options risk management? This too breaks down into three steps; risk mitigation focusing on reduction of severity of harm, risk reduction focusing on the reduction of probability and occurrence of harm and detection of harm and risk acceptance is a decision to accept risk, i.e., no additional risk control activities are necessary at the time the decision is made. In other words, once risk control is completed the decision to make the move ahead but the next event you will see allows the opportunity to come back.

The next step in the process is to communicate the risk. Risk communication is the exchange or sharing of information about risk and risk management between the decision maker and other stakeholders. Information can relate to the existence, nature, form, probability, severity, acceptability, treatment, detectability and other aspects of risk to quality. The communication of one's stakeholders concerning quality risk management decisions can be made through existing channels. In other words, in each region currently there are ways where industry and regulators communicate on a variety of risk issues.

And this is a piece about coming back to the decision. All risk management processes are dynamic or iterative. Quality risk management would apply to benefit from new knowledge with each decision cycle and used to enhance future decisions allowing for continuous improvement. In other words, when the team exercises that process of going through a risk decision, the outcome of that would be something that would be useful next time a risk decision is required.

Here is a proposed process flow. I just went through it. There's an initiation step, there's an assessment step, there's a risk control step and then a communication step and then a look back or review. The we've listed some risk management tools and in this section, what the team -- what we tried to do was not to go out and re-invent the wheel, and was to look around for what are some of the best tools out there that are available keeping in mind that a lot of these tools are used in other industries and we need to apply the original criteria for retrofitting it to the particular circumstance that we're dealing with in pharmaceuticals.

But one thing that we thought we are going to put on that list is process mapping, which is the orientation of thinking when it comes to risk. Most of the places we're thinking of applying this, we're talking about a process where the knowledge of events prior and following are important to realize. And there's a list of them here and Ajaz mentioned HSSN (phonetic) and FMEA. All of these have a variety of attributes and are used in different places.

A complimentary list to that list is the use of statistical tools that give you information that allow you to make a good discussion and there's a list of them here. Design of experiments is something that was mentioned already, so now this part talks about how we take these concepts of risk management and use of the tools and where could they be used and here's a list of them. Risk management or risk assessment could be used in product development, e.g., a discussion of the risks and the limits of knowledge or the specification being set during development. Regulatory authorities can use risk assessment and risk management when they do regulatory pre and post-approval. It could be used as a component of quality system. In other words, in auditing complaints, recalls and changed management, there is always a component that could benefit from the use of risk management.

And there's a list of other applications. It could be used in facility management, it could be used in supply chain management, in other words, materials management, assessment of suppliers, that sort of thing. It could be used in production. It could be used in validation. It could be used in laboratory controls, packaging and at the end we put Regulatory Authority Activities which applies to some of the other regions. It is quite active in this committee and they put forth some valuable information to this product -- to this document. David is going to talk about it tomorrow. The risk granting and the process that's proposed comes from that.

Our next step is apparently the draft document is out there to the parties that are involved in ICH to review this thing and give their comments back. In September, we plan to get together and try to consolidate those comments and take a Step 2 document to Yokohama, Japan for the steering committee to approve. I've listed here for you the organizations that are participating in this working group. As you can see, it's quite diverse and it's a challenge to work the consensus process and it has benefit of leadership from PhRMA, the FDA and from the regulators. And we've gotten very good technical feedback from the European industry. This is the beginning of the list of definitions. This list is expected to grow as we get a little more detailed into the document.

And then finally, I have some references for you. Thank you.

CHAIR BOEHLERT: Thank you, Fred.

(Applause)

CHAIR BOEHLERT: Are there questions or comments from the subcommittee members for Fred. Yes.

DR. RAJU: Fred, as you look forward, how do you see the Q9 and the Q8 processes in --

MR. RAZZAGHI: That's a good point. What we've talked to Q8 about so far is Q9 is basically a tool that needs substance in it. In other words, the real value of risk management is what is the process of working through a decision for example, to come to a decision. But that vehicle would be hollow if it's not filled with information. So the best use of this tool is involvement would be if the relationship between knowledge and lack of knowledge and development can be explored as a risk that using this process will allow us to move to the next phase, continue to make progress and collect more information and --

DR. RAJU: And that's something that will take -- is the thinking about connecting the science of this with the science of --

MR. RAZZAGHI: Yes.

DR. RAJU: -- approaches that would happen after the --

MR. RAZZAGHI: Yes, some of these things are working in parallel. Q9 is working to develop the document and we're kind of working closely with Q8 to find out what the synergies are and we'd like to do that same thing. We have in our section about integrating. The real value of this tool is going to be how to be used in a variety of places. So the criteria that we have used for selecting and using would be for it to be flexible and simple but maintain the poignant parts of it.

CHAIR BOEHLERT: Other questions? Dan?

DR. GOLD: Yes, Judy. Can you explain why you're not developing the severity concepts that are related to all this?

MR. RAZZAGHI: That's a good point. We have looked at some models and we haven't quite gotten to the point where we're going to negotiate or discuss how that ranking is going to be done but the preliminary thinking is it is fair to stakeholders to discuss it and come to an agreement as to what the ranking -- what the appropriate ranking should be in the absence of one that's out there that could apply to everybody. There isn't one out there that applies to everybody.

In other words, given a certain process, given a certain product, in the context of the science of that product and process, you can discuss and come to an agreement what the appropriate ranking could be or if generally speaking, the risk is low, the person who's using the tool can do a risk ranking on their own and then explain it, you know, in an appropriate setting.

DR. GOLD: Have you seen any differences in the three regions in evaluation of severity levels or concerns for severity level differences and viewpoints?

MR. RAZZAGHI: Yeah, I think John is a lot more gracious about it than I. I put that bullet in my slide. It's quite a challenge. It's quite a challenge to work with a topic like this in ICH. And there are a variety of -- I mean, risk is understood in a variety of ways by all participants. And work off of a template that says let's look at these principles that we're trying to implement every time you look at a topic, look at a specific issue, it's helping us make progress. And as I said, the regulators especially FDA has come forward with a lot of information and they're really helping to move the process along.

PhRMA has done a good job of providing leadership and kind of moving it along. So I would say that the chemistry within the team is working pretty well but we have no illusions about the feedback we're gong to get once the document is out for comment.

DR. GOLD: Thank you.

CHAIR BOEHLERT: Okay, Nozer?

DR. SINGPURWALLA: Yeah, I have two comments. On your slide entitled "Risk Assessment", the first comment I'd like to make is that there is a difference between what we mean by probability and what we mean by likelihood and to articulate that difference is going to take me an hour but for the record, I don't think you should use the two words interchangeably.

The second comment is that your definition of risk analysis is circular and let me tell you why. You define risk analysis in terms of risk but you've not defined risk. So --

MR. RAZZAGHI: No, that's okay. I have the definitions in the back and I kind of flew through it, but --

DR. SINGPURWALLA: Okay, and the third comment is your catalog of supporting statistical tools is very incomplete. You can have --

MR. RAZZAGHI: It is.

DR. SINGPURWALLA: -- a long catalog, but the more important elements that should go into that catalog should be a elicitation of probabilities and elicidation of debilities. That seems to be the very important function that one needs to do a risk analysis. Design of experiments, I'm not going to argue with you but I don't think that it should be an important tool. Control charts, it's accumulated some charts -- it's cumulative some charts, not accumulated some charts. So these are just academic quibbles for the future. You may want to look at these slides more carefully.

MR. RAZZAGHI: I would be interested in those two points that you raise because one of the challenges we've issued to the team in I think it was in Osaka, was that in order for this thing to work, we need to go back and do some homework. It's -- you know, we really have to manage the dynamic --

DR. SINGPURWALLA: I'm delighted to go to Osaka and tell you what it's all about.

(Laughter)

MR. RAZZAGHI: You're certainly welcome.

CHAIR BOEHLERT: Other questions or comments?

If not, thank you, Fred.

MR. RAZZAGHI: You're welcome.

CHAIR BOEHLERT: Our next speaker is Dr. Tobias Massa and he's going to be talking about an industry proposal for life cycle management for processes and system control.

DR. MASSA: Good morning. What I'm going to talk about now is not formally an expert working group at ICH. It's a proposal made by the three regional industry groups to look at what quality systems need to be in place in order to realize the potential of Q8 and Q9. We are looking at this is how we can utilize science and risk based quality management systems to enable post-approval change and improvement. So we're trying to take what have we learned in Q8, what do we know about the process, how do we apply risk management tools to it and be able to operate in an environment that allows us to make continuous improvement, make post-approval changes, but the important thing is trying to operate within that box that Dr. Berridge described, define what the box is so that we don't have to get into a loop of continually having to make supplements in order to implement that change.

So what we want to be able to do is define what are the quality systems that we need to have in place that give both ourselves as well as industry the confidence that we're looking at our manufacturing and control processes appropriately and that based on the knowledge that we gain during development as well as during commercialization, that we are appropriately using all of those tools, collecting all the data appropriately, evaluating all that data appropriately and then implementing change in a controlled manner. What we want to do is put this into -- put this process into a guidance because there are different expectations about how this should be done that vary region by region and inspector by inspector.

One of the things that both of the previous speakers talked about was that there is disharmony in what some of these expectations are and the goal here is to try and create a harmonized guidance of how do you apply this tool. What we would like to have in this document is a description of how you monitor your process and controls to identify trends. Now, those trends may tell us you're in control and you don't have to do anything further. You just continue to monitor or they may tell us that we need to do something to get things to an appropriate level of control or improve the process.

We also want to have a system that allows us to look at what we've called the undesirable occurrences, the things that we need to react to, such as deviations, product complaints, audit or inspection findings, or the results of our root cause analysis and how do we incorporate those into a technical agenda for the particular product we're talking about? We also want to have a system that allows us to take our proactive activities into account. We know that at the time we go to commercialization, we may not be optimized. In most cases we are not optimized. So we go into commercialization with a knowledgeable technical agenda. How do you -- what quality systems are you going to use to make sure that those are appropriately worked into the quality plan for that particular product?

What we hope to do by having this guidance in place -- and it's important that these things need to be linked. What we're talking about needs to be linked to Q8 and Q9, is that we have a standard that allows us to realize the full potential of Q8 and Q9. We have a standard that encourages industry to make changes. I'll show you some slides at the end of my presentation that explains why this industry is discouraged from making changes.

We also need to give the regulators confidence that we have the appropriate quality management systems in place to handle this. And as Fred mentioned in his presentation, we want to be able to provide product to the customer and insure that we have a continued source of supply for these valuable products to the customer. One of the things that we've looked at over time or what some of the concerns have been out there relative to our products, and this is a slide that I think Ajaz may have actually presented here at the beginning of our discussions about product quality and GMPs. And one of the key concerns was that we had variability that creates an increased risk. What we don't know about the product and how variability impacts the product creates risk. As a result of that risk, we have more compliance. You have to test more, we get inspected more but that's absolutely the opposite of what we're trying to accomplish.

What we want to do is have quality by design; design these things into the process, into the control of the manufacturing process rather than testing to assure quality. And I think this slide kind of gets to what Dr. Peck and Dr. Gold were talking about. In our typical GMP process, we have raw materials coming into a process that's controlled by process variables that lead to some product that meets some determined set of specifications. During development, what we currently do or at least the perception of what we currently do is we concentrate on the process variables and we don't look at the variability of the incoming raw materials. So we concentrate on the process variables and we try to optimize those during the development process and during commercialization, we concentrate on controlling those process variables. But when we get variability in the raw material, to Dr. Peck's point, you know, some of the physical attributes of these materials, we end up with an impact on product.

So what we're trying to do is change this paradigm. Now, I'll leave this for you to read but Deming, you know, 50 some odd years ago made a comment about variability in inspections and testing quality in as opposed to designing quality in and the key things to take away from his comments so that you have to understand the process. We were talking about this 50 some odd years ago, we still talk about it today. And we want to be able to predict quality from upstream activities and measurements, not on final product quality attributes. And we want to do all of this by working toward reducing variation. Well, that's exactly what quality by design is.

Dr. Hussain, today, presented information that was also on a slide that Dr. Nasr gave at a presentation at DIA just last month, talked about FDA's desired state is. Well, I think you can take the FDA off the top of that and put industry's desired state up there as well, because these are exactly the same things we want to achieve. We want to have quality by design. We want to be able to set specifications using mechanistic understanding. We want to be able to have continuous improvement and we want science and risk based regulatory policy that allows us to undergo continuous improvement.

These are the same things that we want. This slide has been shown before. It's one that started out in PhRMA and the quality by design paper. It was adopted by the ICH industry groups as we started making our pitch to the regulators about what we were trying to accomplish with Q8, Q9 and Q10 and I think it's been used by I don't know how many people in various presentations. The concept here, quite honestly, is that the more you know about your product, the greater your level of manufacturing science knowledge is, the less risk there is that variability is going to have an adverse impact on your product. So as manufacturing science knowledge increases, and that's not necessarily during development. That can be during commercialization.

To the points that have been made before, we've probably learned just as much or more about our process during commercialization than we do during development. So we should take that accumulated knowledge, the risk that associated with that product and processes and controls should decrease over time as that manufacturing science knowledge is obtained. The goal here is to have an appropriate level of regulatory oversight that matches up with the level of manufacturing science and the level of risk that you have. So the more manufacturing science you have, the less regulatory oversight you should need particularly in the area of post-approval changes. The key to that it having the right quality management systems in place that control how you're doing change within your company for that particular product because having that flexibility doesn't decrease the oversight that you have to have as you are implementing change.

It's just, what we're trying to talk about here is what's the level of regulatory oversight, what's the level of prior approval that you need in order to implement changes. So how does this come together? How does this work and I'll go through this with words and then show you some diagrams of how we envision this. It starts in development with quality by design, using data rich experiments to identify the critical quality attributes of a product and the process. To the points that have been made before and what Q8 is all about is taking this development data and getting it appropriately into an application for review.

The point has been made before that several of us in industry have met with FDA to share what the data base is that we have going into an application and it's, I think, true that we've been reluctant to submit all of the information or more information than what we currently do in an application because all of that is looked at as a regulatory commitment. It's not looked at as here's the data that got us to what the actual regulatory commitments are. How did we identify what the critical process parameters are? How did we identify what the in-process controls and specifications are? It all gets looked at right now as a regulatory commitment. So there needs to be a give and take on both industry's part and the regulator's part what information gets submitted and how those data are reviewed and looked at.

All of that data leads us to our validation protocol. What are the critical process parameters that you're actually going to validate and monitor during commercialization? That will lead to your validation report and both of those things, I think, are appropriate to be submitting as part of this piece of data that you're going to be giving the agency. One of the things we haven't talked about, we've talked about setting specifications based on a mechanistic understanding of the process but what we haven't talked about is interim specifications. In other words, what are the specs based on your development data and how might they change as a result of the accumulated commercial data that you get over in your initial manufacturing process.

Q6 actually talks about setting interim specifications but it doesn't go into how you go from -- or how you set interim specs and then how you convert those to long term specifications. So that's something that we should be able to think about and work out. Dr. Hussain talked about comparability protocols and hopefully the final document that comes out on comparability protocols will be broad enough to encompass the types of changes we're talking about here. All of this leads to the point of having continuous improvement in supplements without prior approvals. Having the science and the risk management piece of that is one part of doing that. Having quality management systems in place to control that process of continuous improvement is what we're trying to implement with Q10 or propose in Q10. And this is kind of what we, at Lilly kind of call our radiator diagram that depicts what we envision this process to be, starting in development and driving towards a development history report based on the information that's in there, you start to develop an integrated validation master plan.

We also have what we call a process flow document which gets very specific about how you make and control the product. It's very specific to what equipment is used, what are the operating parameters, raw material specifications, all of that. Ultimately that leads us from working in the pilot plant to transferring this process to the ultimate site of commercial manufacturing where we undergo qualification and validation using today's parlance.

We then get to commercialization, what we're calling execute and monitor, where we're accumulating information and getting ready to make two types of changes; one what we can technical evaluation changes. That's the prospective part. How do we want to optimize the product based on what we've learned during development and what we've learned during commercialization. The reactive part is the GMP or quality evaluation and that's the response to things like out of specs, deviations, product complaints, adverse events. Both of those would go through the same type of risk analysis that Dr. Razzaghi referred to and we would develop a quality plan for that product at that site. And that would cycle back into the process, maybe even going back into further development and then working its way down through the chain again.

But in order for that to happen, and what we're showing here are two parallel processes. The top process is really the scientific part. The bottom part of this, the bottom three boxes or the bottom half of this diagram, really refers to having the appropriate quality management systems that allow the science to drive forward. So you can't have one without the other and that's what we're trying to drive through with Q10. So again, coming back to Dr. Gold and Dr. Peck's concerns about how the process should work, if we are concerned about physical attributes, for example, of raw material coming into a process, if we're using PAT to measure those raw material attributes, we can adjust the process variables on a feed forward basis. By the same token, we can look at the product and measure critical quality attributes that are being accumulated for the product and feed back on those process variables. And the combination gives us better control of the product and this is exactly what, I think, we're talking about when we talk about quality by design and operating in that box that Dr. Berridge referred to because making these changes to these operating parameters, these process variables, if you've defined them appropriately in the box are not really manufacturing changes and they're not things that need to -- certainly not things that would have to go through a regulatory approval process.

What you need to have are the appropriate quality systems that allow you to monitor these things and keep track of how they're occurring and determine what changes need to be made based on that monitoring. Q10 is only part of the solution to post-approval changes. Now, part of the deal here is that if we're identifying the box appropriately that we talked about, we don't have to get into a lot of post-approval changes because they would be considered part of the process. But I still think and I'll make the pitch, that the regulatory process needs to be changed. And the reason we say that is that regulators regulate regionally. Manufacturers commercialize globally. There is definitely -- we talked about disharmonization before. There is definitely a lack of harmonization on the regulations that govern manufacturing changes.

Every region has a different set of rules that we operate under and these differences can include the regulatory mechanism for filing the same change, what the review cycles are for the review of the dossier, data requirements and even interpretation of the same data. Over time, this has resulted in this reluctance on industry's part to make changes because the regulatory hurdles are high. And just as an example, if you consider an API in Product A, we start off submitting one CMC dossier for that product. That gets submitted and we'll just talk about four regions right now that result in differences in the specifications, in process control, shelf life and in some cases can even impact how you're actually making the product.

One of my colleagues related to me that for the same product they actually have three different manufacturing processes that came out as a result of the review process. So now you've got, instead of having one product, you've got four different bulbs that are regulated differently because of the differences in the review process. If you now start to make process improvement changes, you start getting differences in those products as well or that review process results in different APIs there as well.

So now you've got two different processes running three to five different products. It creates an absolute logistical nightmare to do this. Now, if you take that and magnify it even more, saying that you're making a change in an API that effects three different formulations of the same product, you can see that this becomes a real logistical challenge to make change. And just by way of a simple example, we at Lilly had a change which was an extension of an expiration date based on real time data, based on an approved protocol. We had to file over 100 supplements or variations and it took over two years to get all of that approved. And that's a simple change that certainly in the United States is an annual report filing, but because of regional differences, we had to go through a rather extensive regulatory process. So I think the combination of what we're trying to do with Q8, Q9 and the proposed Q10 and a change in some of these changed regulations will get us to a point where we have much better use of our resources, much better use of the regulator's resources, and a system that allows us, a quality management system, that allows us to do continuous improvement.

Thank you.

CHAIR BOEHLERT: Thank you, Dr. Massa.

(Applause)

CHAIR BOEHLERT: Any comments from the committee? We're using up a lot of time very rapidly. Ajaz?

DR. HUSSAIN: Well, I think I wish to thank Toby for coming, especially today's is his wedding anniversary and --

DR. MASSA: Thank you. My wife will thank you if the plane gets home on time.

CHAIR BOEHLERT: Ken?

DR. MORRIS: Just one question, maybe you said this but what's the timeline of this?

DR. MASSA: Well, that's an interesting dilemma for us. One of the issues we're running into, particularly with the EU and Japanese regulators, is they have said they don't have the resources to devote to Q8, Q9 and Q10 simultaneously. So we're kind of on hold at this point. The ICH steering committee has given a tentative approval to the Q10 concept but we're not going to be able to form an expert working group until we get to Step 2 for either Q8 or Q9.

Now, give credit where credit is due, I think in FDA we're trying to drive this forward independent of the ICH guideline. So we may be able to lead the way here and try and push the EU and Japanese regulators to see the benefit of this.

CHAIR BOEHLERT: Other questions or comments? If not, thank you, Dr. Massa. Our last speaker before we take a break this morning is Don Marlowe, who's going to be talking on the ASTM E55 committee.

MR. MARLOWE: Good morning, Madam Chairman and committee. I appreciate the opportunity to speak to the committee about the development of standards for PAT. What I hope to do this morning is give you a very brief history of where we've been. It's been about a year since we've started doing this and try to give you a feel for the framework that we're operating within and please, as I go along, if there's any questions about where we are, don't hesitate to jump on me here.

First of all, I hope to leave you with these four points when we get done and to a later or lesser degree I can do this and get you out in time for your scheduled break. Why use consensus standards, first of all, for PAT? Consensus standards provides an opportunity for all interested parties to participate in the discussion as equal playing partners, so that they members of the regulated industry, academic experts and people from the agency can all come to a non-threatening forum and sit down and talk about the issues and talk about what the important topics are and agree on what approaches should be to accomplishing the objectives that everybody wants to achieve and it's a balanced discussion. If you operate within the voluntary standards community in the United States and particularly if you operate with an ANSI accredited standards developer, you are guaranteed that the process discussion will be a balanced discussion. That means that no sector of the community will have a dominant voice in the discussion and we'll talk about that as we go along this morning, but for example, the FDA is just one partner at the table. The regulated industry and the academics are partners at the table but nobody can dominate the discussion.

Due process is an important consideration. The ANSI, American National Standards Institute, basically has an umbrella set of rules within which all standards are developed in the United States and they follow closely to the WTO Code of Practice and the TBT Agreements on the handling of documents within the standards process and one of the key attributes is due process. Everybody has an opportunity to be heard and nobody can summarily dismiss a discussion. It has to be considered and evaluated by all the partners.

And finally the NTTAA, the NTTAA is the National Technical -- Technology Transfer and Advancement Act. It was passed about 1995 and has been implemented by the Office of Management and Budget in a guidance document, A-119 which basically tells the federal agencies to use the standards developed through this process, through a voluntary consensus process, wherever possible. So in order to comply with our responsibilities under NTTAA, we are using this standards developed in ASTM as an engine for accomplishing this activity. And ASTM is, as I said before, an ANSI accredited standard developer with all of the baggage and attributes of an accredited developer. They have more than 100 years of experience. They were formulated. They were developed in 1989, specifically at that time to improve fatigue, what we now believe to be the fatigue resistance of steel rails for the railroad industry.

But they have many years of experience in all kinds of committees. There's more than 130 committees operating within ASTM. The agency works with more than two dozen different ASTM committees and E55 is just the most recent of the committees that FDA has worked with in ASTM to accomplish our standardization objectives.

ASTM is a recognized developer of international standards. If you look around the world, more than 44 countries have written ASTM standards into the national codes, so we believe that ASTM is an engine for accomplishing an awful lot of the objectives the previous speaker mentioned. The difficulty with the resources problem in many parts of the world is that the resources are scarce to accomplish the changes that everybody wants to achieve here and with ASTM being a globally recognized developer, we hope that some of these will be eased.

Finally, their offices are close. They're up in -- just outside Philadelphia, up between Philadelphia and Valley Forge and it's a speed run up the road. We can be there in about three and a half hours, so it enables us to go up there, consult with the staff managers up there on activities that we need for standards development and also we've held several meetings in their facilities up there and it's a speed run up and down the road for staff.

The history of our working with these folks is very brief. It's almost a year that we've been working with ASTM to develop standards for PAT. You can see the calendar here, it really got organized in February of this year and it took about four months to have the first standard published through this consensus process. There's a terminology standard, E2363 and there's more than 70 terms already agreed to by the consensus process in this standard and the standard is being revised as we speak. More terms are being added, terms that their needed discussion in the first cycle of approval for that standard are being revised and added as we speak.

The next meeting well be in November here in Washington and it will be part of the standard ASTM committee week. It will be over at the Omni Shorham Hotel over on Calvert Street. And I encourage anybody and everybody who is in the room and wishes to participate in the process to get engaged and I'll have a slide at the end that tells how. This is how the committee is organized. There's really three functional committees; Sub 1 on management, Sub 2 on implementation and practices and Sub 91 on terminology. The Sub 90 committee is just a kind of organizational thing that you need to do to have a committee to keep the train running on time. But the activities of these committees, when we sat down to talk about this, we realized there were a few activities that were easy to talk about, to break out as separate entities, materials, operating equipment, control the environment, people training, analytical equipment and control systems, transport and storage of packaging and package parts and packaged pharmaceuticals as well as the management of the processing and packaging and obviously the systems infra-structure at the bottom, what the plant needs to make it work.

I didn't see the second -- the operations and maintenance systems, there's an awful lot of things of that type that can be standardized. The initial work items, you see there on the left-hand margin there is a work effort ongoing. WI is work item. There's a work item to develop some standards for raw materials, another one for manufacturing equipment and finally, a work item on instrumentation. These are the three active work areas. We anticipate that as some of these things are accomplished, that the committee will move onto some of the other activities. So the items that you see there in detail are all managed in E55-02. This was the implementation and practices subcommittee and overall, there's an over-reaching management system being discussed, a management systems standard being discussed in E55-01, the first of the subcommittees that I mentioned and the objective here, obviously, is to have a unified system and E55-01, an umbrella document and a bunch -- several, many E55-02 implementation documents to reflect the best practices.

Some of the -- the overall effort will be to describe and accomplish a work plan and describe and accomplish and enable the outcomes. As I mentioned before, we would like people to participate. The agency has a pretty heavy commitment to making this work. I am the chairman of E55 and some of my colleagues here in the Center for Drugs are active on the three committees that I mentioned previously, the three subcommittees. Interestingly the senior management of all the other subcommittees are industry people. They are members of the regulated industry and actually have taken their responsibility every seriously about their roles in managing the activities of development of standards for PAT. And contacting Pat Picariello at ASTM is a clean easy way to get into the system. They have a website also, astm.org and E55 has a link in the website, so that if you want to go see what's being done and what the status of things is, it's an easy access to the information. And I'll answer any questions. And I missed by a minute.

CHAIR BOEHLERT: Very good, nevertheless. Any questions in E55? G.K.?

DR. RAJU: Don, I really value the due process in which you operate and we certainly hope to live up to the expectations in all these meetings. As you look at the rest of our discussion around ICH and you look at the compliment in terms of resources internationally, on one side that's a positive thing. Do you see any duplication possibly in the future in terms of ASTM doing things and ICH doing things given how long it takes for the government. It's tough to look at duplication after the product is over and if there is some, does it get managed with the people more common or is it done structurally with people like you?

MR. MARLOWE: It is actually -- I think it is actually done best with the people that are involved. I think that it's unlikely that there would be some kind of a super management system of the whole thing, but I do think that the exercise within ASTM will be a detail exercise, not an overall quality system management discussion. So there will be a discussion on best practices for management of PAT within a manufacturing facility where the regulated industry, the firms, get to share their best practices but the overall impact of that and the overall role that that would play in a quality system management plan for a firm will not be on the table in ASTM. That will be an ICH discussion.

CHAIR BOEHLERT: Any other questions or comments?

MR. MARLOWE: Thank you, ma'am.

CHAIR BOEHLERT: Thank you, Don.

MR. MARLOWE: Appreciate it.

CHAIR BOEHLERT: And we are right on time so I thank you for your effort on our behalf. We're scheduled for a 15-minute break and we'll reconvene promptly at 10:45.

(A brief recess was taken.)

CHAIR BOEHLERT: Okay, it looks like we have all members present and accounted for. Now we're going to change directions a little bit and we're going to be educated hopefully, on Bayesian statistics. Nozer, ti's all yours.

DR. SINGPURWALLA: Well, thank you for the opportunity or the imposition to give this talk. Let's see, okay, thank you. Well, the good news is that I've given this talk about -- this is the third time I'm giving this talk in the last two weeks which is fortunate because I was asked a few days ago by Sandia Labs to give a talk on Bayesian statistics and things like that. Then I was in Iran giving the same talk and Los Alamos Labs wants me to give this talk again, so I've got a package that I can keep talking and talking and talking about.

Now, the motivation why I was invited at Sandia to give this talk is that there is a large group of individuals who are thinking in terms of alternatives to probability. And so they wanted me to talk about this topic and particularly as applied to reliability and fortunately, Ajaz mentioned the word "reliability" so I feel slightly comfortable talking about it but basically the title of this talk is "Reliability for the Analysis of Risk" and it is a Bayesian perspective.

So these are my coordinates and this is mostly based on a book that I'm working on for a long time. So first let me start with proper definitions. Everything has to be defined so that there is no confusion of vocabulary. So the first question is, what is reliability and why is reliability relevant to this particular community? It's -- this is some spy is ringing the phone.

Okay, so it's the quantification of a certain type of uncertainty associated with the efficacy and safety of a large complex system to include biological systems where it goes under the name of "Survival Analysis". So your drug -- sorry? The drug manufacturing is also a large complex system and it doesn't matter what the complex system is, but basically, reliability is the quantification of uncertainty.

The next question is, why do we need reliability, why reliability? Well, it is one of the two necessary ingredients for making logical decisions in the face of uncertainty connected with the efficacy and safety of large systems. So reliability is one of the two ingredients that we really need to make logical decisions no matter what the decision is, whether to administer a certain drug or whether to manufacture a certain drug or how to manufacture the drug, it doesn't matter.

What is the other ingredient? The other ingredient is utility and utility is a very difficult concept to essentially make precise but most of the time when we talk about utility, we talked about costs and our rewards that occur as a consequence of any chosen decision. So every time you make a decision, there are going to be consequences and associated with the consequence there is either going to be a risk or -- I'm sorry, I shouldn't use the word "risk". There is either going to be a cost, a penalty, or there's going to be a reward.

So the next question comes up, is what do we mean by risk analysis? We've heard this term used repeatedly in this particular audience and I think I would like to see risk analysis as the process assessing reliabilities and utilities and it should include the identification of the consequences. So risk analysis is the process of assessing the reliability and the utility and think of reliability as a probability. Think of reliability as a probability but let's keep it specific.

And it should include the identification of all the consequences.

The next question comes up why must we quantify uncertainty? Why this business of quantification? Why not just do things? Managers essentially make decisions without quantifying, you know. Generals make big wartime decisions without quantifying. Why not just go ahead and do it based on whim. Well, I'm not saying that by doing things on whim you won't do the right things but essentially formally, by quantification we mean the measurement of uncertainty and by measurement we mean a comparison against a scale. For example, we use feet for distance and pounds for weight, so what we need to do is really we need to come with a scale to measure uncertainty. We are uncertain, we have to have a scale to measure uncertainty because we want to quantify uncertainty.

And measurement is a necessary ingredient for invoking the logical method and mathematics is a logical method and I'm sure there may be others but I only know of one. Because without measuring, we cannot talk about it as said very nicely by Lord Kelvin several years ago. So we need to quantify so that we can invoke the logical method and without quantification, we really can't talk about anything systematically. Thus, to quantify uncertainty we need a scale of measurement.

So the basis problem is we are uncertain about certain things. We need to quantify it and to quantify we need a scale and so the question comes up what is the scale. What is the scale for measuring, what is the fortrula (phonetic), what is the weight for measuring uncertainty? So what are the scales for measuring uncertainty? Well, probability is the oldest and perhaps the most commonly used case. There are alternatives to probability that are popping up on the horizon with a lot of passion and with a lot of debate but sometimes without much content. And these alternatives are possibilities and as this community gets more and more into this game, I won't be surprised if 10 years down the line, there will be an Ajaz Hussain standing up and saying, "We should use possibility", so I want to caution you that there is a scale that's lurking on the horizon.

There is also another scale, it's called belief. There is another scale called plausibility. There is another scale called fuzzy measures. Confidence limit and point estimate is also a scale, but probability is the oldest and perhaps the most commonly used scale. Well, the questions comes up is if you are advocating probability as a scale, why it should be the scale, what about these other possibilities and beliefs and so on and so forth? Confidence limits, the FDA uses them. Point estimates, the FDA uses them. We think these are alternatives to probability. So what are the strengths of probability?

Well, the first strength is it has a foundation that is firmly grounded in coherent behavior -- coherent betting and the axioms of coherent behavior. So there is a foundation behind probability that is firmly grounded in coherent betting. Coherent betting simply means you don't go to Las Vegas purely with the intention of losing money. You're hoping to come out ahead. So any time you gamble, there should be a fair chance of also winning. And axioms of coherent behavior it's a long story but human beings behave in certain ways and the calculus of probability is grounded.

But the more important reason, particularly germane to this particular activity, is that it's calculus leads us to a prescription for decision making under uncertainty. Most of you in business and industry are decision makers. So you need to make decisions and you need to make logical good decisions, how you're going to do it. Well, it says that the calculus of probability and I'll tell you what the calculus means, leads you to a prescription for decision making under uncertainty. The others to the best of my knowledge, do not have a similar prescription.

So the next question comes up, if that be the case, why are there alternatives to probability? Well, this is a technical issue and I won't go through the details of this but the axiomitization of probability, the legitimization of probability from a mathematical point of view is based on a certain structure which some people find is very rigid and therefore, they propose alternatives to probability, but we won't go into the details but to the best of my knowledge, the alternatives do not have a behavioristic foundation and do not lead to a prescription for making decisions.

Also some alternatives lead to answers that are inadmissible. That simply means you get silly answers, answers that fall flat in terms of common sense. But I'd like to make some qualifying comments and slowly we should get to that. As a word of caution, the axioms of coherent behavior upon which probability and its calculus are based are set to be normative. That means they tell us how to behave. In actual individuals may not behave according to the dictates of normative behavior. We have plenty of examples. People do silly things. I like to drink alcohol every day in the evening. I know it's bad for me but I do it. So that's not normative behavior. I'm told not to do it, but I do it and there are other examples. I've done some recent work with my colleague, Jane Booker, who is at Los Alamos Labs, and we have been able to overcome some of these objections. Again, I won't go through the details.

All right, so that much for some background. And now the main question, what is Bayesian inference which is what you all want to learn or those of you who know about it simply find all of this very trivial. Those of you who don't know, wonder why all this is happening. So what is Bayesian inference? Well, the answer is very simple, Judy, extremely simple. And the answer is this; when the quantification of uncertainty is solely based on probability and its calculus, inference is said to be Bayesian. So to be a Bayesian simply means following probability and the rules of probability. And of course, it's not easy to understand the rules and it's not easy to work with it, but as a general statement, if you are purely going to describe uncertainty, and measure uncertainty using the calculus of probability, you are a Bayesian. Any time you violate from that, you're not a Bayesian.

In other words, a Bayesian is strict in his or her adherence to the rules of probability. That's it. It's not very hard to be a Bayesian. Well, of course, within the class of Bayesians there are categories and I'm just putting this down. One are called Objectivists and the other are called Subject Matter Specialists. The Objectivists, the spokespersons for that particular school were Jeffreys, a British astronomer, mathematician, philosopher. Jaynes was a an American physicist, passed away recently and LaPlace, you all know who he was.

So they wanted everything to be objective and they simply said, "We should quantify uncertainty using probability but we should not have any personal opinions coming into the picture and what we need are standards by which we can work". Of course, this particular school was criticized. In fact, La Place was severely criticized for doing this and essentially La Place suffered a tarnishing of his reputation. Then there are the subject matter specialists and the biggest proponents of that school are De Finetti, Savage and Lindley, who happens to be my co-author and friend. They basically are of the opinion that to quantify uncertainty you really have to understand the subject; drug manufacturing, engineering, economics, physics, whatever have you. You have to really get into the guts of the subject in order to be a good Bayesian. That was basically the idea.

There is a long debate about it and a long -- so, what is non-Bayesian inference? Well, it's the opposite of Bayesian inference; any process of uncertainty quantification that does not fully subscribe to the calculus of probabilities so labeled. Well, of these, Frequentist Inference is the most prevalent. In the FDA and in NIH and in government, Frequentist Inference is the most prevalent. All your military standards; 404, 105D, a lot of your control charts, quality control procedures, the old ones, the Shoehart (phonetic) chart, Quinsome (phonetic) charts, they all Frequentist and a Bayesian would reject them, including Deming, who at some times rejected them not because he was a Bayesian but he was using his common sense.

Now, why is there Frequentist Inference? Frequentists, while subscribing to the notion of probability as a metric for quantifying uncertainty, interpret probability in such a way that sometimes they have to forsake probability as the sole basis for quantifying uncertainty. Well, I just mentioned probability but there are many ways to interpret probability and if I had the whole day, I would go into all those particular issues but I've been given only 45 minutes. Fortunately, they are during the morning. I was scheduled to speak in the evening when all of you would be either gone or asleep or if you were awake, you would fall asleep. But we've been moved up and there is a long reason why all this happens.

So I'm just going to put up one little picture as a schemata of what's going on. So here we have the quantification of uncertainty and we basically have two groups. One group says probability is the metric. Then there is another group that has possibility, belief, confidence intervals, and all as metrics for confine uncertainty. Within this particular group, you have the objective Bayesians, we have the subject matter Bayesians and then we have the Frequentists or Sample Theoretic people and it's a kind of a strange box here because this box has an arrow here and also an arrow here. This particular proponents of this, most statisticians that I know and I was trained as a Frequentist, essentially use probability as a metric but the interpretation of probability at some point in time drives us into this particular box. So that's the schemata.

Well, that's an overview and that's a general statement. Well, the best way I can illustrate all this is by a very simple example and in the course of the example I will define what I mean by risk and I will also define what I mean by utility and this is what you would call risk based decision making or whatever verbiage you use. The simple example that I will use is the simple example that I've always been successful using for the general audience because everybody flies, takes an airplane, including myself and you're faced with a decision. And what brought this to my attention is I was on a committee of the National Academy of Engineering or Science or whatever on certification of aircraft and I was dealing with a lot of people who manufactured huge, big, powerful engines which take this plane up and the particular individual who was on this committee was a very fine gentleman from Boeing who was responsible for putting two engines on the Boeing 777. So that was a big decision why they built this plane with only two engines when the classical jumbo jets had four engines, so how did they make this decision to use two engines?

Well, they didn't use decision theory to be quite honest with you. They didn't use what I'm prescribing but I had to talk to him and tell him this is how I would go about doing it. So I'm going to give you that example. So the example here is should we outfit a newly designed airplane with one engine or with two engines? Now, when you're manufacturing drugs at Pfizer or wherever have you, I'm sure you have a lot of decisions to make. You can translate this into your own particular problem. So how should we go about looking at this particular problem?

Well, I'm not going to put numbers because I'm very uncomfortable with numbers, so let's C1 be the cost of acquiring and installing an engine. Risk analysis is the most important thing are two ingredients, probabilities and utilities. Utilities are costs. Probabilities are probabilities no matter how you interpret them, those two things are the most important elements of making risk informed decision making or whatever verbiage you use. So C1 is the cost of acquiring and installing an engine. This is slightly loose. C2 is the loss incurred due to an aircraft failure. So if the airplane fails because you don't have enough engines, you're going to suffer a big loss, I just called it C2 and I call this C1.

And I'm assuming that C2 is much bigger than C1 because a loss, if an airplane goes down, is going to be much more than cost of putting an engine. You know, it keeps running and running and running. Let C1 be the reward received upon successful flight. So every time you carry passengers from Tehran to London, which is what I flew and then back from London here, they collect effort from. So this is -- just measures the air flow. All right, now comes the next component and again, it's all laid out in notation, P1 is the probability of failure of an engine during its mission. There's a probability that the engine will fail and I do faultry analysis, failure modes on effects analysis. I do all kinds of things, collect data, collect expert judgment, talk to the fellows who design these engines, blah, blah, blah, and come up with a number P1 as the probability that a single engine will fail. Well, I have two engines so P2 is the probability of failure of both engines. So you know, one engine can fail and there is a certain probability, and P2 is the probability that both engines fail and when both engines fail, we have a bit of a problem. How do we calculate P2? It's a big complicated question. I have simply multiplied P1 by P2 which is what old-fashioned individuals in the industry were doing.

They were assuming that the chances of failure -- that the failure of one engine doesn't increase the chance of failure of the second engine. So they were just multiplying it and they got into ridiculous problems doing this. But I've just put P2. Now, the next question is, so this is a part of risk analysis, getting this P1 and P2 and C1, C2 and C is all a part of risk analysis. But also a part of risk analysis is the consequences to each decision. What is the consequence in this simple example? Either we succeed, which is S, or we fail which is F. So there are two consequences. It again, illustrative. There are other ways to look at this in much more detail but I'm just giving you a general sense of what needs to be done. If you want to move forward in this business, these are the kind of thinking that should come into play.

So we start by constructing a decision tree. Again, there is fancy vocabulary here used by different people. The last meeting we had they used some other term which was more acceptable to others but basically you had a constructive decision tree. So let's look at the decision tree. And this is the guts of everything. We have to make a decision and that's called a decision node, D. The decision maker, the engine designer, the airplane designer has to make a decision. So she has two choices. She uses a single engine, which is decision D1 or she uses two engines which is decision D2. So those are the only choices she's allowed.

Now, as soon as she makes her choice, nature comes into play, that's called R1 to denote the random node. What is nature going to do? Either it's going to result in a success or it's going to result in a failure. This is not a game because you're making a decision against a benevolent nature. In a game, when you want to use this in the context of strategic issues, you have an opponent who is kind of active, but this is a passive opponent. So you either result in a success S, or an a failure, F. Then you have to outline your utilities. The utility of a success when you make decision D1 is USD1. The utility of a failure when you make Decision D1 is UFD1. P1 is the probability of failure, remember I did that before and one minus P1 is the probability of success.

Again the rules of probability say that if this is P1, this should be one minus P1, so you have the utilities here. Similarly, you do this at this node, the second node, that is you have chosen two engines and then at least one engine survives. We assume that with one engine the airplane can fly and we assume that with both engines failing the airplane comes down. In actuality, it doesn't, it glides down, but we just assume that it's a failure and then there is a utility associated with those two. So any risk informed decision making you want to make, if you're not going to come up with a good decision tree, then you're just doing it in a haphazard way. This is the important step that you have to go through and the important step involves a lot of important sub-steps.

You have to calculate your probabilities. You have to calculate your utilities and you have to outline what the consequences are. Here I have only two consequences, S and P1. Well, the rest of it is all mechanical calculations but I'll illustrate what the calculations are. At this random note, R1 we compute the expected utility of decision D1. This expected utility is called, by definition, the risk. This is the risk of decision D1. It's the expected utility. What do we mean by that? It's the -- the following calculation is the utility of success when you choose decision D1 multiplied by the probability of the success plus the utility of the failure when you use Decision D1 multiplied by the probability of failure.

So this expected utility is calculated by R1 and I, of course, should also write here saying that this is what is called the risk of decision D1. This is the definition of risk, expected utility. And that's why I made a comment to the previous -- one of the previous speakers what it means. Well, these are just numbers. You don't have to worry about it but these utilities I have set down in terms of costs. Of course, discomfort to a passenger also is a form of utility and we need to quantify that and that's going to be very important especially in the drug business where you can take some kind of a medicine and have side effects. It cures your disease, but you feel lousy. How do you put a value to it?

Well, that's the more difficult part but somehow you had to come up with a value and I have simply used dollars and cents to encapsulate this. Similarly, you do this at R2. You do exactly the same at R2 and you compute the expected utility at the second node. And again, I have these numbers. You don't need to go through the details but you have to compute the expected utility at this node and at this node. Then the beauty of all this is this principle of maximization of expected utility, MEU. It says, use decision D2, namely two engines if the expected utility, that is the cost multiplied by the probability, added over the two consequences, exceeds the one for decision D1. Otherwise choose decision D1 which is a single engine. So all you have to do is construct the tree, not easy but this is where you have to work with the correct scientists and the correct people, elicit probabilities, which is where most statisticians would play a role, elicit utilities which is where economists, managers, marketers and others would play a role and compute expected utilities and choose that decision for which the expected utility is the highest.

Well, these are some notes because the audience I was talking to was engineers who always like to dabble with numbers and always like to pull out their calculators and punch a few digits, seven digits off to the decimal point and brag about it. We don't want to do this here. So here's a commentary. The role of probabilities and utilities in making decisions is clear. The more important point is this; that it is the calculus of probability that leads us to the maximization of expected utility as a prescription for taking action. So there is probability and there are rules of probability which would be the next topic if I were continuing this talk but just so that you may know that it's the rules of probability that lead you to the maximization of expected utility.

The alternatives to probability need to provide a similar prescription. I don't think they have one and they need to come up with one before the alternatives could be. Okay, the above plus the fact that the calculus of probability has an axiomatic foundation that is grounded in coherent betting and behavioristic rules is the strongest argument in favor of the Bayesian paradigm so why should we be a Bayesian? Because it's the calculus of probability that leads you to a prescription for making decisions and that the calculus of probability and probability as a metric for measuring uncertainty had a foundation that is grounded in so many other things.

Now, a lot of people like to be Bayesians. The fact that the Bayesian recipe can address problems like one of a kind system. Suppose you've designed a new airplane where there has been not trial runs, do you make a decision to fly it or if you want to send a spaceship to the moon, you have not sent spaceships before, should you decide it or not, that's a one of a kind system.

Information fusion, the Bayesian -- the calculus of probability allows you to fuse information systematically, rather than doing it in an ad hoc way, the ability to make predictions. Savings on sample size are simply desirable by-products. There are a lot of by-products that are very desirable but the key argument for advocating a Bayesian point of view is philosophical and mathematical. The key reason is to have a sound philosophy and sound mathematics. The fact that there are some nice by-products should not be the driving argument. That's just something which is desirable.

But there are some issues and what are those? But this philosophic disposition also entails a price to be paid. It takes the form of two issues. So you want to be philosophically clean and clear but you have to pay a price. And what is the price? The actual behavior of humans is not always normative. We don't do things which we are supposed to do always. We get more pleasure doing things that we are not supposed to do and maybe pleasure is a part of our utility but we -- there is a specification of the prior that comes into this business, posses difficulties and my previous meetings here at the FDA and other places the big flag raised against the Bayesians is the prior. You'll hear the word, "But the prior, where do we get the prior for". Because to get the prior you need to understand the underlying science and engineering or the economic theory so statisticians don't like to get involved, at least some of them, don't like to get involved in physics or chemistry or pharmacy or economics. They just want to do what they're trained to do.

But this particular paradigm requires that you start talking to your scientific colleagues in other disciplines and that becomes an issue. The other more important issue is that the priors may not be unique. My prior and your prior may not agree and, again, it's a big topic of discussion. Why it is so, we won't go into it but the Bayesians have an answer to this and what is the answer of the Bayesians? Well, the answers are the following. The first answer is that the behavioristic axioms dictate how one ought to behavior. They're a prescription for rational behavior. The Bayesian says, "This is how you should behave. The fact that you don't shouldn't be a criticism of the paradigm".

The second more harsh reaction is that one has no business working on a problem that one does not understand, thus studying the underlying science and engineering is a desirable thing. And the basic argument is whether you're testing an engineering unit for success or failure should not be viewed in the same vein as studying the sex of newborn babies, whether they are male or female. There has been studies, you know, what proportion of newborns are males or females and there is also this same similar issue of testing for success or failure. You shouldn't look at those, both those problems in the same vein. One has genetics and biology; the other one has physics and other things going into it.

Non-Bayesian methods lead to inferences that are inadmissible and this is a heavy price to pay. And here are some examples of non -- of inadmissible answers. You can get estimates of failure rates and densities that are negative. You're estimating something which by definition is a positive quantity and you can produce estimates that are negative and engineers will simply reject that answer. Well, you get confidence limits that are silly. I won't go through the details, and you can also get into this trap. Perhaps more important for the FDA, you are testing some kind of a drug for acceptance or rejection, approval or non-approval. A capricious individual, a capricious organization, can manipulate the process in such a way that you will accept bad things.

So in the context of military standard 781(c), sequential live testing, there is a nice example where a manufacturer of bad products can sell the government the bad product by completely following the rules but by behaving in a certain capricious manner. I won't go through the details but just as an example.

Thus, as a matter of principle, some do not use procedures that could lead to a trap, even if the alternative procedures demand more of the user such as specifying a prior. And the other point I want to make is there's no known situation wherein the use of a Bayesian approach has resulted in an inadmissible solution or an inconsistent estimate. In other words, the Bayesian solution is a safe bet once a prior has been agreed upon. And the main important problem is eliciting priors which seems to be the main job of a statistician; namely, you elicit priors to estimate probabilities and of course, it's a big enterprise which is what we need to work on and I have -- this talk goes on for the whole day but I'm not going to punish you, nor am I going to give you a test which is what I promised Helen, so I'm going to spare you in the hopes that -- okay.

I have all this on a disk which the people at Sandia were kind enough to transcribe to a disk, so I'm not going to give you all the 80 slides. I can provide 19 slides but this is just a casual conversational overview. There is a lot behind this and there is a lot that needs to be done but my only advice to you, Ajaz, is unless you take a specific problem, simple as it is, and work it through, you cannot lead the way. We are simply otherwise talking about what needs to be done. Sit down, take a problem and work it step by step perhaps in collaboration with industry, get the whole group together, just to see how this needs to be done, thank you. Bye.

(Applause)

CHAIR BOEHLERT: Thank you very much, Nozer. Are there any questions or comments? Yes, G.K.

DR. SINGPURWALLA: G.K., yes.

DR. RAJU: Nozer, have you seen people at Boeing or -- ever use this successfully?

DR. SINGPURWALLA: Oh, yeah.

DR. RAJU: And what is the benefits, what has been their experience?

DR. SINGPURWALLA: Well, since you asked the question, the subject of reliability was invented at Boeing. They invented the idea of fault trees. Well, it's part of the game.

DR. RAJU: Is it strictly Bayesian influence, Bayesian decision?

DR. SINGPURWALLA: Well, I'll tell you what, Boeing Laboratories closed about 20 years ago. So I can't talk about Boeing any more. I can only say one thing, that they invented the Bayesian -- I'm sorry, they invented the fault trees, failure modes and reliability. They contributed fantastically to it. Where I see this happening mostly is right now at the labs, at the national labs, there is a lot of passion one way or the other, for this and there is a lot of activity going on in this.

Of course, people in business have used it quite a bit. People in oil exploration have used it, you know. There are pockets of resistance but I think the pockets of resistance are losing the battle.

DR. RAJU: The arguments from the purists is the traditional --

DR. SINGPURWALLA: No, no, we are the purists. The argument from the impurist, okay. As long as we get it right.

DR. RAJU: The FMEA that the aerospace industry started are not truly Bayesian and you can't really multiply them because they haven't really been formulated as probabilities. I mean, this is --

DR. SINGPURWALLA: FEMA?

DR. RAJU: FMEA.

DR. SINGPURWALLA: Failure modes and effects analysis is a strictly engineering function. What they do is they say that the airplane has failed, why did it fail? Was it the engine or was it the pilot? If it was the pilot, why did the pilot fail? Did he have an alcoholic drink or was he upset and if it's the engine, was it the wings? You know, they go through and trace the whole process. So that's the failure modes and effects analysis.

Now, when you design a new airplane, you want to calculate the probability that it will be successful, so you have to first lay out the whole scenario, that's the failure mode and effects analysis, then work your way up calculating the probabilities. Now, people make mistakes. What's the biggest mistake they make? They multiply probabilities when, in fact, they shouldn't. So here's a classic example. Take the Boeing 777, the Boeing 747. It's got zillions of parts. Each part had a probability of failure. If you multiply all those probabilities, then the probability of success of the airplane goes down to zero, yet the airplane flies. So immediately the reaction was something is wrong with our calculations. So the big criticism is not Bayesian methods and don't confuse Bayesian methods with calculating probabilities, you know.

If you don't calculate your probabilities correctly, you are going to get silly answers. So I think the big question is, how to do it correctly. It's very difficult, time consuming and demanding, but there are certain rules which have been -- obvious rules which have been violated and that is the biggest problem.

Any other comments? Ajaz?

DR. HUSSAIN: No, I think if I recall the discussions we had at one of the previous meetings, probably the main advisory committee meeting where we discussed the zero tolerance and we discussed the traditional confidence and --

DR. SINGPURWALLA: That's right, that's right.

DR. HUSSAIN: -- confidence and criteria for bio-equivalence and so forth.

DR. SINGPURWALLA: And we changed?

DR. HUSSAIN: Right, and I think could you put this in that framework? What are the advantages of moving away from that type of approach to something that uses a Bayesian type of approach?

DR. SINGPURWALLA: Well, let me give you an example of why you shouldn't use confidence limits, okay? And this is going to be a quiz, Ajaz because that's how you're going to learn. I have -- X is the height of all men in this room. And suppose X is distributed normally with some mean -- don't even worry about normal, there is some mean MU1. Y is the height of all women in this room and they're also normally distributed like us, thank God, otherwise we'd be accused of sexism, and their mean is MU2. Okay, the height of men is MU1, the height of women is MU2.

And for some reason, some crazy statistician wants to estimate the ratio of MU1 over MU2, the height of men over the average height. And he calls that RO and he computes confidence limits on RO. Does all his calculations nicely, computes confidence limits and he comes and says the following. "I've computed the confidence limits. They are minus infinity to plus infinity and the probability of coverage is 99 percent". Will you buy that? No, it has to be one. That's the kind of answer you'll produce. So there are certain traps that you can fall into. Now, it doesn't mean that you'll always fall into a trap. Sometimes you'll fall into a trap but once you fall into a trap, you have to be careful because you don't know where the next trap is.

There's another reason. The meaning of confidence limits is itself a convoluted idea. A confidence limit when you calculate, doesn't tell you anything about the particular scenario. It says, if you repeated this process over and over and over again, 95 percent of the time you'll get what you want, whereas the Bayesian response is, "Well, I'm not interested in the, you know, 99 other scenarios that I have not seen. I'm more interested in this particular scenario". That's why you should get away from them. But they are very strongly ingrained into our culture and that's the reason why we have this. So the particular meeting that we had, we advocated a decision -- they used another language, but basically this is what they were doing. Thank you. Any other comments?

DR. HUSSAIN: Just one more, one of the other aspects, we had a two-day workshop on this, at FDA at Johns Hopkins University.

DR. SINGPURWALLA: I'm familiar with that. I mean, I'm familiar with the characters that go to the workshop.

DR. HUSSAIN: Right, and our sister center CDRH has been using Bayesian approaches.

DR. SINGPURWALLA: For equipment only.

DR. HUSSAIN: Right. In the context of what we are talking about ICH Q8, Q9 and so forth, I think one of the attraction that leads me to seek more information and probably more research in this area for myself and for FDA is use of priors because prior knowledge and use of prior information to make better decisions is the opportunity, I think, I see of --

DR. SINGPURWALLA: That's right.

DR. HUSSAIN: How can -- can you share some more thoughts on that?

DR. SINGPURWALLA: Yeah. First is, I want to criticize you with no prejudice, of course. You should not be a Bayesian because you could use prior information, no, no. You should be a Bayesian because it's logically closed and coherent. Now, the fact that it allows you to use prior information is certainly a big advantage because you're going to save on the amount of testing and so on and so forth. The danger is bad prior information could also lead you astray. So getting an honest and honorable period is going to be an activity and there are methods by which you elicit prior information from people who are subject matter specialists and experts and codify it very carefully.

There are methods and there is a large body of literature to do it. There is also a philosophic position and that is the following. That any Bayesian analysis is the analysis done by either an individual or as a group of individuals -- as a group acting as a whole and it's their best judgment. So it's completely possible that given the same data, and given the same information, one group can come up with a certain conclusion and another group can come up with a different conclusion because they have different prior knowledge and different priors.

That people find objectionable. They want one answer to run across the board. So that is a criticism. So I don't know if I've answered your question but getting prior information is an essential step and there have been efforts to get away from this ever since the days of La Place and right now there is a large body of Bayesians in this country actively growing, who are trying to get away from the prior information and come up with canned priors.

Most of the pure Bayesians reject them as, you know, not being to the spirit of what is intended here. So there is a big activity but there are methods by which you can elicit and quote prior information and that's where the research effort should be going. The prior information plus the data gives you the probabilities. Utilities is another big very important subject, particularly in the drug context because there are side effects which are uncomfortable. The drug industry has a very serious problem in terms of utilities. It's not just dollars and cents. It's more than that, so I think those two are the key important steps. Another question?

DR. MORRIS: Yeah, so if I understand correctly then, so if your risk is the weighted average of the utilities weighted by the probabilities --

DR. SINGPURWALLA: That's right.

DR. MORRIS: -- and if we don't really have priors, as you say, if there's an absence of priors or in some cases maybe the data that have been collected aren't really critical attributes and don't really reflect the utility or -- so you can't really calculate a probability I guess, then are you basically saying that that's -- you can't really apply the Bayesian methods until that's the case?

DR. SINGPURWALLA: No, thank you.

DR. MORRIS: So --

DR. SINGPURWALLA: Okay, I got the gist of your question.

DR. MORRIS: Okay.

DR. SINGPURWALLA: And it's because I just didn't make one thing clear. It is true that you have to calculate the weighted average, utility multiplied by probability. How do you get the probability? There are two schools of thought, the Bayesian and the non-Bayesian. Okay? The Bayesian says you must have a prior to calculate the probability. The non-Bayesian says well, the priors could be subject, non-unique and therefore, we should only have data to calculate it. The Bayesian said, you need the prior and the data to calculate the probability. The non-Bayesian simply says, you only need the data and no prior, okay?

But once you've calculated the probability, both the Bayesian and the non-Bayesian will use the same prescription. The only flaw here is that the non-Bayesian, in using the prescription, essentially uses the calculus of probability and the calculus of probability demands that you have a prior. It's slightly, you know, elaborate to explain but both will do the same thing.

Decision theory has been practiced even by non-Bayesians, okay, but the foundation for it comes from the Bayesian thought process. Simply being a Bayesian means following the rules of probability.

CHAIR BOEHLERT: Okay, any other questions or comments? Nozer, thanks very much.

DR. SINGPURWALLA: Sure.

CHAIR BOEHLERT: Our last speaker before lunch is Dr. Ajaz Hussain.

DR. HUSSAIN: I wanted this to be sort of filling the gap to some degree but I think it's an important topic. It's again, an awareness topic that we wanted to sort of put on your radar screen. We probably will discuss this in detail at a subsequent meeting but I do want to sort of bring an awareness of this initiative to you as a critical path initiative and I'll focus on the industrialization dimension.

The key aspects here I think, I hope you had an opportunity to at least look at the executive summary of this initiative document or the White Paper that we issued recently. The key focus area is innovational stagnation. I think we are trying to examine this and challenges and opportunities on the critical path to new medical products. The finding that I think as a nation both private and public funding for research and biomedical research has been growing quite significantly over the years but the translation of all that basic research to products for the patients seems to be not in sync and that's what we were trying to examine and at the same time the cost of new drug development seems to keep skyrocketing.

And there are different figures out there, 800 to $1.7 billion and so forth. So from a regulatory perspective, I think what we feel is the critical path which is from the prototype design to the approval of that, is not receiving adequate attention from the research community and even from the academic community and this could become or is becoming a bottleneck to new drug development. So the critical path that we have identified and defined is an area which has not been receiving the attention with respect to new methodologies, more efficient methodologies, and research in development of drug products and medical products.

So if you really look at it from a new drug development improving efficiency of drug development and review, new development is a high risk and highly costly enterprise and it's often due to the high failure rate that we see. And can we do better? And I think we must do better is the theme that we are trying to move forward. There is a plan to issue a list of projects that we thing are the high priority projects in both safety efficacy and industrialization. And the feeling is strong that the current process is not sustainable if you want to maintain a robust pharmaceutical industry to meet the public health needs of the U.S.

With that in mind, I want to focus on the three dimensions of the critical path initiative, the one on industrialization which goes from the physical design of the prototype to characterization small scale production, manufacturing, scale up and mass production. If you really look at the challenges we face today in conventional materials and dosage forms, tablets, capsules and so forth, the functionality of exigence, the availability of exigence, the characterization is still a big gap, we don't understand all of those things, but as we move forward to its nanotechnology, nanomaterials, the physics becomes more and more important and we are not able to address physics adequately for our conventional materials, so a challenge in the complexity is going to be much greater.

So how does -- this is simply to sort of remind us what the current state is. Research and training needs from both the national perspective as well as the perspective of FDA, I think, is clearly a topic for discussion that we want to sort of bring forward and have it in a public forum. The question I have is our nation's education and research infrastructure, is it adequate to meet the critical path challenges? To me that answer is a clearly sounding no. And I say that from two perspectives.

One is before coming to the agency, I came -- spent nine years in teaching so very familiar with the academic situation in the U.S. The society essentially has decided that the role of pharmacy from pharmacists in the U.S. is going to be of a drug information, patient care. So the schools of pharmacy which used to have a program and the rigors of physical and analytical sciences in those programs has completely be gone. So schools of pharmacy, the pharmacy graduates coming out of schools of pharmacy in the U.S. actually often do not qualify to fund the PhD program. In fact, I would prefer not to use them because they don't have the physical grounding necessary.

So schools of pharmacy, the industrial pharmacy programs in the U.S. are really incapable of meeting the needs of this nation. And I've said that. Some people have disagreed with that but I think that's -- I strongly feel about that. And I think there is a need to focus or take our focus on more of a pharmaceutical engineering type of curriculum and there is a need for center for excellence in pharmaceutical engineering, education and research.

Now, how do we sort of promote that? Several schools have contacted us, schools of pharmacy and in collaboration with schools of engineering have contacted FDA that they would like FDA to work with them in developing such a center. And I think we have a strong interest in that and we will meet and we are meeting with these schools to see how we can support this. But clearly, the critical path initiative document was intended to bring this issue at a level for public discussion, debate, so the society can decide how well to fund this area because a lot of this information, a lot of the science and a lot of the knowledge that needs to be created has to be a public data base. It cannot be a private enterprise.

So I think I would like you to sort of think about and if you have towards the end or right after my talk how should FDA support the case for a focused effort on pharmaceutical engineering? We have met with ISPE, International Society for Pharmaceutical Engineers, and politely I said, there's not much pharmaceutical engineering there. So we need to bring more pharmaceutical engineering in that and actually have a workshop on the topic of pharmaceutical engineering and the national need for this focus. So please think about this and please share your thoughts on how we should proceed.

We will be meeting with schools of pharmacy and engineering who have interest in this and try to explore this possibility. I think clearly from an internal FDA perspective, I think next several months we will have to put a research agenda together. We are right now focused on the Office of Pharmaceutical Science on the industrialization dimension, so what are the research and training needs of FDA?

I think from a research perspective, we have been sort of collecting a set of topics, projects, or topic areas for research and realignment of our research programs and clearly the PAT research program that we have initiated, some internally, some on collaboration, for example, the collaboration with Pfizer, we are exploring other collaborations with other companies, too, that will be part of this critical path initiative but we are, as I speak, have a group of people meeting with NCI, National Cancer Institute, on looking at collaboration on physical characterization of nanomaterials and physical and biological characterization, so we're moving in that area of physical characterization of nanomaterials.

Clearly we have an interest in computational methodologies. Office of Pharmaceutical Science has a wonderful group of bioinformatics with respect to toxicology. We have done some work with respect to use of prior information and use of export systems in terms of formulation but that has been limited. There's an opportunity for that. There's an opportunity -- actually, we are putting together a very strong chemometrics group. We already have a few people. We're hiring a few more to include computational fluid dynomix (phonetic) and include all elements that I think would be needed to bring a sound computational basis for CMC aspects. I think our other aspect is support for generic drugs, efficient methods for bioequivalence (phonetic) is clearly one of the aspect, but I think as we move forward in the critical path, I see blurring or actually increasing the challenge of what is pharmaceutical equivalence and how do you define bioequivalence, so our focus will be on that and in fact, we will have to probably take up the topic of what is pharmaceutical equivalence soon because I think there is an opportunity to align that and to streamline that and to actually make it more simpler because today a tablet is not pharmaceutically equal to a capsule but if you put a tablet inside a capsule, it's pharmaceutically equal. So we have logical ways of defining this. I think we need to sort of pick that up.

So all of this sort of comes together as a research program that we have Mon Surhan (phonetic) in the room. We just hired him from the University of Texas and I think he and Cindy Busey (phonetic) are focusing on the industrialization dimension. So this year's program planning for research, I think, we will really focus on this. Jerry Collins and others are clearly focused on the clinical side of it. So here's an opportunity but you also have a chance to sort of give us your thoughts, what are the project topics that we really should consider, these are the broad areas that we are working on and developing a research program to meet these needs.

Clearly, the training needs are equally important, the pharmaceutical inspector training program, the critical elements development that we start next month, the training program, but also training of the CMC review staff that Moheb will talk to you about. And I think we will have to have a systematic way of doing that, especially if you have to alleviate some of the concerns John Berridge raised and how do you address these things.

So just I'll stop here and put these two questions on your radar screen. Anytime you have suggestions and so forth, please send these to us. Thank you.

(Applause)

CHAIR BOEHLERT: Thank you, Ajaz. Any questions or comments for Ajaz? Ken?

DR. MORRIS: Yeah, just a comment and this is not news to Ajaz. I'll apologize in advance for repeating it but to get it as part of the record, I think one of the historical issues has been separate from FDA or industry and that is that NIH and NSF just don't view the kind of research that we're talking about as fundamental enough to be treated by them and they expect the pharmaceutical industry to shoulder the burden of that and that's historically, I think, why the departments, particularly at the graduate level, have had to abandon the sort of research so that they could maintain funding in other areas.

So I think that's -- not to just express regrets but to say that in the future if we can bring pressure to bear as I know you guys have already talked to -- Helen and Ajaz both have already talked to folks in the other agencies, but if we can bring pressure to bear so that they understand that significance of this both financially and in terms of public health, can only help.

CHAIR BOEHLERT: Any other questions or comments?

DR. SINGPURWALLA: Yeah, I was just going to pursue the point that was raised by my colleague here. I'm just curious. Work that needs to be done which is of interest to the FDA, why should the NSF put money into it? Am I correct in articulating that?

DR. MORRIS: Well, I guess what I would say is that the disconnect hasn't been that it's work that's needed by the FDA. The disconnect has been their recognition of this as a relatively fundamental set of research topics that need to be addressed in general. I think, just as we draw largely on material science and biology and the other disciplines to bring into pharmaceutics, there are specific aspects of -- in my particular case, of course, I'm narrowed by the scope of my research. For instance, if you look at material science literature, very little of it deals with small molecular organic molecules.

So it's not like you can go to the book and grab the fundamental theories to be able to be used on these sorts of compounds necessarily. And they've just not historically recognized the value of this and the broad significance of scientific endeavor.

CHAIR BOEHLERT: Any other questions or comments?

DR. PECK: Yes.

CHAIR BOEHLERT: Yes, Garnet?

DR. PECK: Well, that's not what I was going to talk about but I'll say it anyway. Several years ago we applied to NSF a rather, what we thought a rather good grant proposal to study the fundamentals of corn starch. And the only way that that grant was eliminated was the fact that corn starch is not a uniform material. We were trying to find out why it wasn't uniform and what kind of physical properties we could measure and we had a methodology that was proposed but they couldn't fathom why we would look at this very variable material, how important was it to our particular endeavors and at the time that was the major disintegrating agent in most of our pharmaceutical tablets.

We simply wanted to understand it more. So NSF turned us down and we did something else. Concerning what Ajaz said, I have to be very careful, Ajaz. You may know of my feelings and some of them are historical. I'm not convinced that our solution is in pharmaceutical engineering. If we consider basic engineering programs, at least the ones I'm aware of, the amount of biological education that is provided those individuals is very limited. You hit on something that has to do with pharmaceutics and the fundamentals of pharmaceutics which gave us those tools to bring along new drug delivery systems for the patient.

But it was aided by this sensitivity to where the products were going. I'm having trouble right now coping with pharmaceutical engineering programs. There are so many excuses why we cannot open up the programs and that's going to be a major, major hurdle with doing what is needed. As you have noted, we have to change in our fundamental programs, in our graduate programs. So you have identified the needs and that's great, but some of those that have control over what we can do have to loosen up. That is a concern that I have.

DR. HUSSAIN: I think your point is well-made and well-taken that just an engineering approach is inadequate and not sufficient. I totally agree with that. And therefore, I think the pharmaceutical engineering curriculum itself will have to sort of bring together the key elements and not looking at that as a purely engineering discipline. It has to bring the fundamentals of chemistry, biology, and engineering all together and that's something which is not present in our curriculums in the U.S.

But if I start looking outside the U.S., you see a very strong push for these comprehensive programs, especially in China, and more so in Japan coming through quite vigorously in a sense. So I think the challenge here is this; the community, the pharmaceutical community is a very small community. If you look at the American Institute of Chemical Engineers, it's a huge community. If you look at American Association of Chemists, it's very huge, but the subset that is interested in the pharmaceutical industry is often small. So you need to maintain that identity. The industrial pharmacy programs and the pharmacy school programs were successful in sort of meeting those needs, but now the societal needs and the societal demands, supply and demand is such that look at BS degrees that you have either in chemistry or even pharmacy BS degrees that Purdue has, you create a scenario where the professional pharmacist and their salary structure is so dramatically different so it's not sustainable from attracting the strongest candidates to your program.

The pharmaceutical engineering as a team provides a means to create that identity, provides a means to create that resource structure and attraction for students then focus on that. So we will have to develop the curriculum that is needed to meet the needs. So your point is well-taken, Garnet.

CHAIR BOEHLERT: Any other questions or comments? If not, I'd like to thank all of this morning's speakers. We are right on time. We will break for lunch and reconvene again at 1:00 p.m. I'd just mention, members of the committee, we've made arrangements for lunch and Bob King will be escorting us, right, to the place, our destination.

(Whereupon at 12:01 p.m. a luncheon recess was taken.)

A-F-T-E-R-N-O-O-N S-E-S-S-I-O-N

1:03 p.m.

CHAIR BOEHLERT: Good afternoon everybody and welcome back. We're going to start this afternoon with some introductory comments by Ajaz Hussain followed immediately by Ajaz and his presentation. G.K. will come after Ajaz.

MEMBER HUSSAIN: I think the afternoon session will hopefully provide the Committee with more information and more substantial information to help answer some of the questions we have posed.

The thought process of putting this afternoon session was to still take a look at some of the opportunities and what we have been able to accomplish with respect to the concepts that we have developed.

And then have share some thoughts from Moheb Nasr and Gary Buehler because these individuals are responsible for managing the day-to-day activities and some of the challenges they face. And what are they planning to do in helping us moved towards the "desired state".

So you'll see different levels of activities while they're trying to manage the day-to-day activities, how do we move towards the "desired state".

And following that discussion, I've invited Ken Morris to come and speak to you about his experience in helping us think about this and helping us move towards what I would like to call a question-based review process.

And I like that term because it helps us to hopefully focus on asking the right question. Question-based review process is actually in place in our Office of Clinical Pharmacology and Biopharmaceutics. And I actually like it quite a bit where you simply, clearly identify what are the questions to be addressed; and then focus your review around those questions.

And I think we have an opportunity in the CMC world to do the same. And so Ken has been working at it with the CMC leadership within the Office of Pharmaceutical Science, debating, discussing. So he, I think, is the right person to share some of his thoughts with you before you get into your deliberations and discussions.

So that's the agenda for this afternoon.

After listening to the discussions this morning, especially with respect to some of the discussions with the design space and some of the opportunities, for example, Dan, you raised the issue if you have understood this range of conditions work fine, why don't you sort of take advantage of that?

And I think that's what we are trying to do in Q8. I see as Q8, from my perspective, is trying to harmonize different regulations in Europe, U.S., and Japan with respect to changes or variations by changing what is -- how we define change.

For example, if you have a range of studies done, and you understand the range is not critical, so why not redefine that as not being a change? So that's, I think, what we're trying to achieve.

So keeping that in mind, I'll share with you some of my thoughts on specifications. Some challenges and opportunities in the enhancement of CMC sections of NDA's quality by design is how to set specifications.

And I was planning to speak after G.K. Raju but I think listening to this might help you because I think G.K. is going to talk to you about the wonderful opportunity we have from the knowledge-sharing perspective.

So with that in mind, I'd like to sort of again repeat that I think the opportunity is therefore companies that acquire extensive understanding about the product and manufacturing processes and share this with the regulators, that helps us to be -- enhance our science and risk-based regulatory quality assessment in setting specifications, reduction in volume of data to be submitted replaced by more knowledge-based submissions, and flexible plus continuous improvement.

In fact, I think our goal is to move towards the state where you have one cycle review, CMC review, and essentially everything is banished in the GMP inspection site in the continuous improvement.

And I think this is the desired state that is possible. And I think Dr. Woodcock's presentation, which is in your handout, she has continued to think about this. And her latest presentation on quality by design I think is quite telling in the sense this is a proactive approach on how you approach the development and how you approach specification settings.

Quality by design stipulates or postulates key performance parameters early in the development process. Now this is based on what we know at that point plus your prior information. And then you design product and processes to be robust around for these parameters.

But the challenge today, as John Berridge discussed some of this in his presentation, without adequate product and process development and/or knowledge sharing, you have high levels of uncertainty with respect to critical attributes, what is critical and what is not critical.

And when you have that high level of uncertainty, we often have to make decisions conservatively. If you don't know, everything is critical then.

And also I think the questions that we struggle with is is the sample size representative, in representative disc samples and adequacy of risk coverage? Example, compendial discs to assure batch quality.

So those are the regulatory risks or concerns that our reviewers are trying to minimize through their approach to specification setting. In absence of extensive understanding of product or process factors, you have to make a conservative decision.

I think reduced concerned risk by covering all apparent attributes with acceptance criteria based on capability of test methods and/or manufacturing process plus very inflexible SOP that sort of follow from that. So that's the current way of sort of doing business of current regulatory risk mitigation strategy.

But I think I wanted to illustrate some of this using a current situation on distribution attribute. Now there are many, many guidances that sort of you have to look at to glean this information but I won't be able to do all of that for you today.

But I just wanted to sort of share with the ICH Q6A decision tree and how it sort of addresses the resolution and why I think the current state tends to be testing to document quality. And in ICH Q8, we're moving toward the desired state where we are trying to get to a quality by design.

The biopharmaceutics classification system, the BA/BE guidance, the SUPAC guidance, and the dissolution guidance itself are sort of interconnected. Unfortunately we don't have the time to share with you all of those connections that I have sort of worked out.

But let me start with the Q6A decision tree. The first question that we asked in this decision tree does the dissolution significantly effect bioviability? If the answer is yes, we develop test conditions and acceptance criteria to distinguish batches with unacceptable bioviability.

If the answer is no, we go down this decision tree to say do changes in formulation or manufacturing variables effect dissolution? If the answer is no, we go down to adopt appropriate test conditions and acceptance criteria without regard to discriminating power to pass all clinically acceptable batches.

But if the answer was yes, are these changes controlled by another procedure and acceptance criteria? If the answer is yes, we come back to the previous result. If the answer was no, adopt test conditions and acceptance criteria which can distinguish these changes. Generally, single point acceptance criteria acceptable.

Now, I have inserted some questions. How? How do we know dissolution significantly effects bioviability? Okay? There are wonderful studies that are done in Phase I, Phase II which actually show you so much information.

For example, one typical that is carried out is a related bioviability study solution was established. We actually do not use that effectively in our decision-making. Often you will see a solution perfectly superimposable to a solid dilution essentially saying dissolution is not great limiting. Okay? So we know that that happens in many cases but not in all cases.

But then the solubility, the particle size, dissolution rate, all can give you the signal. We don't utilize that information today.

So often our answer is yes, dissolution is an important attribute. It is an important attribute and we have to control it using a dissolution test.

And the many questions that how, what, why, and so forth that you see on this chart are not fully addressed but not only the information is scattered throughout the NDA submission but also I think we often don't have time to pull all this together in a concise way to answer these questions.

And, therefore, we often set specifications because that is the tradition.

Suppose I go down this route, dissolution does not significantly effect bioviability. Should we be asking the question do changes in formulation or manufacturing variables effect dissolution?

Why would we ask that question?

The answer is for over shelf life, over the period of shelf life, there might be change which might not be apparent in the release.

All right. But then we establish a dissolution criteria using a dissolution test. So that's the current situation.

And here are three examples, more recent examples of how we set specifications. Now these are three very recent examples. And here are the reviewer comments, three different ideas.

Without adequate product development and/or knowledge sharing, we debate frequently. So one of the last decisions we might do is this is your specification to the end of the NDA review cycle, this is what our decision might be. And you often have no choice but to accept it.

So here is the first comment. The reviewer recommends tighter dissolution specification. Q of 80 percent in 30 minutes. And in this case, it was based on, you know, what the clinical batches were.

And if you go down the list, they say the sponsor-recommended dissolution specification method was unacceptable. We simply say the sponsor's Q of 70 percent is too low. The direct product that releases only 70% is likely to be bioequaled -- is less likely to be bioequaled than a product that releases 100 percent.

Therefore, we recommend a Q of 80 percent. Sometimes that Q of 80 percent may not be actually a profile point in this, the total example. Therefore, we propose the sponsor's specification of Q of 80 percent at 60 minutes should be changed to specification of Q of 80 percent in 30 minutes.

Much of this discussion is based on three, four, five batches that we see in the new drug development. We do not bring the systematic thinking with respect to the physical, chemical properties of the drug, the formulation, the disintegration mechanism of any of them. That's not really fully utilized today.

And then what I say here is we have cGMP problems. Here is a warning letter. An inspection of your drug facility, blah, blah, blah, there is no assurance that written production and process control procedure established for coating are sufficient to produce a product that has the quality it purports or represents to possess.

The duration of coating cycle as determined by the pan operators is based on a visual determination that coating solutions are even distributed before proceeding to the next step.

It should be noted that it was hundreds of batches. So the numbers are not small here. A number of batches made in `97 or `98 were rejected due to in-process distribution failures.

And then you go on to the partial release of various products even though there was not data to invalidate all the specification results. And so forth, and so forth. This is catastrophic. And this is not a small company. This is one of the major companies.

So what happens is, I think, every aspect of our regulatory is interconnected. And G.K. Raju, his data has always shown us in the sense that, you know, all the specification results are a significant -- they contribute a significant increase in cycle times and so forth.

And here is a couple of examples that I took from his slides. But here also many of these are physical attributes, dissolution. And what I would argue is many of these are physical attributes that -- where we have struggled with.

Dissolution is not the worse case scenario. I would say when it comes to particle size, gasket compacture, and others, you have significant measurement variability that you have to deal with.

But let's look at this. Testing to document quality clearly requires a less variable test method. Here is the data from our lab in St. Louis. The current USP 10 milligram Prednisone caliber tablets exhibit slow dissolution over time. It's not a stable caliber. It keeps changing.

So if the acceptable test equipment calibration limit is 28 to 54, and if you often live with our F2 criteria, which is an average of six, and then you compare the two average profiles, and that average profile should not be more than ten percent different between the pre-change and post-change, what do we see?

The calibration limit far exceeds that but that's what we have been practicing for years. So what can we say about the use of F2 criteria where the mean profile difference that we accept is ten percent or less as a way to document and change quality?

And if you look at the table there, the table from two different data sets, the shift in the stability of this calibrate, so if I look at calibration as a means to say this is my target, that's giving me a target value, even the mean estimate, the point estimate is questionable with this method.

And just to summarize the dissolution experience at the FDA's Division of Pharmaceutical Analysis, dissolution testing with USB Apparatus 1 and 2 requires diligent attention to details, both mechanical and chemical, dual response can respond differently to small variation in apparatus setup or degassing, large difference in dissolution results are possible unless all parameters are carefully controlled.

The experience at Division of Pharmaceutical Analysis, FDS St. Louis indicates that differences in reproducibility can often be traced to improper mechanical calibration and/or degassing.

And we have a situation where we often have to reject, recall batches, because of minor dissolution failures. And we have no good means of getting out of that trap that I think we are in.

And this is not new. Our Canadian colleagues, Health Canada, has been talking about this for years. And this is from 1992. We often see false positives and false negatives in some of our measurement systems.

And here is just one example. I'm not going to explain that but Ian Miggelri, and he used to be at Health Canada, published this some time ago.

Now, just to continue the thought processes that are so entrenched in testing to document quality, and we often ignore all the prior information and we focus on the test results, is a reason for thinking -- of major thinking.

Here is another example from the Q6A decision tree. I just want to illustrate two points from this. Now the question I want to illustrate from this is do we always need a dissolution test for every solid dosage form? The answer is yes currently.

But I think Q6A opened the door to say not necessarily. Although I'm not too pleased what Q6A recommends, a disintegration test instead of dissolution, which is probably far worse than that. I think there is a better way to deal with this.

In Decision 3, No. 71, it says the product is not modified release, the drug has high solubility, the product has rapid dissolution, then you ask the question has a relationship been established between disintegration and dissolution?

If so, then you might want to go to a disintegration test instead of a dissolution test. Now in Europe, this is acceptable. I don't think we have approved a single one in the U.S.

But the point I want to make here is just pay attention to that. We're focused not on understanding the product, not on understanding the process. We are trying to create comparison between two different tests, a disintegration test and a dissolution test.

And the reality is this. If you are familiar with the disintegration test, you have a cube with a 10 mesh screen which goes up and down. So you put a tablet and that goes up and down. And you just look at the time when all the tablet fragments have passed through the sieve.

So in this case, the table is disintegrating into larger chunks to small chunks at a point where you stop and say the tablet has disintegrated. The total dissolution of that is throughout the surface, larger particles, smallest particles and so forth. So dissolution can continue after disintegration is over.

Now the point to illustrate here is this, they're twofold. One, we are comparing apparatus -- dissolution apparatus to that of a disintegration apparatus. The hydrodynamics are different and the medium might be different. That's not a true comparison. That's not a quality comparison per se. But that's fine.

The other aspect here is, I think, the hesitation that we often have is now, yes, there is a risk associated here by moving to a disintegration test because dissolution continues even after the disintegration time is over. The reason a risk could be polymorphic transitions. You may see polymorphic transitions and a disintegration test might not ever pick it up, correct?

So these are sort of the questions that I think with good science, what we have talked about in Q8, we can address some of these questions in a submission. But not today because we don't have all this information to really make a rational decision.

Testing to document quality, the face has many dimensions. It is applied as in process and end product release and stability testing. So the reliability of specification is a key question because, I think, we look at that in absence of process understanding.

Managing post-approval change and continuous improvement is a challenge. And I showed you just one aspect of the F2 metric and what challenges it poses. Product and process knowledge acquisition and generalization is also challenged because now you are relying on a traditional wet test to -- and if you're trying to do a design of experiment, that's a humongous resource commitment in the time it takes to do these tests.

So how can pharmaceutical development knowledge help? How can we demonstrate quality was designed in, specifications based on mechanistic understanding, continuous "real time" assurance of quality, and flexible continuous improvement.

I think the Q8, the Q9, and the overall Q10 are all trying to move in this direction to answer these questions. What I would hope to see, and this is for debate, discussion, and so forth.

This is the same decision tree that I showed you earlier from Q6A but now, from a design -- quality by design perspective, dissolution significantly effect bioviability, that's a design question.

You postulate that based on the characterization of your API or drug substance. You know the solubility and you know the pKa, you know so you have a knowledge based on how this molecule might behave. And so you postulate.

And then throughout your development program, you confirm based on mechanisms and/or empirically. So that product design applies to those two decision trees that you have.

At the same time, from a risk perspective, if we understand the PKPD of this, we will have a better focus maybe towards the end of the drug development process, not at Phase I, Phase II, but towards the end of the NDA submission process, what is acceptable? What is not acceptable bioviability?

Today, the answer is anything outside of 80 to 125 is, by virtue, an acceptable bioviability. And that's a wonderful clinical pharmacology question of what that question is.

So once you have that, you start answering this question, design for manufacturing and controls or design of manufacturing and controls and how reliable are these because the second decision diamond that you have, do changes in formulation or manufacturing variables effect dissolution? Right?

If the answer is yes currently, are these changes controlled by another procedure or acceptance criteria? If the answer is yes, you still go back to the dissolution test step. My answer to that question would be is that really necessary? With this scientific knowledge base and so forth, can we do better?

So those questions can be brought to bear on this. An overall, risk-based CMC, why can be asked. I think a reviewer should ask why do need this? Why do you need redundant system? What is the value of this? And so forth.

But also I think we need to find ways to answer the question so what. Now if the virtue of, I think, what I have learned from a quality system is you have to focus on the voice of the customer. Now if dissolution does not significantly effect bioviability, if a drug is highly soluble, and this is a rapidly disintegrating drug, is that a critical variable?

I think today we'll answer always yes. Dissolution is an important attribute, no doubt about that. But a test? Is that important? I think we have to start thinking about so what? And the so what has many, many connections. What is acceptable? And so forth.

I think overall CMC systems approach that Moheb will talk to you about, I think he's starting to think about this as a quality systems assessment program. And it's to sort of bring the connections and the Q8 offers that opportunity to link the morphic form particle size stability failure mechanisms to ask those questions why and then how.

So based on quality of pharmaceutical development knowledge, can we not evaluate overall CMC systems approach, that is link to morphic form particle size stability failure mechanisms and address the concerns and risks? Is dissolution specification needed? Instead of wet dissolution test can we use disintegration test?

I don't like that personally but that's a valid question. Real time release and stability based on process controls and say NIR tests, capsules and so forth.

The key is, I think, we all understand that not all information is mandatory. We are okay with this. And we are work in the ICH to avoid a two different system model. Instead we are moving towards one system with different levels of quality by design.

And you'll see that, I think, in different offices you'll have different levels of process understanding. And so forth.

The challenges we face. Common approach to a more clear articulation of not all information is mandatory. We seek your help on that, I think, in the questions we have posed.

Improved process understanding and control technologies may afford reduction in regulatory requirements. That's the design space concept that that's coming about.

And I think the key is and in most relationships it is expected between effectiveness of the quality by design and risk to patient being exposed to product that is not fit for use. That's something that will need to evolve.

And I think what we are moving forward is hopefully ensuring continuous improvement and a process for continuous learning and updating of this knowledge base.

So with that, I'll stop. And I have -- invite G.K. to share his thoughts on it.

CHAIR BOEHLERT: Are there any questions or comments for Ajaz?

Yes, Nozer?

MEMBER SINGPURWALLA: Ajaz, I'd like to make a comment.

MEMBER HUSSAIN: Yes?

MEMBER SINGPURWALLA: Just to keep the notation and the language clearer and clean. What you have is not a decision tree. What you have is an event tree. A decision tree is one where you make a decision. What you have is a flow of event as they occur.

So just so that we don't, in the future, confuse, you should really call it an event tree.

MEMBER HUSSAIN: Unfortunately, I can't change the ICH.

(Laughter.)

MEMBER SINGPURWALLA: Change it.

CHAIR BOEHLERT: Any other questions or comments?

(No response.)

CHAIR BOEHLERT: Okay, before we begin with G.K., I would just like to note for the record that there is no open hearing this afternoon because, indeed, there were no people that requested time.

So having said that, G.K., it's all yours.

MEMBER RAJU: Thanks, Judy. And thanks, Ajaz, for the opportunity to present today.

I'm going to try to talk about manufacturing science and knowledge and in some ways build on what I presented before in this general audience. And I think in many ways compliment the presentations of here today.

The outline for my talk, I'm going to frame manufacturing and science within a broader social context. Once I have a frame, I'll define some vocabulary. Hopefully, Nozer will approve of the vocabulary. And use that vocabulary to then describe the desired --

CHAIR BOEHLERT: G.K., G.K., you may need to get closer to the mike.

MEMBER RAJU: Sure, okay.

Once I've defined the current and the desired state, I then use that vocabulary to define leverages to go from here to there. Implications of those leverages, possible next steps given those implications for the leverages and, of course, acknowledgments because we stand on broad shoulders.

The frame that I'm going to use for the rest of my talk is to say that pharmaceutical manufacturing is not really something you do inside a plant in a company. It really is a social capability that has resulted from a set of choices that we have made, all of us as patients.

So all of us here are patients. But all of us as patients have made decisions about risk, what is a good release? How does it work? And how much are we going to pay for it?

The government, who has decided to fund certain kind of research, and if Ken wasn't happy that they didn't fund other kinds of research, the pharmaceutical industry that has decided to focus on product innovation and in doing so has made a tradeoff about process innovation. And academia, who has decided to have all their tenured professors to focus on everything except pharmaceutical engineering.

(Laughter.)

MEMBER RAJU: And so all of us are stakeholders in this broader society as if we could go with what Ken said. And in the end, inside that plant, in the broader social structure, somebody is making these drugs that we consume.

So I'm going to try to frame it in that sense and now let's look deeper with that frame. Given that frame, let's define a vocabulary. The first set of vocabulary is around science. It was the first thing that Ajaz wanted to include in my talk.

And interestingly science is both a noun and a process, in some ways something active and it's doing. And there is the process of scientific inquiry. And there is an extent of science which is what you know at any point in time.

Given that, and we've defined manufacturing science in the past, you can then go to the next word in your definition and say once you have science down, how about the word system. A system is a set of processes and broader systems, including people, with a common material and information flow.

The way I define system, the manufacturing system is very much connected with the quality system. They're not two different things. They're almost the same thing although there are reasons to be different in that particular industry. So the second piece of vocabulary is now in place.

Here is a set of manufacturing systems that you could have. I'm going to call them A, B, C, D, and E. That's pretty obvious. That's how I learned the alphabet. And given these classes of manufacturing systems, let's look at what our manufacturing system looks like as we go to the rest of the talk and move forward.

The third piece of vocabulary is the word capability. I'm going to define given the frame that pharmaceuticals is a social capability to have manufacturing capability to be defined consistent with that frame. Manufacturing capability is the ratio of the voice of the customer to the voice of the process.

And we, as a society, have focused on how much, what is important to us in terms of one, the patient who says what is important to him is safety, efficacy, and availability, the regulator who we as a society decided that their role is to assure that safety, efficacy, and availability, the head of that operation who only wants to do better because that's how his job is really about, the CEO who focuses on not only the effectiveness, that is he wants all of these customers to get what they want but he also wants to do that with an efficient allocation of resources, and the scientist in all of us, not just the academic who simply wants to understand because that's just the reason why he exists.

And so we have a hierarchy of customers, each of which has a voice. And we as a society decides which of these voices will be heard and we invest. And we make the investment.

What shows up after many, many years, is the voice of the process. That simply said, this is what you've invested. This is what the society is giving you back in terms of its inherent variability of its process.

That then is the manufacturing capability in the world, in the United States, in our group of industries, in our segments of industries.

With those three pieces of vocabulary, which is manufacturing science, manufacturing system, and manufacturing capability, let's now define where you want to be in the context of this desired state that we heard five or six times on the previous slides earlier today.

What did we say the desired state was? We saw the FDA desired state. And we had the industry come up and say you can put industry here. We want the same thing. What is that same thing? That same thing is that we give the customer what he wants with a deep amount of understanding in our designs to make sure he always gets it. So we're not even worried about him any more at the bottom of the pyramid.

It says we understand the mechanistic basis why something happens and we try to understand the first principles of that knowledge. You can argue that this is an unreachable state. We're still trying to find out first principles. We believed in Newton, in Isaac Newton. Here comes all of these new things with nanotechnology that says maybe Newton misled us. But at least he took us so far.

So this is an evolving thing. It's about a domain. It's about a set of questions. This is the first principles for pharmaceutical manufacturing as we know it.

The desired state is dynamic. That is we want to be at that level in society but we get to that level one product at a time based on the product we're making now. And that's the development process and that's the continuous improvement process.

Strategically, you'd like to have society have laid the foundation of that knowledge so that you already start with the generic mechanistic understanding, understand the basic causal variables. You adapt it to your own new drug.

You're already starting so high and then you do a little bit of development here and then you're at that level. You should have no supplements to file. That's the design space that you saw in the earlier presentation from Ajaz.

The other alternative is to say society has laid all of that foundation great but I'm not going to invest in going too high too far ahead of time because this is enough to ensure safety and efficacy.

I am going to work with my commercial plant and I'm going to continue to improve. Because the basic foundations are in place, I may or may not have to make any submissions even in this case because the foundation of mechanistic knowledge is available in the greater social structure.

That's where we'd like to be. If you translate that's where we'd like to be from a knowledge point of view into what do we want our manufacturing system to be, I'd like to argue that we'd like to have much simpler processes.

Today, much of our processes look like System B. What we'd like is processes that have few steps. They have a lot of automated control. And maybe we won't even have to do the final product release testing if we've laid the foundation of knowledge that has been institutionalized into our system and shows up in our capability.

The current state, however, seems to reflect -- at some point this is personal opinion, of course, that the level of our knowledge in pharmaceutical engineering is at a basically correlative and descriptive level.

It's a consequence of the broader social investment in it that shows up in academia and, therefore, in research, and a greater industrial investment and a customer prioritization about what he wants in a pharmaceutical and its regulation and what he thinks the FDA should do if it needs to exist in the first place.

Given this is where we are from a knowledge point of view, what is the dynamics of that knowledge? The dynamics of that knowledge is we stay at that level of knowledge and we stay at that level of knowledge from the beginning to the end. So this is what I call a social structure that has a learning disability.

And we need to overcome this learning disability by saying from a system point of view, this is what our system looks like. We have a system where the causes are far away from the effects. And we can't correlate them. And so we can't get to causality and so we can't climb this family of manufacturing systems.

We spend 25 days testing here. And we have a cause organization that is separate from it. We need to transform this system which is the result of social decisions made in the past.

What is that transformation about? It's about two choices which really are about when you do that transformation. You could do that transformation in development, which is the strategic leverage, which is learning before doing. You do all this improvement, change your manufacturing system to be E or D during development.

Or simply the other alternative is to do that during commercial manufacturing if we've laid a body of knowledge already in place, you might still be able to do that.

But what shall we do today when we haven't laid that body of knowledge in place? And our processes look like this. And we all agree on the desired state that we want to look like this. What are the leverages that make us go from this unsatisfactory position to here? And you saw Ajaz present the benefits of getting to this higher state.

That is how are we going to all work together during manufacturing or during development given this body of knowledge to climb up this portfolio of manufacturing systems? Why is it important to do? One of the leverages -- and I'll take one leverage.

In this case, I'm going to choose the tactical leverage instead of the strategic leverage, which, I think, you've heard a lot about in the morning. Let me talk about the tactical leverage.

That is let's climb this set of manufacturing systems during manufacturing if we can. Why is this important? A number of pharmaceutical companies have warning letters. And what is the most cited component of these warning letters over the last few years? It's about the quality. It's about investigations of the broader quality system.

Let's think about an investigation around some real data. Here is the solution. And as a broader social structure, you have to first ask the question is this a critical quality variable? If we had asked this question and socially invested in the answering of this question, I would have either had yes here for this graph or I wouldn't have a graph because we wouldn't have this variable.

But because we didn't answer this question over the last 25 years, I have this graph. And I have this question on the graph. First question.

Second, because I'm not even sure about this, the next question that remains, what is its specification? If this and this had been laid in place ahead of time, I wouldn't even have to show them on this graph. So let's put them out because they are strategic leverage questions.

Let's ask the tactical leverage question. The tactical leverage to climb up the pyramid, not the question that's about releasing a batch. I'm not asking the question should you release a batch. The answer to that in today's vocabulary is easy.

I'm asking the question if we are going to use knowledge as a basis for changing the way regulation is done in our social structure because we can't pay the price for it, we've got to climb up the knowledge pyramid and here are the questions we have to answer for ourselves to be able to climb that knowledge pyramid.

First, are these data representative of the underlying reality? Is this the solution really the dissolution of the one million capsules it's meant to represent?

As part of that, there's a sampling question but it's also a measurement question that Ajaz talked about. Is that measurement an appropriate measurement of dissolution and the way it was done? So this is a sampling and testing measurement.

Two, have I seen this before? Learning disability is about seeing the same thing and giving the same reaction and not able to separate that you haven't understood and prevented it. That's a knowledge management question. That's about have I seen it before? Can I go back to a past answer?

What is this variation? Is this somehow inherently different from all of this variation? Or is this simply a little bit of variation put together showing up in a general pattern that regresses that? Is this a special cause? Or is this just natural or common cause or normal cause?

This is the whole basis of SPC and Shewhart's theory where he spent many, many decades of his life teaching us about how to answer these questions and how to ask these questions.

Is this process capable? Capable of meeting which customer's needs? The patient's needs? The regulator's needs? The head of manufacturing who simply want to do better? The scientist's needs who want to understand why?

And then have we put in a place an effective, corrective, and preventative action here so that this doesn't happen here?

If we're going to use a knowledge-based and science-based approach to manufacturing in the future, then answering each of these questions should be a piece of science just list each of the clinical trials and their publications are pieces of science. That is if we are to climb that pyramid, it should be based on building blocks that have significant scientific quality.

Small scientific studies about sampling and testing not for release but for process understanding. How much you sample and what should be your measurement technology to climb that pyramid? And you are going to come up with very different questions when you're asking the climb the pyramid question versus release question.

How do I know? What is the body of knowledge? What is the scientific study that I have to put in place to say this is special cause variability versus common cause variability?

What is the basic building block of science in this overall pyramid that allows me to put in place effective, corrective, and preventative action that makes me climb up to System E so I don't see that again.

And the bigger questions that I put in a different color are how do we answer and put pieces of science ahead of time in the development context? Investigations, small leverage in manufacturing. And that's 90 percent of our products today. We must focus on the strategic leverage one part at a time.

But the opportunity in manufacturing is to build these blocks of science around investigations, around technology transfer, around process characterization. And this is the basis on which we get regulatory relief. But beyond that, satisfy the higher customers in our overall social capability structure.

This is one way of climbing up this family of manufacturing systems and reaching one that is much more independent of the broader social structure, much more independent of the operators as this is highly automated.

And that is the basis for completely eliminating any of those warning letters or even having to see the investigator because no one want to really see him.

Implications of the vocabulary and the leverages are first the vocabulary provides a positive position. It doesn't matter what word you use but if you use the word science, the customer likes it, the regulator likes it, the patient loves it, the government likes it, maybe NSF doesn't like it in some cases. They all like it. It's a positive word. And so is capability.

It's an enabling vocabulary because it's something that's so general. And we all like good science. And it's all about a broader community of understanding that I think it is the basis of collaboration among all these four stakeholders. To work together for this broader social structure of understanding.

Three, it's a basis for a very different relationship with the regulators. If you think about academia as saying let me start with some general glass beads instead of reality and try to understand if I can explain reality that is starting with first principles and trying to see if they explain any data and really industry that starts with today's data and try to understand it better.

Causal knowledge in the middle is the middle of the top down and the bottom up strategy that says let's look at using some of these research exemptions and these safe harbors that are put in place in the PAT guidance to really work together between the regulator and the regulated to truly understand the root causes in these investigations including bringing in new measurements to do that.

In doing so, that would lay the foundation to climbing up the pyramid and making of the regulator quite irrelevant. But while doing so, this is the opportunity and the guidance is an opportunity to start going deeper than today's root causes.

And guess what? That fits perfectly, that vocabulary fits perfectly with the current momentum around the FDA, cGMP in the 21st century. The critical path takes it further as well.

Not only is this one of the components of their four-pronged components for the 21st century, but it is the fundamental basis for risk. Risk analysis is a scientific process. It is a fundamental process through manufacturing system for modern quality management techniques and science.

And you heard the Q8 and the Q9 discussion. What did they say? They said we can get this a lot more harmonized. This is a lot more difficult to harmonize.

Remember what Fred said? Science is the underlying theme that is also going to be the more powerful framework in which to harmonize because of the very reason that everybody has a positive, enabling view about it. And this is a very powerful foundation that the FDA has laid.

Five, science is a basis for the collaboration among competitors. It's very difficult to climb that pyramid in development when you are in a hurry to push out a product. You are always going to hear every company say that.

What is missing in that conclusion is the presumption that you can't learn from all your past products and you can't learn from all the other companies that do the same set of things again and again. That is can you learn through science and publications about excipients that are more than 50 percent of your products that you all share?

Could you learn from the fact that you've been doing this for 12 years in a row? And can you capture that knowledge which is your priors?

Science to collect to your past and to collect with your competitors to get out of that dysfunction that says I only have a year so I can't move up the pyramid. You only have a year in the boundary that you've drawn for yourself.

And finally, science is about going into the very process that gives us all the rewards that we want as regulators. It is the benefit. It is the fastest way to generate the products that we need. It is the basis for true process understanding, for the academics, for the regulators, and the broader CEO to ultimately get back his economic rewards as well.

Those economic rewards lay the foundation for enhanced manufacturing capability that allows all of the different stakeholders to achieve all their needs, that is the voices of the different customers, and lays the foundation as a social structure for a complete reversal of where we spend resources.

If you go back to the last 25 years and you look at where we, as a society, are spending resources in terms of QC and QA and regulatory people, and the FDA, and the investigators, you could say maybe the qualitative direction is clear. Maybe the units are tough to figure out. This is clearly on the wrong track.

And when we design it then, which is quality by design, let's spend the next 25 years reversing back, go back to the same basic level so that all these resources, including the industry, can focus on bringing in new products.

The next steps for the next 25 years, given that the cGMP initiative is coming to its two-year cycle and an end in a month that is based on many years of history before that, first is to broaden the shared vision. We saw the FDA put us a vision. We had the industry come back and say I agree with that vision.

We can now connect this vision to the CEOs. If this is a social capability, how are we going to bring them into this? With the government, which might impact decisions about funding, for example, a long-term social map.

At this time, we have good intentions. We're beginning to have a common vocabulary. The PAT guidance is a guidance but we need much more of a map into the future. A lot more of science and knowledge has to be characterized. And the implications are there in terms of benefits, rewards.

And what do I do next has to be clarified over the next few years in the real economic case. And I believe that could be the basis to broaden the shared vision and maybe get funding at a social level for some of this research that is badly needed and has been for a while.

Something that came up earlier today, we need some real case studies. In terms of the PAT submissions that are coming, they're still let me just test the waters, in my opinion, however little I know about it. Let's do something real now that we've trusted each other and we've learned to trust so that we can really turn things around in the next 25 years.

Besides case studies of real data and the fact that I presented those slides to you shows that I'm willing to go as far as I can but I'm not somebody who generates these data and they can go further than me.

Pilot the future. Just like you have a new Medicare, a Medicaid program that's piloted in a state before you push it out to a broader society, pilot something about this science-based manufacturing, knowledge-based manufacturing into the future where nobody loses. It's a fish bowl for the broader society.

And I know a number of academics who would probably play a lead role in that. And I've thought about it as well.

Acknowledgments, of course, I must start by acknowledging the Consortium for the Advancement of Manufacturing that has funded a lot of my research. MIT and Purdue, Ken Morris is here. I stand on big shoulders which Charlie and Steve as well. And Janet, Helen, and Ajaz, who have been an unbelievable help for society. And I've really benefitted from all.

And if you just look at this list, you can see that it has got industry, academia, and regulatory. You can't do it without all four of those -- did I count -- I missed one. I didn't work enough with the customers, I think, because I am one.

Bottom line, to end, I introduced a frame that said it's a social capability. And what we see today is the result of the social choices, of all of us together equally responsible for the good and bad.

I said science, system, and vocabulary are three words that we can all share to describe the desired state and the current state. Given that we seem to agree on the desired state and we seem to agree that the current state is not satisfactory, we had to then talk about leverages to go from here to there.

I took one case, a very tactical case, and a strategic case would be actually a much more powerful story, and let's say investigations is one of them. And you could take technology, transport, you could take characterization. Let's build a body of science around it, science of processes to climb up the pyramid.

What are the implications? And what are the next steps? And, of course, thank you to all those who have helped me along the way.

That's my talk.

(Applause.)

CHAIR BOEHLERT: Thank you, G.K.

Are there any questions or comments from members of the Committee? Yes, Kenneth?

MEMBER MORRIS: G.K., as the sort of keeper of the statistics in general, are there any estimates of the number of non-value-added tests, real or perceived, that we do in the course of releasing material?

MEMBER RAJU: First, tests are non-value added.

MEMBER MORRIS: Right.

MEMBER RAJU: If they're designed in, you don't have to do the tests. So that's the amazing part. Even if you count the tests as value added, by most computations in the literature, about five percent on a time basis is value added in our industry. Ninety-five percent is non-value added in all the paperwork and all the waiting time because we haven't designed in the quality. And that's because of our social investment or the lack of it.

There would be a time when the number would grow if you include testing but let's not even go there. Let's go over the body of knowledge that we have to put in place. And we deal with the consequences but maybe we said I'd rather fund genomics than this. And we deal with the consequences of making that choice.

CHAIR BOEHLERT: Any other comments? Questions?

(No response.)

CHAIR BOEHLERT: If not, thanks, G.K. for a job well done.

MEMBER RAJU: Sure.

(Applause.)

CHAIR BOEHLERT: We have a speaker with two ovations so I don't know what that means.

(Laughter.)

CHAIR BOEHLERT: You know the next topic is risk-based CMC review and we're going to look at it from two perspectives, the Office of new Drug Chemistry and the Office of Generic Drugs. And first Moheb Nasr will be speaking on the ONDC perspective.

DR. NASR: Good afternoon. Can you hear me okay? Can you hear me now?

(Laughter.)

DR. NASR: I don't know why I'm hear.

(Laughter.)

DR. NASR: I think we'll find out collectively. I think many presentations were made this morning that very much convey why we are here. I think we talked about the principles behind Q8 and Q9. Ajaz articulated his vision of the desired state.

And G.K. did his always wonderful job even though he did something I asked him not to do and that is his insistence in using pyramids. I think being an Egyptian, I'm entitled to use of pyramids but G.K. always uses pyramids.

What I would like to do today is to share with you where we are and where we are heading. What I'm sharing with you is a roadmap into the future. Without any exaggeration, I think we are changing the paradigm of how to assist quality of pharmaceuticals in the U.S. and in the world.

I'm going to share with you where we are, why we are changing, some of the high-level thoughts, and by the end of my presentation and Gary Buehler's presentation, our combined effort, hopefully we'll illustrate to you where the Agency is heading. And then we can open the floor for discussion and seek your input.

I will appreciate hearing from you all after my presentation because we are working at a very fast pace in order to make this change happen. And we would like to make this happen in a matter of weeks and months, not years and so forth.

These are the topics that I will try to cover within 25 minutes but Gary and I have an hour so I may use a little more time, Gary.

I would like to share with you where we are. I would like to update you on what we had before, which we called the CMC risk-based approach or initiative. I want to tell you that we are changing from chemistry review into a new quality assessment paradigm and describe to you what I mean by that.

I would like to summarize in a few slides the difference that I see between chemistry review and the quality assessment. And I would like to share with you some of our pilot programs and supplement review and so forth.

CMC review, as we all know, is intended to assure the identity, purity, quality, and strength, an potency as related to safety and efficacy for drugs throughout their life cycle from IND to NDA, most of all through the ANDA process.

This is an organization chart of ONDC. You see how simple it is. We have about 130, 135 review chemists and scientists spread out through 19 chemistry teams co-located in 15 clinical divisions. It's very difficult to manage such an organization. We are not managing well.

I hope in the future when I come next time, if Ajaz invites me, to share with you our new organization and how it will not only compliment the future product assessment but manage the losses within the agencies much better than it's being managed today.

This illustrates how much work we do in the office. The in the last fiscal year, we reviewed 159 NDAs. We had close to 1,000 INDs. We had about 2,000 supplements. That's a lot of work. And if continuing in that direction, we are going through a viscous cycle for when every time we approve a drug, the number of the supplements increase, our workload increases, and we create a problem not only for ourselves but for efficacy in the public as well. And there is a crying need for a change.

To summarize our current CMC review practices, when it comes to the application that we receive, the quality of this application varies considerably. Some are much better than others.

The applicants don't always seek consultation and meetings through the review process or follow some of the recommendations that we make and agreements we make during the review process and during the submission.

And sometimes they have, sometimes they don't have, but in many cases they do not provide enough pharmaceutical development information that I consider to be essential in order for us to do what we call risk-based CMC review.

What about our review? We evaluate all CMC information and data that comes in the application without doing too much as far as differentiating between what is critical and what is less critical.

We evaluate all the information that comes to us. And that evaluation does not necessarily utilize the vested training and background of our reviewers. Basically we have one CMC reviewer, for most part a chemist, who conduct the entire evaluation.

And if you don't have enough knowledge, they try to do the best they can. They are trained while they are doing the review. And there is good mentorship throughout the process. It's a value list-based review. I think someone today called it a check-list review. It's not really a check-list but it's a value list-based review.

We don't do enough in-depth review of process information and that's in part not totally because of the center field agreement. We have tight specification, I have to admit to that. But the specifications are set based on the limited data we receive.

This is the information we get, and based on that information, we set the specification with our goal is to assure that consistency of manufacturing process. So basically the specification is a way to control the manufacturing process.

Often we have late and voluminous CMC amendments that lead to delay in review. And as you all know, we have problems with the cycle of review and approval.

The decisions are made based on submitted data and the individual experience. There is a lack of critical information pharmaceutical development. Guidances, for the most part, are established to provide regulatory relief but at times create an increased number of supplements and that creates problems for us at the agency and for industry as well.

What are the problems with the current system? For us at the agency, it is very resource intensive. You have seen our organization chart and you see the workload. We have to deal with recalls and drug shortages at times.

For you all in the industry, there's a perception that because of the existing regulatory system, it discourages continuous improvement. Regulatory burden, what's the value of all the supplements and all the review we do? And what is the consequences of being out of specification that require investigation, recalls, 483s, warning letters, and so forth.

What about the public? High cost drugs maybe and delay in drug approval at times.

In the middle of this, with all what we are doing, with all the problems, we are facing some major challenges. In trying to outline these challenges in this slide here, we have the GMP initiative which, I think, many of us agree is really a product quality initiative for the 21st century.

How can we fit the existing regulatory system into the new way? How can we do that? There is a conflict. How to deal with first cycle approval? The heavy workload. How can we address the consistency issues and problems and difficulties that exist among the 19 chemistry teams in 15 clinical divisions?

We are attempting to do that through the guidance process. It helped some but created different kind of problems.

We have problems with the guidance and policy development. There is a lack of expertise in many critical CMC areas, many sites of pharmaceutical development. We are dealing with novel, new delivery systems, combination drug products, new technologies.

Because of all these, what we have done before and attempted to do it with some success is react rather than have a proactive proposal of how to deal with issues in the future.

I want to spend a couple of minutes talking to you about the standards of the risk-based CMC initiative that started in the year 2000 and went on until last year when I came here to this shop. That initiative was evolved over many years.

It's multi-tiered. If you look at the initiative, it was outlined as a three-tiered process. When everything was said and done, it was a five- or six-tiered because every tier split into two sub-tiers. We would start with Tier 1A and talk about three years. So if you go through the five-tier process, it would have taken us many, many years. That's okay.

The whole initiative was product specific. It addresses and deals only with what we are very comfortable with and that's mainly synthetic drug substances. Characterization must be done using traditional analytical techniques that you can clearly see. It applies only to very specific products such as immediate release or dosage and so forth.

That initiative was intended to provide regulatory relief by incorporating science-based and risk-based assessment in CMC review. But one thing that became obvious with the GMP initiative is the relevance of that initiative with our new product.

This is something that we have to deal with only for a small class of drugs and in very special cases or if there is some merits for better utilization of science- and risk-based to apply that for everything we do, from that pre-marketing into the post-marketing.

So now we are dealing with more progressive and expanded initiative that was focus on the totality of quality assessment. The risk-based quality assessment has a variety of advantages. And what I have done in these two slides is summarize some of the excellent findings that were obtained after the PQRI Conference about a year ago. The PQRI Conference that Toby Massa co-chaired.

The benefits of the policy assessment risk is the quality assessment for the patient for the increased availability, faster approval, and the patient will continue to receive our quality products. So we are not going to sacrifice the product by -- that may result from a reduction of regulatory oversight. It's basically more focused on our regulatory process rather than reducing regulatory focus.

For us at the Agency, there will be more product and process knowledge that is shared by industry, more efficient resource allocation, increased trust and better communication. And for industry, there will be more efficient science-based inspection, faster -- and you will hear more about that. I think David Horowitz will talk to you all tomorrow about the new paradigm in GMP inspection.

There will be faster, more consistent review, a potential for reduced regulatory burden, ability for you to manage the changes without very strict regulatory oversight from the Agency, focus our resources on critical issues, flexibility to focus on what should be done not what can be done, improved communication with the Agency.

And I think that the striking element of what we are trying to do today is if you look in the past, the Agency changes regulation. The industry we had. The industry raises the bar because of new delivery system and newer technology. The Agency react. But in this new paradigm, we are working together in order to head in the right direction.

When we talk about the new quality assessment paradigm, I would like to make clear to everyone here today that this is not a single initiative to address one dimension of a multi-dimensional, often complex quality assessment process. This is not a streamlining effort.

It's a new paradigm of quality assessment for new drug applications. And Gary will share with you his thoughts about generic drug applications as well. But that covers for the new drugs the entire or the totality of quality assessment from pre- to post-marketing activities.

With that we have to change our vision and our mission. And that is part of where we are heading with our new organization. I'm going to focus here on a couple of things because I think -- I do believe that the vision and the mission should clearly indicate to us, to our staff and to the public, where we are heading.

Our new vision indicates very clearly that this is a scientific organization that services the center, the Agency, and the public through leadership and innovation and international collaboration. I do believe in international collaboration. I do realize that we are dealing with global industry. And our efforts here have to be done under the umbrella of harmonization with other international agencies.

As far as our mission, we no longer continue to do chemistry. What we will be doing is for our office to assist the critical quality attributes of manufacturing processes for new drugs, establish what is the standards to assure safety and efficacy and -- and that's very critical here and that's why we need to work together to be a partner to facilitate drug development.

Some of the future elements that we need to work on and we started working on our assessment will start with a comprehensive quality overall summary. And I think you had some questions and some comments about that this morning. And that is something that we need to work on.

Review practices should be based on good scientific principles. There will be considerable increase in emphasis on manufacturing science. The CMC review and the quality assessment functions we do will be critically reviewed by our colleagues and staff and scientists at the Agency. And we must integrate our review functions with the inspection. And that goes under the umbrella of Q8, !9, and potentially Q10.

When it comes to CMC's specification and there will be another time for a larger group for another discussion about how we set the specification and why we set it and how it should be set but the main principles are specification has to be risk-based -- based on risk-based assessment, clinical relevance, safety considerations, process capability, knowledge gained from pharmaceutical development reports, and better utilization of modern statistical methodologies.

There is such a thing as regulatory relief. Such relief will be provided based on the following three criteria.

One is process understanding and control. And that what you can share with us through the pharmaceutical development reports, assessment throughout the manufacturing process, and your ability, because of your understanding of your process, and your plans to continue to improve the process. So these are three criteria that has to be there in combination in order to provide an assurance of your ability to continue to improve the process. One of these elements by itself is insufficient.

Pharmaceutical development reports may facilitate meeting for a cycle approval, science-based specifications, risk-based GMP inspection and regulatory relief from post-approval activities.

What we do at the Agency is done by people, not by machines and computers only. And that's why it's very important that we invest in our staff and provide the correct work environment and resources to support our staff. So it's very important for us to provide better work environment to our staff to facilitate superior performance and job satisfaction.

During the CMC restructure, we are in the process of reorganizing the office. The reorganization is intended to facilitate the implementation of the new quality assessment paradigm. What I'm saying is we are not moving 15 or 19 offices from one place and put them in another place. The organization will be there for one purpose and that is to facilitate the new paradigm and to facilitate the implementation of the new quality assessment.

I may come back to you later on on this one but I just want to give you heads up. We are considering establishing a CMC Scientific Advisory Board and some of the functions of this Board would be to provide scientific consultation when needed.

There is no way we will have enough expertise in house to address every regulatory or scientific issue we deal with. The Board will oversee the ONDC regulatory research program, restructure and modernize the ONDC training program, and also develop regulatory science seminars.

We are in the process of recruiting and hiring and training pharmaceutical quality assessors with expertise in drug discovery, analytical chemistry, pharmaceutical development formulation, and pharmaceutical engineering. I think there are so many people here in this room, if you know of anyone whose is looking for a challenging opportunity, I'm all ears.

(Laughter.)

DR. NASR: We have several vacancies both in the review side, on the technical side, and in management as well. And I'm serious of inviting you to help us help yourself by sharing some of the talent that is out there that we need in the Agency.

ONDC is building a strong and independent scientific organization to better serve the public and our internal stakeholders. And if you see where we are today, we are co-located with the 15 clinical divisions.

Linkage with clinical division is very important but it is one of many linkages that must be there in order to assure appropriate quality assessment. So we will maintain the linkage with our clinical colleagues but we will have to work closely with our colleagues in the Office of Compliance and the Office of Generic Drug as well. And with industry and other scientific organizations.

Our re-engineering effort is intended to work on problems that have been identified in order to meet expectations and to establish a modern equality with appropriate metrics to measure the quality of CMC review and performance.

This is very important here and we are working very hard to do that. It's very easy to have metrics to count beans, how many reviews, how many supplements, how long it takes you to do that. But we need to identify the appropriate metrics to measure the quality of the work we do and that input of our review into drug development. This is something we need to work on.

Before I go to these two slides, I'd like to remind you all that we have a very large quota of competent, dedicated, hard-working scientists. But what I'm sharing with you today does not necessarily indicate in a negative way that our organization is not functioning well. But we are shifting our paradigm.

So I want to describe to you where we are today and where we are heading. And I think I can best describe that in these two slides.

Here is what we do today. What we do is chemistry review. This is not something -- I've used a term that I intended that everyone is using that term around the agency. The review is conducted by chemists. There is extensive data analysis in order to generate the necessary knowledge and summary reports of CMC issues. That's what we do.

We get a lot of raw data, stability data, validation data. We use -- we review everything that is submitted to us. And generate summaries in order to be able to have a story to tell about the product itself.

One would question is it us who should be developing this story or is it the industry or the sponsor who developed the product that they can come and tell us their story?

It's a guidance-based review. There is more focus on chemistry and specification issues and there is less focus on process and manufacturing. There is no clear emphasis on what we consider to be critical CMC issues. We do not have a peer review process to evaluate the quality of the work we do at the center or in the office.

Quality assessment is a very different thing, assessments conducted by interdisciplinary scientists, chemists, pharmacists, engineers, and others as needed. There is more reliance on knowledge provided by advocates and that includes pharmaceutical development report and comprehensive quality overall summary.

It's a risk-based assessment. It's not everything. Focus on critical quality attributes and developments to safety and efficacy and these are some of the critical attributes that we must focus on. It's a question-based review and there is a greater utilization of peer review process.

I want to spend the next two slides to briefly summarize where we are with some of these changes we are making. You will hear tomorrow from Steve Moore, a team leader in our office, talking about comparability protocol.

I think comparability protocol can serve as a bridge or linkage between the existing system and the new quality assessment paradigm. And that's why it's taken us more time in reviewing the comparability protocol guidance before we put it out because when we put it out, we want to make it more useful and more meaningful and to facilitate the changes that we are all trying to achieve.

Comparability protocol utilizes and applies quality by design principles. It should facilitate continuous improvement with risk regulatory oversight from the Agency. It provides scientific basis for expecting, understanding, managing, and addressing changes.

It brings more focus of what is critical and what is less critical. It has a great potential for down-regulating CMC supplements. The bottom line is with the workload that I described to you earlier in the first few slides, we can no longer continue to have a quality review of the large volume and that application information we get within the existing system we have.

We are exploring ways not only to down-regulate but potentially eliminate certain types of CMC supplements that have many potential to adversary effect on identity, quality, purity, safety, strength, and potency as they relate to safety and efficacy. So we are looking why do we have supplement? What role they serve?

ONDC is developing in our new organization ways to manage the supplement review more efficiently to facilitate continuous post-marketing product improvement and to provide more resources for new NDA review. I think if we understand what you are doing and you share with us your understanding, and we'll do that at the pre-marketing stage, we have great confidence in your ability to manage your own change.

You can go ahead and manage that. That will provide more resources for us to be more of a partner during drug development.

We have a pilot program for resubmitting the NDAs because we have to find ways to reduce the resources and put the resources where they are the most needed where a single CMC reviewer perform initial assessment. Initial assessment is being done in two weeks. And relevant material are requested.

An assessment protocol is developed and then assigned to a primary reviewer. A primary reviewer will perform an in-depth assessment as always done.

Streamlining of resubmission will provide more resources for our original NDA review. Where I'm coming from is this, if from direct resources and have enough and correct and enhance the level of communication with the sponsors, that may lead to first cycle approval and potentially a decrease of the number of resubmissions.

And this slide here, this is my summary slide, this is my last slide, what I have here on the left are some truths. These are truths. We are working on re-engineering supplement review, streamlining our review of resubmissions, talking about quality by design for pharmaceutical development reports, comprehensive quality overall summary.

The re-engineering of the supplement will provide less regulatory oversight for post-marketing approval changes and that may lead to more incentives for continuous improvement. The same thing with the other tools. They will provide more resources. They will enable us to do risk-based assessment. And there will be less review time.

And all this will lead or may lead to first cycle approval of new drugs. And putting all these things together, what we will end up having is at the end better product available at maybe less cost.

I think I missed one slide. My last slide that you didn't see, I would like to acknowledge Dr. Janet Woodcock and the Steering Committee for providing a lot of insight, Helen, Ajaz, Chi-Wan, and Guirag Poochikian for providing considerable input in this presentation.

Thank you.

(Applause.)

CHAIR BOEHLERT: Thank you, Moheb. You have some very ambitious endeavors.

Are there any questions or comments? Gerry?

MR. MIGLIACCIO: Well, I want to go back to your CMC specifications to be based on, Slide 18. You say clinical relevance and safety considerations, which obviously we all agree on. Then you follow that with process capabilities. Can you elaborate? Those could be mutually exclusive.

DR. NASR: I can elaborate but I think there is time that will have to happen very soon, Gerry, where we will need to get together. By we, I mean the Agency, the sponsors, and others as well, to look at the ways we are setting specification.

The way that specification are being set now is at times because of process capability, that means if you can produce a product with a certain level of impurity, that would be in the spec --

MR. MIGLIACCIO: Right.

DR. NASR: -- whether this is justified or not. And even if that's not the spec, what is the detection ability of a particular analytical instrument? We set specification at times because of safety concerns for certain kinds of impurities because of some compendium requirements.

What I'm saying or suggesting in this slide that we have to exam all of these things together in order to see how can we set specifications.

And what we will end up having at the end of the day in my mind, and this is just me and not the Agency speaking now, so I'm going to take off my FDA hat, is a combination of all this. And it would be more on a product by product basis rather than the more generic level of setting a specification for all products, one size fits all.

So, again, I did not answer your question. But I think yes, many of these things are conflicting. And I think that's what you are saying. But we will have to look at all this -- two weeks together and all these issues together to see how we can set specifications in the future.

MR. MIGLIACCIO: Well, just a follow on, I mean conflicting yes but a highly capable process has generally very little clinical relevance to slight changes in that process. And that's what the concern is is setting specifications based on process capability. There is no clinical relevance to that.

Secondly, at the time that we're setting specifications, you have preliminary process capability. The knowledge base will increase significantly in the first three to six months after commercialization. And so to base anything on preliminary process capability is a concern.

DR. NASR: I agree with you. And I'm not talking about specification the way we do it now after the initial review of the NDAs. I think Toby talked this morning about interim specification which, by the way, is something that we do now. It's not that novel of a concept.

But what I'm trying to say in this slide that there is a crying need for us to have a handle on setting specification. And to have a specification that are most relevant for that particular product and not use a specification as a tool to control the manufacturing process.

I think what we have done before because we didn't know -- we don't know in many cases how you are developing your manufacturing process and you know that, Gerry, you know, the level of information vary from sponsor to sponsor.

We try to have an assurance because we have our responsibility to the public that the product that you will produce in the future have the same critical attributes to the product that was used in the clinical trial. And that is by making sure that the level of impurities, for example, are the same. And even if they can be tighter, we tighten that so to make sure that you continue to -- you have better control over your process.

Is this the best way to do it? I don't think so. But we will have to put our thoughts together to see how can we set that in the future because what is happening now in some cases is the specifications are too tight and they may not be that relevant to clinical issues to start with.

And that may result in disruption of the manufacturing, recalls, need for investigations, and so forth.

MR. MIGLIACCIO: Thanks.

CHAIR BOEHLERT: It sounds to me like this is a subject we might need to have some continuing discussions on because this whole issue of manufacturing capability versus safety and efficacy is one I think that drives industry a little nuts from time to time.

And if you want to reduce the number of supplements, this may be an area that we can take a look at because -- and you mentioned impurities. And it happens to be a subject that is near and dear to my heart.

And very often safety has been demonstrated at very much higher levels than are approved as specifications. And if something changes down the road, you shouldn't have to file a supplement if it's well within those limits that have been established as safe as effective.

And so I think it's a topic for a continuing discussion and an area we may be able to relieve the regulatory burden.

DR. NASR: That's a very good point, Judy. Without stealing the thunder from future events that will be taking place, we are currently working on having a public workshop between the industry, the Agency, academia, and so forth, to focus only on setting specifications.

And all the issues I outlined on this slide what comes from analytical methodology, from safety and efficacy, from clinical relevance, from manufacturing, all these things will be raised because I think we need -- if we are talking about the future paradigm and specifications that are more relevant and not one size fits all, there is a need to do that.

And we started the elementary discussions to get there.

CHAIR BOEHLERT: Okay.

Ken?

MEMBER MORRIS: Thanks. You know, Moheb, it hadn't occurred to me until I saw it on your slide even though we've talked in general terms about this, but in terms of metrics for determining the quality of the review process in the future, do you have any ideas of what that is going to look like?

I hadn't thought of it before you mentioned it but I can see whereas now you can sort of count submissions or something like that, it's going to change in the new system.

DR. NASR: I think we started already, Ken. Question-based review, the peer review process that we instituted already. And also we are looking in instituting a quality management system throughout our new organization. Quality assurance program and I also, as I indicated in one of my slides, am considering the establishment of a Scientific Advisory Board.

So I think we have several elements but what really needs to be done is to see are these sufficient metrics? Are they quantitative enough? Do we have a map here where we can connect all these dots to have an overall system?

Once concept that I've seen that's been used by other regulatory agencies, if you wish, is sharing the review with the sponsor. I mean if we are talking about scientific organization and dialogue between industry and the Agency, how about if we share our assessment, if you wish, and see how we can learn rather than judging the in-depth of the quality, how can we learn from this to do a better job in the future?

CHAIR BOEHLERT: Okay.

Dan?

MEMBER GOLD: Thank you for a very interesting talk. I think you're making a lot of progress.

I have a question related to an issue that came up during the last meeting of this Committee where a representative pointed out that in Europe the quality summary is -- it's a top-down approach to the review of the application. And they were pointing out that they thought that in the U.S. it's a bottom-up review. And that your reviewers are really not looking at the quality overall summary.

Can you comment on that please?

DR. NASR: Yes, I can.

I think, as you can see, that's one of the major elements in our future review practices. Because of that, I spent about two and a half weeks in Europe in April because what I've decided to do is to expand my area of knowledge about other regulatory processes that proved to be successful. And I went to visit several national authorities and I participated in advisory Committee discussions and so forth.

If you are talking about the expert report which was used in the old system versus quality overall summary which is currently part of the common technical document, I can share with you the following. What I'm talking about goes beyond the existing quality overall summary, which has a very narrow scope.

I think we are talking about more expanded quality overall summary that has more pharmaceutical development component into it. That's number one.

Such a summary can serve as a summary because part of what we do now in our review is creating the summary. So why don't we have you, as a sponsor, as the one who developed the drug, provide us with such summary?

And then the focus of what we do is to be -- is to assist the critical areas that in the application itself.

Number three, such a summary will not be the only thing we review but it can be a starting point to highlight what could be critical CMC issues that we expect to see in that particular application.

And then we will focus our efforts on critical issues but also since we have the entire submission, we will go and be as detailed as we need to in order to have complete understanding of some of these issues.

MEMBER GOLD: So do I understand --

DR. NASR: I forgot to add one thing if you allow me. That also may require us revisiting under ICH or under another way of how the submission is put together.

MEMBER GOLD: Do I understand you then to say that if we put into -- if we submit a very good quality summary, this is going to accelerate the review of the application and the more rapid approval of the application?

DR. NASR: Yes.

MEMBER GOLD: All right. One second question if I could? I realize that the initiatives that we're talking about are very new for the Agency. Do you have any metrics that indicate the improvement using these techniques that you have seen so far in terms of reducing application review time?

DR. NASR: I have some metrics and I'm doing some experiments. As a scientist we have to continue to do experiments. Some of the knowledge I have is based on my experience talking to our European colleagues. And when I talked to them about utilization of quality overall summary and expert report, it does reduce the review time. That's number one.

Number two, we are currently experimenting with resubmission of NDAs in some of the critical CMC review teams within some clinical divisions. And what we are trying to do is to start the assessment process, as I indicated on one of my slides, by a high-level evaluation of the application itself, and development of an assessment protocol in order to -- before the assignment is made in order to facilitate the review.

That's much better than the current practice where you have the many folders, as you know, Dan, and you go through the entire review before you develop the entire story.

I think having a quality overall summary will facilitate the development of the initial assessment protocol, if you wish.

MEMBER GOLD: Thank you.

CHAIR BOEHLERT: Any other questions or comments?

(No response.)

CHAIR BOEHLERT: If not, Moheb, thank you.

DR. NASR: Thank you.

CHAIR BOEHLERT: From the Office of Generic Drugs perspective, we have Gary Buehler.

DR. BUEHLER: Thank you, Judy.

First I'd like to thank Ken. Usually I'm last to speak at just about everything I go to and somehow I don't know what you did to someone, Ken, but thank you very much.

(Laughter.)

DR. BUEHLER: It's really nice to not be last. I was last at the GPHA meeting in the wintertime. And I was right before the golf tournament.

And I started to speak and I heard all these cleats outside and everything. People were banging their bags around and everything. So it's very nice to have a nice quiet group here.

I'd like to acknowledge Dr. Berridge's presentation. I have to say, Dr. Berridge, that was the clearest explanation of this paradigm I've ever seen. I mean it was -- your slides were great.

And actually I may be calling you for some of them. After you see my slides, you'll understand but it was really a very clear explanation of what we're trying to tell people today.

And I have to admit there is a fair amount of repetition here. And I'm not going to be an exception.

Also I have to say your English accent is great. You know I am from Philadelphia. I'm a Colonist. I haven't lived there for 30 years but people still say I talk like a Philadelphian. And it's just so authoritarian. I'm hoping to be able to do this in that way.

Acknowledgments, I have to say that a lot of my talk was furnished by Frank Holcombe and Vilayt Sayeed. They're in the audience today so if I say anything wrong, there they are.

Our mission is really very simple. It is to provide quality, safe, effective generic drug products to the American public. I'm a nuts and bolts guy. This is what I have to do. And it basically is we have to review and approve applications.

We almost approved 400 applications last year. That's what I do. And, you know, this is a vision. This is a vision for the future. And believe me we are fully supportive of this vision in trying to make the quality of all drug products, generic and innovator, better and the process much easier and much better for both the industry and FDA.

But, again, as you can see, my workload is increasing. And it has increased dramatically over the past two years. In 2003, we received 449 applications. In 2004, we expect to receive 566 full, original ANDAs.

You don't -- I have about -- it's somewhere over 50 review chemists. It maybe 52 or 53. You don't need Bayesian statistics to figure out that that is about 11 original applications per reviewer per year.

MEMBER SINGPURWALLA: You'll get a better estimate if you use that.

DR. BUEHLER: Okay, thank you, thank you.

(Laughter.)

DR. BUEHLER: That's a lot of work. We have a tremendous amount of work. It's increasing. It's increasing much faster than I can hire people to review these applications.

So we are looking for better ways to review these applications. We recently had an office-wide retreat for the entire office to look at ways that we can cut down on our workload, become more efficient. If we're looking at something we don't have to look at, we don't want to look at it anymore. We're trying to identify anything we can to have a more efficient operation.

Along with our originals, and Moheb brought out the point that every time we approve an original, we're looking at more supplements. And if you approve 300 or 400 a year, you're looking at a lot more supplements. So anything we can do to reduce the supplement load, we're also very interested in.

Quality -- and this -- I mean these posters you may see on buses. If you go to Los Angeles or Chicago, we've actually had our posters on buses. The waiting rooms in Eckerd's and I believe Giant had then in waiting rooms. So we are very proud of the quality of the generic products that are on the market today.

We believe your generic drug is safe, effective, and bioequivalent. We believe people should be able to take them with full confidence.

So the products out there today are not bad. I mean they're good, safe, effective products. We're just looking at better ways to make them, more efficient ways to make them so that the industry and the FDA will have a less burden in reviewing the applications.

And it gets to the definition of quality. And Helen asked me, she said your quality slide is blank. And there are a lot of definitions of quality. I know David will probably give you one tomorrow. I think Janet Woodcock has one.

And to me quality is pretty much, you know, in the eyes of the beholder. You know when something is inferior in quality. I had a 1976 Dasher a few years ago. And it was the worst car I ever owned. It wouldn't start. The air conditioner wouldn't work. And clearly my decision, based on the quality of that car, was I never bought another Volkswagen.

And all of you out there have stories about appliances, or electronics that you've had, that really did not perform the way you thought they would. And your judgment on those were that they were poor quality. And you probably never bought that particular brand again. That's your right to not do that.

Quality with drug products is a different thing, though. Sometimes we can tell. If you have a patch that doesn't stick right, that falls off when you take a bath, or if you have a bottle of pills that are broken when you open then, you can make a sort of a consumer-based assessment of quality there.

But for the most part, you don't know if they're within specification. You open that pill bottle every day and you take a pill with full confidence that it is going to make your cholesterol go down or your blood pressure go down. It's going to relieve your pain because you trust the FDA, you trust the drug industry that what they say is in that pill is in that pill. And what they say that pill will do, they'll do it.

So that's where we come to play in. The FDA has to be the person that helps to assure this quality. That's what we've been doing in reviewing the applications to date and that's what we want to continue to do.

Now the slide I showed previously, this one, our challenge with generic drugs is that many people relate quality to cost. And that's not a far stretch. A Lexus costs ten times more than a Daewoo. And they don't sell Daewoos anymore, yes. I mean but that's an extreme example.

I actually rented a Daewoo once. It was a horrible a car really. I see why they're not around any more. But really that's -- I mean that's a clear judgment people have. You'd always rather drive a Lexus than a Daewoo.

But with respect to generic drugs what we tell people is it doesn't matter that they cost half as much. You should take them with confidence, that they're made under the same quality conditions that the innovator drug products are and you should be able to take them with confidence.

That's our challenge. And that's why Congress actually asked us to start this campaign to make consumers aware of the quality of generic drugs. And believe me with the number of applications escalating that I'm getting, that's of primary importance to me is to continue the quality of generic drugs.

Now our current paradigm, and this is what we do today when we get an application, we look at the quality standards. We make sure that the standards are comparable to the reference-listed drug. We do look at the specifications of the reference-listed drug established by Moheb's people in the CMC review in the innovator products.

We make sure the product is manufactured in compliance with good GMPs. And the process and specifications are conditions of approval that require approval for any subsequent changes. Basically we lock in the specifications. If you want to change it, you've got to submit a supplement to us.

That's what we do now and we will probably continue to do that for a little while longer.

Now in original ANDAs, there's extensive negotiations over specifications. And we did an internal study in our office recently where 40 percent of the original applications, the comments on the first review cycle were all related to tightening specifications.

And basically I don't blame the generic companies. They come in, they base their specifications on the batch that they made, that they submitted to us, and they don't know what the specifications of the RLD are. It's a mystery. It's kind of a guessing game for them.

And so they submit specifications based on their biobatch. And they try to, you know, make them as wide as they think we'll accept because these are the specifications that is going to lock them into their manufacturing processes for the next who knows how many years.

And we try to crunch them down a little bit according to, again, the references to drug and what we think they can do.

And, unfortunately, this takes time. And our average review time for an ANDA right now is about 18 months. And we would like that to get down. Congress would like that to get down. And we're doing all we can to try to reduce that number.

It also necessitates a high number of supplements because once we lock in these specifications, any time that the company wants to change one of these specifications, they have to submit a supplement.

Now in the new approach and, again, I harken to Dr. Berridge's presentation. You know, I feel like I should be like Mickey Mantle and Casey Stengel when they went down to Congress and they were testifying on the reserve clause in Congress and they asked Casey to give an explanation of the reserve clause.

And he went into this long explanation that, you know, went all around and around and whatever. And actually the Congress was kind of laughing at the end of it. And then they went and asked Mickey Mantle if he could give his comments.

And he said I agree with Casey.

(Laughter.)

DR. BUEHLER: So basically in this, I agree with Dr. Berridge. The extent of product knowledge is key. It drives the range of risk-based decisions based on supportive data to assure a quality product. And that is a product with established quality attributes, purity, potency and strength, identity, bioviability and delivery, labeling, packaging, and physical performance.

So, again, very general terms. You know where is the specifics? And I said to myself if I had to make a talk on the quality initiative, I want to be able to provide good examples to the industry because the industry asks me what do you want us to do?

And I was hoping to be able to kind of have a slide where one side is this is what you do now and the next slide is this is what we want you to do. And then the next slide will be like this is what you'll get out of it, you know. This is what you won't have to do because you've done the second part.

I'm still not able to do that. We're still working on that. And I will throw some challenges out to you at the end of this presentation to try to help us to get to that point because I believe we have to get to that point.

You out there have to know what's in it for you. You're a business. You're a business to make money and the generic drug industry especially is a very competitive business. And they want to know, you know, how it can effect the way they manufacture drugs. And we have to be able to tell them that.

This is voluntary. And I want to emphasize that. I know that there are some companies that are not ready for this. And these companies are the companies that are submitting my 500-plus applications to the Office of Generic Drugs.

We will work with you. We will be glad to work with you. We want to work with you through your trade organization, the GPHA. We will try to organize webcast presentations so that you can begin to understand what we want from you.

It will be a phase-in process probably. We hope that certain parts of your application can use this paradigm if not the entire application. And, hopefully, you can do that through comparability protocols.

We want to be able to move the generic industry into this paradigm but we know it won't happen overnight.

We don't want to unnecessarily impede optimization of manufacturing processes and that's what people are accusing us of right now. They're saying that FDA is in the way of the, you know, movement forward of the generic industry. And we realize many firms won't be able to do this.

Gerry, I'm going to pin you down. Do you make Viagra 24 hours a day?

MR. MIGLIACCIO: No.

DR. BUEHLER: No? Do you have a dedicated facility for -- is that because of the competition? Did you make Viagra 24 hours a day?

MR. MIGLIACCIO: No.

DR. BUEHLER: No? Okay. I thought those bathtub guys were giving you some competition.

MR. MIGLIACCIO: They are.

DR. BUEHLER: They are? Okay. How do they get those bathtubs on the side of the mountain? Have you ever seen that commercial for the bathtubs sitting on the side of the mountain?

(Laughter.)

DR. BUEHLER: How do they put the water in?

But, I mean obviously for a product like Viagra or Norvasc or some of your big guys, I mean you are making -- you don't ever shut those lines down, correct?

MR. MIGLIACCIO: Sure we do.

DR. BUEHLER: I mean -- but I mean to just do some maintenance on them but not to make another product.

MR. MIGLIACCIO: Sure we do.

DR. BUEHLER: Yes? Okay. Really?

(Laughter.)

DR. BUEHLER: I'm amazed. Okay. I thought you just -- 24 hours a day. No? Okay. All right.

MR. MIGLIACCIO: Let's stop with this.

DR. BUEHLER: Okay, I should. I should. Well, all right. The innovators are always beating me up. So I thought I would pick on Gerry a little bit but he's got the answers so I can say for sure generic companies don't make products 24 hours a day. And they don't even make products probably week after week after week.

Some very isolated products perhaps but most of your generic companies make numerous products and they are breaking down their equipment and starting to make new products, you know, weekly or monthly. So it becomes more of a challenge for the generic company to implement these process initiatives.

And that's why I'm committed to work with the generic industry to try to phase these processes in to how they make their products.

We want to get a review completed in one cycle within the statutory time frame. We'd like to get an approval out within one cycle. That's pretty rare right now but we are working to that.

We'd like regulations based on knowledge and science that provide flexibility in approval conditions. And we'd like the need for supplements based on knowledge in the risk of changes effecting the quality of the product, again, Dr. Berridge.

Now we have made internal changes to enhance approvals. We're changing work assignments to optimize review resources.

Right now we have a system where we are assigning teams of reviewers to batched applications or actually applications of -- we often get applications from different sponsors for the same drug product.

And so we are assigning actual review teams to those applications because we found that many times the reviews kind of run along the same line. They use the same DMFs. And so it's much more efficient to actually review the applications that way.

We want to improve communications with the DMF holders. We actually want to work with GPHA to try to do that. Many times the DMFs that we have are deficient when we first review them. We would like to remedy that because the DMF review is very critical to our review process.

We are incorporating the aspects of the CMC risk-based initiative. We want to identify CB supplements suitable for expedited approvals. And what we want to do here is when CB supplements come in to our office, we want to triage them through the team leader. And we want to issue an immediate approval if we can, if the team leader can make the assessment on the spot that the supplement can be approved.

We expect to deal with comparability protocols. We expect that the generic industry will phase into this paradigm and that we hope that they will do this through the comparability protocol pathway.

And we want to utilize in-house knowledge for specific drug products to identify new elements critical to product quality and to provide prior approval supplement relief.

Now, for the industry, formulation and process design based on inherent mechanistic understanding of drug and its impact on product quality and performance. We need to have this information from you. Sometimes we get some. Sometimes we don't get much at all. But that's what we're going to be looking for.

And I know, again, you're out there asking what are you going to do with it when you get it? Well, I guess you're going to have to trust us. We want to see it. We want to try to work within this paradigm but we can't do it unless we have the information.

We want specifications determined by the knowledge of the process or the product. We want a clear rationale for selection. And we have to confess that we don't have that clear rationale right now. Our rationale right now is based on the data we receive.

Process understanding to mitigate risk associated with drug substance properties, we want continuous process improvement. We want to identify the parameters critical for product manufacture and product shelf life for stability.

And, again, we have to get together to do this because I know that you're not going to send us a submission where you are going to try to guess at what we want because that's too much of a risk for you.

So we have to get together. And you have to know what we want. And we have to realize what we've asked for so that when we get these applications, we will be able to review them efficiently.

Our staff will follow guidances in current scientific literature. And the staff in OGD is very dependent upon guidances. We don't have the one on one interaction with the drug industry, with the generic drug industry, that they have in new drugs.

We don't have the end of Phase II meeting, the pre-NDA meeting, the little fireside chats every once in a while when they have an issue. We just don't do that. With 550 applications we can't do that. And so we have to work within guidances and formal guidances to the industry.

We have to train our staff and we have to train regulated industry in what this process is and what we expect. And we have to get to the specifics.

This represents a fundamental change in our thinking, in our culture of accepting applications and reviewing applications. And we have to be able to get away from this culture and into this new paradigm.

We need a review based on knowledge of the product and what manufacturing changes will make a difference.

Why should you do this? And this is the big question that many of you have. Greater flexibility in optimizing your manufacturing process. This is a good thing. This should be able to help you. And this should be able to help the industry as a whole.

Lessened post-marketing supplement burden. You saw my slide where, you know, we're getting, you know, almost 3,000 supplements this year. We have to be able to find some way to lessen this burden for my office and for your industry.

And reducing no assignable cause, results, and investigations. These are when you get your 483s and they don't know why but something failed in your process. And there is no cause assigned.

Now my ICH slides, I think I'm just going to blast through because actually Mr. Razzaghi and Dr. Berridge have done a very good job in explaining how ICH fits together with this particular paradigm and mine are just little summary slides.

Dr. McClellan, our former Commissioner, stated that other high-tech industries have achieved enormous productivity gains and we should expect nothing less from the pharmaceutical industry. Yet the Wall Street Journal said FDA regulations leave drug manufacturing processes virtually frozen in time.

It's true that regulations designed to protect the public's health make this a very special industry. And they promote a conservative risk-adverse mentality. And FDA counters that the drug companies resistence to change is also partly to blame.

You don't want to risk changing. And we have to admit that we're a pretty conservative bunch, too. And we sort of, you know, go with the flow and we don't like to rock the boat too much.

But here we've made the first step. We want to encourage the use of equipment and protocols for continuous monitoring of manufacturing processes, PAT. We want to encourage moving to risk-based cGMPs to free the industry from rules that do little or nothing to ensure quality. And we're willing to facilitate initiatives as long as they improve the quality and reduce the risk.

We acknowledge the generic industry as experts in manufacturing. You manufacture hundreds of drug products. And we know that you know how to do this. And we know that you are aware of the many processes, the many new processes that are available.

You can identify and articulate the financial impact both for changing and for the losses with current technology. And I said before, I am sympathetic. I realize you are a business. You do make money. And the economic aspects of this are important.

We have to avoid the perception of a two-tiered quality product system once we get into this. We don't want to have, you know, the sort of, you know, the Level A quality people and the Level B quality people. And I don't believe we're going to get that. But we have to make sure that that isn't a perception.

And the partnership assumes product quality is about providing flexible regulatory impact based on product understanding.

Because this system includes a continuing of information, how this flexibility is applied needs to be well understood to ensure even treatment and outcomes. That's what I'm saying. We have to be able to provide details to you about how this will work.

FDA is not in the business of manufacturing. We don't manufacture. And your question to us is what do we need to do? And our question to you industry is what do you think needs to be done?

We invite you to come to us either individually -- we know that sometimes you will have issues where you want the entire industry to be present when you are presenting your issues to us. You can ask for a meeting on this and we will grant the meeting to discuss how you can move forward.

We also want to work with GPHA and my friend Gordon is in the back. We hope to be able to set up something with GPHA so that we can talk about general principles and, hopefully, again, because we have talked about general principles an awful lot. Hopefully we can get into the specifics of how to do this problem, what we want you to do, and what we expect to see, and what the effect will be upon you long term.

I just have to finish with another slide, another bus slide. But I am very proud of the generic industry. I'm proud of what we've been able to do to alleviate the high drug costs in America today.

I am a bit overwhelmed by the number of applications that we have in our office right now but I'm also very pleased that the generic industry is sending them to us. And we will happily review and approve them hopefully.

Thank you.

(Applause.)

CHAIR BOEHLERT: Gary, thank you. Also some very ambitious initiatives.

Nozer?

MEMBER SINGPURWALLA: Yes. I have a lot of questions and comments.

First is I'm not sure whether you were addressing your talk to the Committee or to the generic drug industry. I got the impression that you were talking to the generic drug industry.

DR. BUEHLER: There's a few of them here.

MEMBER SINGPURWALLA: There's a few. Okay.

Well, I would like to ask you a few questions and then I'd like to make some comments.

First is do you have any example wherein a generic drug is of better quality than its non-generic counterpart?

DR. BUEHLER: Better quality?

MEMBER SINGPURWALLA: Yes.

DR. BUEHLER: No.

MEMBER SINGPURWALLA: So all --

DR. BUEHLER: We say they're equivalent quality.

MEMBER SINGPURWALLA: Oh, equivalent. But there is never a counter example where a generic drug is of better and more effective quality then a non-generic?

DR. BUEHLER: Well, you know, it depends on how you define quality.

MEMBER SINGPURWALLA: Whatever way you want to define it.

DR. BUEHLER: Okay. Well, I mean --

MEMBER SINGPURWALLA: Just yes or no.

DR. BUEHLER: Yes.

MEMBER SINGPURWALLA: There is?

DR. BUEHLER: Yes.

MEMBER SINGPURWALLA: Okay. Second, the approval time for a generic drug you said is about 18 months?

DR. BUEHLER: Yes.

MEMBER SINGPURWALLA: How much is it for a non-generic counterpart?

DR. BUEHLER: Probably I think it's 12 to 14, something like that.

MEMBER SINGPURWALLA: So a generic drug takes a longer time to be approved than a non-generic drug?

DR. BUEHLER: Yes.

MEMBER SINGPURWALLA: Well, I propose that if you use Bayesian methods --

(Laughter.)

MEMBER SINGPURWALLA: -- you will cut down on both the generic and the non-generic approval time because if a generic drug -- if a non-generic drug has been approved, there is prior knowledge there --

DR. BUEHLER: That's absolutely correct.

MEMBER SINGPURWALLA: -- and that should be translated to the non-generic -- to the generic counterpart and you should save on --

DR. BUEHLER: Well, Congress has made this similar argument that you're making.

MEMBER SINGPURWALLA: Well, Congress sometimes is wise.

DR. BUEHLER: Yes, sometimes.

(Laughter.)

MEMBER SINGPURWALLA: Now, on your Slide 23, you cited two examples. One is by Dr. McClellan and the other one is the Wall Street Journal, and you said that that was kind of a contradiction but I don't see it as a contradiction.

One was talking about productivity. That is manufacturing. The other was talking about the process of approval. They're two different things. You know to approve a drug, you have to look at its chemistry and all kinds of, you know, biological features.

To manufacture, it's a different process. So I can see the two -- I don't see the two as being in conflict. I can see the two as being true because productivity gain means how quickly you can manufacture, how efficiently you can manufacture. Approval is a different process.

DR. BUEHLER: Well, I think the point being Dr. McClellan said that the drug industry should do better but at the same time the Wall Street Journal said that we, the FDA, were holding back the drug industry.

MEMBER SINGPURWALLA: Possibly true but on a different matter.

DR. BUEHLER: Okay.

MEMBER SINGPURWALLA: And you say FDA is not in the business of manufacturing. I agree. But there are two comments. You monitor the manufacturing and secondly this is the Subcommittee of the manufacturing. So you do monitor the manufacturing process.

DR. BUEHLER: But we don't manufacture.

MEMBER SINGPURWALLA: Of course not. But you don't design the drug either.

DR. BUEHLER: We monitor manufacturing.

MEMBER SINGPURWALLA: You're just monitoring. And anyway, my comment to you is I think if you were to use Bayesian methods, you would save on time --

(Laughter.)

MEMBER SINGPURWALLA: -- and you'd probably have more time on your hands so that you can give more talks.

(Laughter.)

DR. BUEHLER: Are the copies of your slides available. I should be able to get those.

MEMBER SINGPURWALLA: Yes, but my slides are not going to help you.

DR. BUEHLER: I see.

MEMBER SINGPURWALLA: They are just -- my slides are not going to help anyone. They're just going to tell you what it is all about.

To really -- to be effective, you really have to go, take a specific example, work it through very carefully, and make the case that this is what can be done.

DR. BUEHLER: I agree. I absolutely agree. We need some examples to get through our system and to be able to illustrate to everyone the economics of this and the efficiency of this. And the fact that there is benefits for the drug industry in doing this. I absolutely agree.

MEMBER SINGPURWALLA: I'm done.

CHAIR BOEHLERT: Ken, then G.K.

MEMBER MORRIS: So, Gary, after you've instituted the Bayesian analysis --

DR. BUEHLER: Yes.

MEMBER MORRIS: -- when you're talking about not being able to have the same sort of end of Phase II meetings but in the face of the extended, relatively extended review time, is there a possibility, because it does actually in many cases, I know the direct contact really does speed up the process by resolving issues that are quickly resolved when talking scientist to regulator, et cetera, is there any chance at least for like teleconference --

DR. BUEHLER: Yes.

MEMBER MORRIS: -- meetings and --

DR. BUEHLER: We've actually instituted -- we had -- believe it or not, you know, in past years, we had a system where we didn't talk to anyone during the first cycle on the telephone.

MEMBER MORRIS: Yes.

DR. BUEHLER: And we are revising that policy. And that was a policy that instituted as the result of the generic drug scandal and trying to sort of mandate this level of consistency across the entire office with respect to review.

And we have sort of broken away from those shackles and we are encouraging our reviewers to talk, especially at the end of the first cycle. And to be able to discuss the deficiencies of the first cycle.

One thing that I did mention that we are trying to address are the DMF deficiencies. We're highly dependent upon, obviously, the DMF for the active pharmaceutical ingredient. And we are trying to do something where we can either get those reviews done in an earlier time frame so that the deficiencies can be set ahead of time and that they can be back in time for when the application is reviewed.

Because clearly we get many applications that could go out on the first cycle except for the DMF deficiencies.

Yes, G.K.?

MEMBER RAJU: Coming back to -- you said you like John Berridge's presentation from the morning. In his presentation he talked about the ICH Q8 and Module 3 about pharmaceutical development.

DR. BUEHLER: Yes.

MEMBER RAJU: To what extent does that directly translate? Is it different for the generic industry, the importance of pharmaceutical development and what you want submitted in terms of the whole ICH process and Q8 and what they're putting into that section? Do you want something from the generics? The same? More or less?

DR. BUEHLER: Well, it sort of probably will have a different focus. I mean and -- and Paul can maybe address this better than I but to me a generic firm in their development report, the big part of their development is they want to develop a bioequivalent formulation to the RLD. That's sort of the big target.

And how they do that with respect to, you know, if there is a patent that is in their way and how they design around the patent, how they choose the inactives for the particular formulation. And then, you know, the development aspects of all of the formulating of that product, we would be very interested in seeing.

And so I think to us that would be our, you know, the development information that we would want to see and all that was attendant to that.

MEMBER RAJU: But the paradigm in which you evaluate quality is bioequivalance. Then your desired state in terms of mechanistic understanding is based on the innovator's understanding? Or is it based on getting a special -- a mechanistic understanding for the generic all over again?

DR. BUEHLER: Well, many times the manufacturing processes are vastly different from the generic and the innovator. So if we want to understand the mechanistic, you know, the manufacturing process from, you know, A to Z or whatever, it could be totally different than the innovator's.

We certainly refer to the innovator applications for, you know, referencing and actually looking at what they do and what problems they had. But with respect to the generic, we have to look at their process and, you know, they would have to define the critical parameters in their process.

MEMBER RAJU: Okay. So as far as the product is concerned, it's pharmacokinetics and dynamics. You take that from the innovator because it's already out there. But in terms of the generic, not only bioequivalance but you'd also look for some mechanistic understanding of their formulation --

DR. BUEHLER: Yes.

MEMBER RAJU: -- to give them a specification release.

DR. BUEHLER: Yes. I mean some products are -- I mean like extended release products have vastly different ways of manufacturing and mechanisms. So --

CHAIR BOEHLERT: Okay. Nozer, did you have another comment?

MEMBER SINGPURWALLA: Yes, I'm sorry to come back. I'm curious. Why does a generic drug take 18 months for approval whereas a non-generic one takes 12? Why less? Why more in the other way?

DR. BUEHLER: There we have almost 600 pending applications in our office right now.

MEMBER SINGPURWALLA: Oh, so the cause of it is you are overloaded?

DR. BUEHLER: Yes, it's a queue system.

MEMBER SINGPURWALLA: But it's kind of unfortunate and unfair to the generic manufacturers that since the FDA is overloaded, they have to wait, right?

DR. BUEHLER: Well, yes and --

MEMBER SINGPURWALLA: I don't own shares in a generic drug.

DR. BUEHLER: Well, well, no.

MEMBER SINGPURWALLA: I just want you to clarify.

DR. BUEHLER: And that's an average, too. And we do approve many applications in eight months, nine months, ten months.

MEMBER SINGPURWALLA: Oh.

DR. BUEHLER: And they depend upon the quality of the submission, whether it is a controversial drug or not, whether we have patents to deal with, whether we've been sued on the particular product.

Sometimes when we're sued, well, Gerry, sorry, but Gabapentin, I mean there's still no Gabapentin on the market. The patent went out four or five years ago. We have products in our office that have been pending for seven or eight years. Now what do you think they do to a mean?

MEMBER SINGPURWALLA: Okay. So the bottom line is that it's not for scientific reasons that you are taking a longer time --

DR. BUEHLER: No.

MEMBER SINGPURWALLA: -- to approve.

DR. BUEHLER: I mean it's a -- we had a generic drug scandal in 1990. So part of that scandal was taking products out of order, taking preferential treatment to certain companies. And so we have a rigorous queue system in our office where we take things, you know, first in, first reviewed. Not necessarily first approved because it depends upon the quality of the submission.

And they are stacked up in line. Each chemist has a queue that goes down. Our bioequivalents division has a queue of applications like, you know, 30 pages long.

MEMBER SINGPURWALLA: I got the message. I thought it was for scientific reasons. And if that was the case, then I'd be a bit surprised because you already have knowledge from the poor non-generic drug manufacturer who has done all the investing, you know, and done all the work. You should be able to exploit that.

DR. BUEHLER: No, we acknowledge that. No, they do a good job.

MEMBER DeLUCA: Along those lines, Gary, do you want to comment on the future? Because this is going to get worse as far as workload with the drugs, the biotech drugs that are going to be coming off patents in 2005. You're going to have a very increased workload in the generic area.

DR. BUEHLER: Well, I probably won't comment on the biotech drugs because that's a bit up in the air as to just who will be doing those. But, no, from this slide, obviously the trend is more work.

Moheb, actually his slide, I think he said he had about 100 and some new NDAs, 115 new NDAs. We got 102 last December, 102 ANDAs in December, in one month. So the trend clearly is going up.

Like I said, we did have an office-wide retreat about a month ago where we looked at just about every one of our processes to try to determine where we could do a better job in looking at fewer aspects of the application. And trying to identify really the critical parts of the application that have to be reviewed.

And at the same time, we're hiring people. I mean every, you know, every couple weeks a new person comes on board. And we are trying to get to the point where we have 60 review chemists, where we have three divisions of four teams each, five chemists in each team. And we believe that that will give us a good base to be able to address this workload.

CHAIR BOEHLERT: Paul first, then we'll go Garnet, and then Dan.

DR. FACKLER: I just want to make a couple of quick comments. One about the pharmaceutical development reports. They're admittedly different for generic drug development than they would be for the innovator's product. We have only a couple of targets that we need to hit.

We're looking to have pharmaceutical equivalents. And then we're looking to have dissolution comparability and bioequivalents. So the development reports for a generic product are focused, you know, certainly more tightly focused than you'd have for the comparable brand product.

The question about quality. Are there ever generic products with better quality than innovator products? It depends on how you assess quality. We sometimes have a problem reducing bioavailability on oral products to match an innovator. And you could argue that a better quality product would have better bioavailability.

But then we'd be coming out with a 15 milligram tablet to go against a 25 milligram table innovator. It's not an equivalent. We have to back off that kind of a formulation.

And the other kind of quality comparison is the variability that you see in the bioequivalents study. And there is an inherent variability in a drug substance but there's also a variability associated with a drug product.

And it's sometimes difficult to engineer -- for us using different release mechanisms, it's sometimes difficult to engineer the same variability see in an innovator product.

And the last point I wanted to make was really a question about the review time. We understand that reviews should be -- or the first review should be completed in, I think, 180 days. And recognizing with the large number of applications and the limited resources, we sometimes don't receive those within 180 days.

My guess is that the review time is very short compared to new drug applications if you discount the time that an application sits in the queue, if you will.

DR. BUEHLER: Yes. And that time also reflects the time with the firm. So if we send deficiencies to the firm and the firm decides that this isn't a high priority application to respond to and they have three others on their table that, you know, the patent is going to go out in a month, they want to respond to, they will let the application sit. And so that time counts against us, too.

DR. FACKLER: The other time that counts against it is the 30-month stay.

DR. BUEHLER: Yes.

DR. FACKLER: So that if we've made an application, we can't legally market a product for 30 months whether or not FDA has approved our application.

MEMBER SINGPURWALLA: An unfortunate system of rules I should say.

(Laughter.)

DR. BUEHLER: Well, it's a heavily legal influenced system.

CHAIR BOEHLERT: Garnet?

MEMBER PECK: I do believe that you mentioned something to this effect that you will have an API that has an ANDA submitted by multiple companies.

DR. BUEHLER: Yes.

MEMBER PECK: Yes. Just --

DR. BUEHLER: Many times.

MEMBER PECK: -- recently there were seven companies got approval about the same day so are you trying to work those as a unit?

DR. BUEHLER: Yes, now we are. We didn't previously.

MEMBER PECK: Through the Agency?

DR. BUEHLER: Yes but now we assign them to the same team if we can if it's a small enough number because many of the times they utilize common DMFs so the DMF review, you know, can be utilized for a couple of different applications.

And also the issues related to the review of the application are many times common, too. And so it helps to have a group of chemists being able to discuss the issues with themselves and the team leader in reviewing that.

And we found that the review is much more efficient and actually done much faster that way.

MEMBER PECK: Yes.

CHAIR BOEHLERT: Dan?

MEMBER GOLD: Gary, you mentioned, I thought, that some of the delays are caused by inadequacies in the drug substance DMF.

DR. BUEHLER: Yes.

MEMBER GOLD: I have not seen any publication by the Agency or by the Generic Division as to what deficiencies they are finding and what advice they might offer the industry in order to improve the quality of the DMFs so that you can, thereby, take advantage and review, you know, and reduce the review cycle time.

Why not do that?

DR. BUEHLER: Well, that's a good suggestion. You are right. There aren't any that I know of. Frank? No. DMF guidance? We don't have --

PARTICIPANT: Well, historically we've done this periodically.

MEMBER GOLD: I'm sorry. I cannot hear you.

DR. BUEHLER: Frank said historically we've done it with the industry.

PARTICIPANT: And probably 10, 12 years ago, there was a series of DMF conferences within the Agency where there were a number of instances discussed. Part of that long series was here are the most likely things that you will find wrong, frequently with DMFs.

And it's not something that we repeat. It's usually a special project when we go in and we look at them.

MEMBER GOLD: May I suggest that you consider putting out a type of document that other sections have put out such as Q&As on --

DR. BUEHLER: Sure.

MEMBER GOLD: -- and this one directed to DMFs to guide --

DR. BUEHLER: That's a good suggestion.

MEMBER GOLD: -- to guide applicants in that area?

DR. BUEHLER: Sure. That's a very good suggestion. And as I stated, we hope to have a meeting through GPHA with some of the DMF holders also, a webcast where we can connect people through telephone if they can't attend a meeting personally, and talk about these deficiencies, too. We've had these meetings on other issues within the office.

MEMBER GOLD: And there's another issue here, too, that since so many of the DMFs now are coming from overseas, I think the estimate is of the order of 80 percent of the drug substances are coming from overseas, I think we really have to broaden the approach we're taking in order to reach all the applicants.

DR. BUEHLER: Yes, we have --

MEMBER GOLD: All the DMF applicants.

DR. BUEHLER: -- we have to very often deal with their agents in this country with our deficiencies and our communications.

MEMBER GOLD: No, but I'm thinking in terms of international meetings in order to expedite this because it is important to get generic drugs on the market faster.

DR. BUEHLER: Yes. Okay.

CHAIR BOEHLERT: I have one last comment before the break. Ken?

MEMBER MORRIS: Yes, just to follow up on your point. I think one of the problems that gets lost in the shuffle with DMFs is that the companies, the drug companies themselves often don't have access to much of the DMF so the audience for that sort of a meeting is, of course, the DMF holders.

But depending on their stake in the particular active that you're talking about for the particular generic company, that may not be a compelling enough reason for them to make a lot of changes or to be a very forthcoming.

So I don't know the solution to that but I've run up against that before.

DR. BUEHLER: Well, the drug industry is clearly the customer -- or the DMF holder is the customer of the drug industry. So, I mean, we sort of do look to the drug industry, the generic drug industry, to actually pressure the DMF industry to submit better applications. That way their applications won't be held up.

MEMBER MORRIS: No, I understand the point. My point is in terms of delays that are a result or a manifestation of that, may not be something that lies within the control of the generic company itself.

DR. BUEHLER: No, you are -- that's absolutely correct. They don't even know what the deficiencies are.

MEMBER MORRIS: Right.

CHAIR BOEHLERT: Okay. Thank you all for very, very good discussions this afternoon. We're going to take a break now and reconvene at 3:45.

(Whereupon, the foregoing matter went off the record at 3:30 p.m. and went back on the record at 3:47 p.m.)

CHAIR BOEHLERT: Okay. Our last speaker of the day is Ken Morris. Certainly last but not least. He's already at the podium and ready to go.

MEMBER MORRIS: Well, that's because unlike Gary, who was only facing people who were trying to go golfing, I'm facing people who I'm the only thing between them and the bar. So -- what's that? Yes, when I hear the clinking of ice, I'll know I've overstayed my welcome.

Well, first of all, thanks for inviting me Judy, and Helen, and Ajaz.

The purpose of this is to largely report to the Committee on some of the activities that are going on with the senior CDER and DVM, and ORA folks to discuss and to flesh out the ideas of question-based CMC review.

And in the course of doing this, I'll try to differentiate my opinion from what we've actually done. But in the first half of that talk at least, what you'll largely see are the fruits of the work that we've all done as a group to explore this and brainstorm.

These are by no means final. And this is, as I should point out, a work in progress. We intend to continue this.

Lest you choke at another current versus desired state, let me say that this is a little bit different in that this is the assessment not only of ourselves and the upper management but Directors, Deputy Directors, Team Leaders, and Reviewers as well as the odd academic.

Right now if you -- and you have these slides so the fact that they're animated isn't going to mean much. I'll go through them pretty quickly.

The companies, as we've heard, may or may not have information. But it's not always in the filing. And there's not a lot of incentive for it to be.

The reviewers have to go through cycles of information requests and questions and then wait for the responses. So the companies may or may not have the clear scientific rationales for the choices but, again, they're not always sharing it.

And what this really results in is that the reviewers have to piece together data and observations to discover, if you will, the rationale for a specification, a method, a formula, or a process, et cetera.

And really we're saying that the reviewers are in a large sense of the word, and I'm not laying any blame here nor was the group, serving the function that should actually be done in the company and may well be being done in the company but just not shared.

In a desired state, what we'd like to see, of course, is that companies would include needed data with the filings and could share it prior to the filings, the end of Phase II meetings being the sort of the poster child for that concept.

They would include the data analysis to produce meaningful summaries and scientific rationales. So as opposed to the current state where if there are data missing in the reviewer's opinion and you ask for a data summary, in essence, and you get three boxes of chromatograms, that doesn't really serve anybody's purpose.

The idea would be to have meaningful summaries of the data, that is data that have been analyzed and interpreted in the light of what the company believes is the proper interpretation and shared with the reviewers and the Agency.

This should lead to the specific or the scientific rationales, the product development history sort of rationale we're talking about.

The reviewers then would assess the rationales and the summarized data presentations as satisfactory or not. And in that scenario, what you see is the potential to gain all of the things that we've been talking about all day and will continue to talk about tomorrow.

We had talked -- at Purdue, we had talked about sort of folding this into a risk-based development concept. And now I'll have to couch all this in terms of the Bayesian defensible risk and not. But I'll try to do that as I go along, Nozer.

First of all, the idea, as I said, is a simple concept. And if you use sound scientific principles in the design of the dosage form in the process, you've essentially met Phase I. Not Phase I in the clinical sense.

You have to identify the critical attributes for the raw materials, and we'll talk a good bit more about this as we go, identify the process critical control points for the processes, employ the proper analyses and process analytical technology concepts for process understanding and control.

And tie it all together with the appropriate informatics to feed the information forward and backwards for quality by design and in continuous improvement, which is the daughter of that. And that all leads to innovation, which is supposed to and should reduce risk.

Now we haven't talked very much about informatics today but clearly this is something that is an inescapable and inexorably linked to all of these initiatives. That it doesn't do you any good to collect data if it's not used much less shared between the organizations within the company, within the FDA, or between the FDA and the companies.

So what we'll do as we go along is expand on the righthand side of this list to talk about the associated regulatory question rationale or rationales.

The concept of risk-based development is really all about feeding forward, and I would add backwards, but feeding forward at the outset. This is after a set of quotes that Ali Afian had spewed at Arden House very passionately.

So if you look at it with a little more detail, what we're saying is you can explore the characteristics of the raw materials and possible variability in the raw materials and processing that are expected, that is expected based on some either previous knowledge or model, to impact on required dosage form performance. And we'll come back to what required means but, of course, that's another whole discussion.

Deciding on a dosage form based on the first step and the business case and selection of possible processes would be the logical next step. And what you'll see as a theme as we go through this is pretty much what you would expect if you are in companies you are doing now, and for the Committee, I would say that this is one of the focal points of what we're going to talk about. And I'll tender a hypothesis in a moment that's -- well, maybe I won't.

Then deciding what data are necessary to assess the probable success of No. 2, that is the dosage form, this can be from first principles, literature, design of experiments, et cetera.

Collect and analyze the data in the fourth step and you can see where PAT would play a role here.

Then Gap analysis and refining models as the development proceeds and finally the continuous improvement, which starts the cycle over again.

I wanted to use as an example here, and we sort of used this as an example in the team as we met, Solid Oral Dosage Forms. But, of course, we're not limiting any of the arguments or the hypothesis to this dosage form.

But there are really only two issues with Solid Oral Dosage Forms. One is does it work? That is the performance. And the other is can you make it? And that's the manufacturability.

If you look at the subsets of each of these, for performance right now we have -- and when I say dissolution, I'm not talking about the dissolution testing. I'm speaking of it more as Ajaz was this morning in that dissolution may be important whether or not dissolution testing is measuring it is a different question, dissolution in vivo, absorption, and stability.

And then each of those have subsets which are logically defined by the physical, chemical models that are around or that need to be developed. Where I have flags are places where we actually have models in place. And if you look at this really, the big unknown and the analogy here is on the old maps, when you'd get to the end of the continents, they'd say and here there be dragons, is the absorption, the clinical aspects.

But really what we're talking about is the manufacturability for most intents and purposes since we can't really fill that gap at this stage. And for manufacturability what I have here is physical properties and processes and then those are broken down into their component parts.

So this is an overall example of what the requirements are for the dosage form. They're really -- what we talked about the required part in the first step here, the required dosage form performance, that's really what we're talking about ultimately. But, of course, we aren't there yet.

Well, how realistic is risk-based design, if you will? Or the whole concept we're talking about really. And I start this by stating this premise that as all good pharmaceutical scientists and engineers know, a formula without a process is really a pile of powder if it's a solid oral dosage form.

So even during API characterization, developing a formula implies an expected dosage form and a process or range of choices. And the example is here you don't care about the compressibility of a lyophile, for instance.

But I'd submit that even at the very early stages, if you're sitting at a pre-formulation desk and somebody throws ten milligrams of material on your desk, you know exactly at that point what the dosage form is going to be.

Now you may not know exactly what option within the dosage forms you are going to have, but you're going to know if it's a tablet. If it's an analgesic, you're not going to have an ocular injection is my standard example.

So API characteristics are among the first information you need to feed forward. So if we look at that though for the people that are attending in the gallery as well as the Committee, you have to be saying well what's different about this than what we do right now. We do all of this now.

A good formulator, a good scientist, a good engineer will just tell you right away that this is the thought process they go through. But the difference is that we're not doing it model based. We're not sharing and feeding the data forward and backwards. And there's no informatics to capture this in a meaningful way. In other words, it's the process.

The process itself is what is new. And the process itself is what's necessary to bring all of these ideas to fruition.

Just as an example, just as dipping the toe into the pond of biology here for the moment, even at very early stages when you receive just a molecule, you can -- even a molecular structure and a small amount of material, you can assess solubility impact on pre-formulation on absorption using relationships such as the modified absorption parameter, which does a fairly good job just based on molecular structure and some estimates that you can make either computationally or with simple experiments on whether or not even a low soluble drug will be absorbed.

Well, you've already seen this slide and I'm not -- this is actually from Rick Cooley from -- that Toby showed this morning so he didn't have to cite it because it was his company but Rick Cooley from Lilly actually presented this.

If we look at this in terms of the overall variability of the process, a variable input will lead to an invariable product if you hold everything in the middle constant. This is just common sense.

So the idea is is to be able to adjust it. The catch here is what are you going to adjust, that is what are the critical attributes as well as what are the critical process points, the critical control points in the process? And that's what we're going to talk about.

So the example that we started with in the team was actually API selection. And the idea here was to explore the question of how do you know what questions to ask? So now you have people who are going to be looking at your filings as they come in. And presumably now data would have been shared early on.

And the first question that we all agreed on, we did this as a team, was what's the -- what the first question you'd want to ask if you had your choice is what dosage form are you going to be using? So the first thing I want to know is what's my dosage form?

Then the questions went on. What's the second thing, et cetera? And the hypothesis that we're proposing here, and that the Committee can assess during our discussions is that the development scientist and the regulator are or should be asking many or all of the same questions. So the same process that the scientist is going through in designing the dosage form and designing the process should be the questions that the regulators are responding to because that's ultimately what will determine whether or not the dosage form has been designed by quality.

Well, if you -- I got permission from Moheb to use the pyramid at Arden House so I extended by non-exclusive license to it -- if you go through this pyramid of questions, what you start with is what is intended dosage form, which is what we just said. What's the intended process? And then stepping up through the various tiers of the pyramid to the point where you've actually identified the critical attributes.

And the other dimension here, much like Ajaz's sixth dimension, is time, of course, because that will change. And this will, in fact, be a cyclic process.

So this is the hierarchy of questions that you might expect to see if you were to make a filing and certainly if you were designing your dosage form. And it's really a fairly logical progression of consideration of the physical chemical properties of the API.

If you have an API, it will either be a solid, liquid, semi-solid biological. And what the question is is what are the critical attributes of each of these?

Now if you select one, we'll select solids here because that's what I know best, of course, not that they have to limit it, then if your API is a solid, you go down a logical process of deciding whether or not it's crystalline or amorphous, whether or not it's a polymorph, a hydrate, or something else, and when you've selected the one that it is or identified the one it is, there will be certain criteria which will tell you what the characteristics ought to be and then this might take you to not a decision tree but an event tree as Nozer said, an event tree in the Q6A.

Then this would at least give you the range of possible critical attributes, which puts you back on the path of this thinking.

Now I'm not saying that you have to follow necessarily this sort of a chart. I'm saying this is what most formulation people will follow -- or pre-formulation people will follow intrinsically.

Then you say well, if the dosage form is a solid, it's going to be a capsule, a tablet, or other. There are no pills, by the way, Gary, left any more.

So you go from tablets to selecting which particular choice you have for manufacturing the tablets, for the various critical attributes taken into account. There's wet granulation, dry granulation, dry compression.

Once you've selected that then the attributes that are potentially critical should be fairly well known. And this is a case where maybe modeling gives you the prior knowledge in some cases.

This is then cycled on data to determine what the risk really is. And in this case you might think of it in light of what we heard this morning as generating prior knowledge. And then hopefully you identify the critical attributes.

If you move this on logically to the process design, you start from where we just ended with the raw material critical attribute selection, take this up the ladder so that what is the model for the process. And the what processes are viable, you've already answered that in the raw materials section based on the mechanical and chemical properties of your material.

What's the model for the process critical control points -- say that three times fast -- and then the basis, the possible PCCPs based on the raw materials and the choice of response factors. And there you go continually until you do your design of experiments and ID preliminarily what the PCCPs would be, cycle back until you again optimize it.

So what I would say is that all of these are logical top level questions. And the more detailed questions are the ones that we were just going through in the raw material or the API selection.

Let's use an example. I actually picked on Q6A quite independently of Ajaz. He knew that I was going to do this because I sent him the slides. But he didn't tell me he was going to be doing it.

I'm not picking on Q6A particularly but it was just a good example to use because there are some good things and some not so obvious things in the event tree that Q6A represents. And I think what we're really talking about doing is changing it into a decision tree based on what we're talking about here.

So Q6A in the first table, I can't remember if this is 6 -- I think it's table -- I can't remember what it is but at any rate, the first question is can different polymorphs be formed? Okay, this is fine. If you understand the solid state and know polymorphs are formed, you're done. So there you are at no and no further action.

If there are forms, they must be understood. So it's not enough to just say yes, let's characterize them. What you really have to ask is what are the relative stabilities of the low energy forms. And if you don't know the relative stabilities, at least explore what it is that's -- what information you have that's possible to help you explain that or at least elucidate it.

And those are the right questions for the scientist and regulators. And as we go through the next few tables, we'll try to carry out the same analysis.

The second part of the table is do the forms have different properties, solubility, stability, melting point, et cetera? If it's no, then no further testing or acceptance criteria for drug substance required.

So that's okay. But when we're considering the product, the logical first question should be quite different because the answer here is if they do have different properties, the question is is drug product safety performance or efficacy effected? Well, before you get to that question, you really want to say based on what is known about the material and the process, what, if any, change in form would be expected?

So if I have something that is particularly soluble and I'm wet granulating it and I know that there are form possible, then I might expect that I could either change a less stable form to a more stable form during granulation or I might trap a metastable form on drying. Those are the sorts of questions you would ask long before you got to the point of whether or not it actually occurred.

So if the answer is none based on the scientific understanding, then a confirmatory test during development should suffice because it is possible but you're saying that there's no logic to say that it should happen.

Otherwise, if there is a potential, the next question should be is the observed change the one that you expected? Now we've just gone through this. You should know what change you expect to see based on your process and the properties of the API. And the question is does the change that occurs match what you expect?

And then finally, this is the question that will give hiccups to a few folks I suspect, is what was the rationale for selecting the processing step responsible for the change?

Then we're back to the tree again. So on the third section, it says does the drug product performance testing provide adequate control if polymorph ratio changes during the formation of the product?

And here it might be reasonable to ask instead does the performance testing relate to the performance of interest? And this is what we were talking about before.

Now you may not have an answer for this but that's clearly the question that you would want to know. If the change in ratio makes no difference, then it may not be an issue. If it does, obviously you have to establish acceptance criteria. And if the answer is based on scientific understanding, we're back to here.

A next question would logically be based on the understanding of the form's behavior, what would the expected trend -- that should be expected trend in transformation be? So if I have a ratio of polymorphs and obviously one of them is more stable than the other, you would expect against any other information that the metastable form would transform to the stable form.

If it doesn't then you've -- well, number one, you have the paper. But number two, it brings into question whether or not you understand what's going on.

And now these questions are pretty specific but these are the kinds of questions, these are the level of specificity that you would really like to know in advance of seeing the questions I'm assuming.

Going to the second part of the third table is does a change occur which could effect safety or efficacy? And here I would say does the observed change correspond to an understood and expected transformation? If not, the system is not well understood -- is not as well understood as you thought it was.

And if that's the question, then presumably you would have addressed these sorts of issues early on but the value of this is that if you've addressed each of these during development, then by the time it gets to the regulator and they're essentially echoing these questions, you'll have answers for them and that would expedite the process.

Virtually all companies on the innovator side are doing polymorph screens. We've recommended focused polymorph screen for generics. Because of the number of companies, I don't know the relative ratios but as an example, this would be the case.

Well, let me use the last few minutes here to talk about a couple -- a specific example. I may skip the last section. Judy, just give me a high sign if my time starts to run out. Six? Okay. Yes.

Okay, this is an example that is actually from -- largely from Greg Amadon at Pfizer in Kalamazoo from talks that he's given over the years. But it illustrates one of the things that Dan had raised and Garnet had raised with respect to excipients. And that's the mechanical properties.

We treat table formulation more or less as a black box. Not so much from the chemical sense because the chemistry is often well known by the time you get it. Certainly if it's generic you know it pretty well but in terms of what you would use and how and what the ratios you would use to give a tablet that had acceptable strength characteristics, counting uniformity as well as performance characteristics.

And if we look just at the mechanical properties elements or aspects of the raw materials, there are several tools and I'm just going to introduce one here which are the Hiestand Indices. And Everett Hiestand, when he was at Upjohn years ago, developed indices for bonding, brittle fracture, and strain measurements as a function of relatively easy to get data from relatively small amounts of material.

And these data are tensile strength, hardness, and things that you can get to fairly easily. And I won't go into the details but let me show you some of the results.

And if you look at the overall range of materials that we are involved with in normal manufacturing, I would say this extends even more so to biologicals, is -- I should say even to biologicals, not more so -- everything we deal with if you look at in terms of the mechanical properties and just focus on this column for a moment where we're talking about the description, falls into the category of moderately hard to soft. There's nothing that's really hard. There's nothing that's really soft.

So everything falls into this category. And here you see APAP at the top and starch at the bottom. This is from a great chapter by Rowe and Roberts in mechanical properties.

So we're really dealing with a fairly limited range. And we're dealing with a fairly limited number of excipients. But the APIs, of course, can change.

Well, if you look at the importance of evaluating these indices up front, this is an example of Phenacetin. And here we have a case where in the compaction -- in this compaction, in the tri-axle compactor, we have a compound in Phenacetin with a very low bonding index.

And the result of that is that even though the Brittle Fracture Index is not too bad, that in the dye it comes apart. Now this is -- I'll show you a couple other summary slides but the point is that there are threshold values, if you will, that I would imagine would lend themselves fairly well to statistical analysis apriori that have to do -- that are shown here actually that have to do with their relative properties that should dictate this apriori.

So if you look at that bonding index of excipients versus drugs, you see as no surprise that microcrystalline cellulose has very high bonding index, right, which is also why it's a compaction aid.

If you look at drugs, they vary but drugs tend to be, on average, lower. And if you look at what it takes to make a good tablet, you'll have to have some combination of those.

Brittle fracture index is the -- is, I guess, in a sense one of the most dramatic of the indices because when it fails, it fails spectacularly. Here is an example with a very high brittle fracture indices.

High brittle fracture is bad because it means that on expansion, the compact can't maintain itself. And what you see here is with a high brittle fracture, as soon as the compact is ejected, it laminates. It just comes apart. And if you were to put an acoustic sensor on it, you could hear it. I mean it's very noticeable.

And similarly, if you look at the brittle fracture index now across a series of excipients, you can quite easily determine which ones have the brittle fracture indices that are less desirable or more desirable.

And as Garnet talked about earlier, corn starch being one of our formerly primary diluents, had its own issues with respect to brittle fracture index, which is why a lot of it was granulated, wet granulated.

So put this together and what Greg had done here was to plot the brittle fracture index versus the percent of drug mixed with an excipient for several compounds listed here, Drug X, which is Pfizer, I'm assuming that's not one of the bathtub drugs.

And what it shows is that adding 30 percent of a non-brittle excipient makes a mixture much less brittle and, in fact, quite compactible, which could be predicted with grams of material. So we're talking a long time before you get to a kilo lab and certainly in the generic industry something you could do Day 1 with the proper equipment.

And Greg went on to develop a semi-empirical model that shows how H here is any of the indices or properties so here we have hardness, tensile strength, brittle fracture, and bonding index, are all related via a logarithmic relationship so that there at least is within products and within excipients a predictability.

So if you think about this in terms of the scope of excipients that are available to us, it's already been -- data has already been collected on most of these excipients so these are available in literature.

So there is the possibility of using these data as is to do prediction up front with either very little measurement or at least feeding backwards.

As Ajaz had said, if you have in a big company I don't know how many products a big pharma makes. Over a hundred I suppose, right? And generics can make up to 500 at a plant, the amount of data you have is staggering. To be able to take these data and bring them back, it's impossible to imagine that you couldn't perform some data analyses that would give you your prior information for your Bayesian treatments, for instance.

No?

MEMBER SINGPURWALLA: There's a confusion of concepts.

MEMBER MORRIS: Except for the confusion of concepts --

(Laughter.)

MEMBER MORRIS: -- that's absolutely true. Right. Yes, we'll get back to that.

Okay. So if we look at our beginning slide again at this stage, then the questions that you would expect to be associated with these steps so far would be what were the principles applied and were they appropriately applied?

So if you're using the bonding indices and the brittle fracture indices, were they appropriately applied? And I would say the answer is going to be yes in most cases for the folks who have been using them.

How are the critical attributes identified in the formula design? I mean this is Product Development History 101. It exists in many companies. Whether or not it's shared is a different question.

The next level, as we talked about on the second pyramid, is the identification of process critical control points. And how am I doing time-wise here? I'm over?

CHAIR BOEHLERT: Not so hot.

MEMBER MORRIS: Okay. I'll skip through this section.

CHAIR BOEHLERT: Well, you know, we do have some questions to address for Ajaz this afternoon.

MEMBER MORRIS: I understand.

CHAIR BOEHLERT: I don't mind keeping you late but I think, you know, the rest of your Committee members might mind.

MEMBER MORRIS: Yes, I've got two slides left.

CHAIR BOEHLERT: Okay, good.

MEMBER MORRIS: Because I'll skip the example but I want to get in this point. And that is if you look at the relationship between PCCPs and scale up with monitoring, the basic approach is captured as two simple process understanding premises.

First is that PCCPs are preserved throughout the scale up process. That doesn't mean that the magnitude doesn't change. It may. But the variables being monitored reflect the state of the process.

And second, as was alluded to this morning, and I can't remember who, I apologize, is that monitoring material properties makes scaling less equipment dependent so that even as you change equipment, if you're monitoring the same PCCP, the value may change but the absolute -- or I shouldn't say the absolute but the PCCP being monitored is the accurate one.

And I'll just skip to the last slide which says that based on that example that you just saw, that in addition the next questions are how did you identify the critical attributes?

The next question is how did you identify the PCCPs? What were the basis for the analyses selection? What are the supporting data for all of the above? And finally, the product development history should reflect everything that you've said. And if it doesn't, it's a different issue.

And asking the right questions at the right time, feeding forward and back between disciplines, designing the product and process against meaningful metrics must start in R&D. Development of meaningful specs, of course, results only from the identification of the scientific basis. Real-time monitoring is a big advantage but not absolutely necessary.

Process understanding for quality control is known functionality; that is the models against which data are used to control the mark. And I can't emphasize the model basis enough.

What you get from this, I think we've heard quite a bit. I'll just -- this last point here is that in tech transfer, you get a more realistic process to transfer, which is Gerry Migliaccio's leg up statement from Arden House saying that we don't need a final thing but we really could use a leg up so we're not starting from zero.

And finally just to acknowledge Greg Amidon from Pfizer in Kalamazoo, CAMP, again, with G.K. as our leader in CAMP, of course, Abhay Gupta is the graduate student who did the example you didn't see. And finally the team, which was headed up by John Clark but include Moheb and Rafad and a lot of the people that are here as well so with that I'll end.

Thank you.

(Applause.)

CHAIR BOEHLERT: Thank you, Ken. Any questions for Ken before he departs?

(No response.)

CHAIR BOEHLERT: Sorry we missed the example. I was interested but, you know, we are running out of time.

MEMBER MORRIS: No problem.

CHAIR BOEHLERT: Okay. Ajaz did you have a few comments?

MEMBER HUSSAIN: No, I think what we have tried to do is to give you a sense of what is happening outside FDA, especially in ICH, ASTM, what is happening within FDA, especially from a more management perspective but also from a science perspective.

And we're hoping that I think if I could just put the slides on the questions -- this is a series of questions that we posed to make sure that we are on the right track. And I'm hoping that your discussion and general thoughts on some of these questions might be useful.

You have a printed copy in your packet. Usually we place this on the -- but maybe I can stand here and maybe forward this for you. So it's up to you how you wish to give us your feedback on these questions posed. So --

CHAIR BOEHLERT: Well, I propose that we go through these in order. First and third are relatively short. The second one has many subparts. So we'll start with the first one.

Do you agree that current activities within ICH and ASTM are helping us, FDA, move toward the desired state? They seek our recommendations on how to ensure these activities are synergistic. So I'm looking from comments from the Committee.

Everybody is saying yes. And particular comments? G.K.?

MEMBER RAJU: I agree, very strongly agree. I'm not that familiar with the ICH process but I did go to the ASTM process. And it really is very synergistic as Don had said. They're putting a lot more detail to it and bringing in a lot of outside industry expertise.

So I think they are synergistic. And the synergies are happening with the individual people. I don't know whether there is a possibility for a more structural synergy among the people here but in terms of what FDA does and what ASTM and ICH does, when I spoke to Don earlier today and I asked him that question, he didn't think so.

But there could be a time when it starts becoming really duplicative. I've seen people talk about pharmaceutical development in at least five different organizations. Everybody's versions of what they want and what is risk.

Everybody has risk tool box, these five organizations. So at some point, it's good to have a lot of people do it to get the debate. But at some point it's probably not.

And we're not there yet but we probably will be in the future.

MEMBER HUSSAIN: I think I'll just repeat what Don had said in the sense, I think, the scope and the depth and the details. These are two different standards or guidances, whatever you want to call them.

If you look at the E55 structure, what we're hoping to do there is to create a framework. E55's focused primarily on standards for PAT. And development is clearly broader than that in a sense.

And we're hoping the details that would come about through ASTM's standards would be standards that can be cited. And we really don't have to issue Agency guidelines on some of those things.

So Q8, Q9, Q10 will evolve with a very different focus. And the ASTM would be more of a technical standards rather than guidelines and so forth. So I think there is a difference.

CHAIR BOEHLERT: Ken?

MEMBER MORRIS: That raises -- oh, I'm sorry, were you not done, G.K.?

MEMBER RAJU: No, I'm all set.

MEMBER MORRIS: The one question and it actually came up at the last ASTM meeting, will the ICH be able to -- or not be able to but will they take advantage of the ASTM standards in citing them during their discussions?

MEMBER HUSSAIN: Well, that's a very good question. And I had brief discussion with John Berridge about this a the sense. The Yokohama meeting in November is probably when I would like to sort of bring this topic up to ICH and keep them in the loop on this.

John and I discussed this before the Washington meeting and felt that well, the ASTM had not crystalized far enough to really share some of this. But I think starting in Yokohama in Japan in November, we'll make sure that the ICH is fully aware of what's happening here and seek that synergy.

Informally, I have discussed this with all of our regular counterparts in Europe and Japan. And there are a number of European members on this ASTM and Japanese members. And I'll broach the subject of maybe the regulators joining some of the ASTM groups also. That's a possibility.

MEMBER GOLD: Ajaz, you're -- I just want to ask, you're not going too fast in contrast to the regulators elsewhere, the Japanese or the Europeans, are you?

MEMBER HUSSAIN: I hope we are.

(Laughter.)

MEMBER GOLD: Well, we have to move in concert. And do you believe that you're going to be able to move in concert?

MEMBER HUSSAIN: That's the real --

MEMBER GOLD: I asked the real question.

MEMBER HUSSAIN: -- question. Well, move in concert in the sense we will lay the foundation and hopefully they'll come and join us.

(Laughter.)

MEMBER HUSSAIN: No, I think the ICH process, the Q8, Q9, and so forth, clearly are toe to toe, we're moving together in a completely harmonized fashion.

We have plans I think with respect to the PAT process itself, we have an ongoing dialogue with the European PAT Team. I think we are fairly aligned in many ways the aspect which is of interest is our European regulatory colleagues are hoping that a lot of the PAT concepts will get incorporated in Q8.

And the definition of PATs exactly we agreed in Washington will be the DA definition. And Yokohama will get this concept in Q8 in a very broad perspective. So that's one approach we've got.

Plus, I think, our PAT guidance is becoming final soon with announcements. And we are planning a series of workshops, inviting our regulatory colleagues from Europe and Japan to participate in the planning Committee. We're working with ISPE in setting up some of these workshops in Europe and Japan. And the process has just started.

MEMBER GOLD: Well, I want to say I'm very impressed by what I've heard today and reading the black book that you sent ahead of time. I just want to make sure we're not so far ahead of the others that we are not going to have unanimity.

CHAIR BOEHLERT: Okay. Joe?

MEMBER PHILLIPS: I think definitely I support everything that's been said by the previous commenters. But the activities in ICH and ASTM are definitely moving us forward toward the desired state.

What do we need? We need continued commitment of the key players, many of whom are sitting in this room, from both sides of the ocean. We have the regulators, we have academia, we have industry on both sides.

And from what I'm hearing, I have a lot of contact with industry and regulators in Europe and Japan, there's a lot of interest in this activity. And they just want to be kept abreast of what's happening. And I think the FDA is to be commended for their efforts to keep everybody well informed. Office of Compliance has been working heavily in some of these areas.

Any time some of my colleagues in ISPE have had a question to raise, it's always easy to get a direct answer from this team. So I just hope that the same team stays committed and involved because it takes prime movers and shakers, so to speak, to keep this thing going.

But it's going very well at the moment. But who would have thought two years ago we'd be at this point?

MEMBER HUSSAIN: Okay. Should I move on?

CHAIR BOEHLERT: Yes, let's move on to the next one.

Nozer?

MEMBER SINGPURWALLA: What is the desired state?

PARTICIPANT: California.

(Laughter.)

MEMBER HUSSAIN: Well, I think I was getting tired of showing my desired state slides, maybe I ought to keep these. It's prior knowledge.

(Laughter.)

MEMBER HUSSAIN: So prior is all mixed up right now so -- no, I think the desired state simply is to -- in a -- sort of a conceptual way is to increase the level of scientific knowledge that is shared between the agencies so that we can make more science- and risk-based decisions which removes -- brings or removes the hurdles for continuous improvement and reduces the burden on all of us. And improves the efficiency of the whole system.

I think clearly we believe that the quality of the products available to the U.S. public is adequate for intended us. We have an opportunity to improve the efficiency but at the same time a few years from now, the complexity of our systems is increasing especially with biophysics, nanotechnology, and others that are coming. And we are getting a better handle on variability today through pharmacogenomics and so forth.

So ten years from now, the current aspects of quality may or may not be adequate. So I think it's preparation for the future as well as improving the efficiency of today's systems.

MEMBER SINGPURWALLA: Well, if that be the case, then I'd like to comment on that particular issue.

Based on what I've been hearing and what I've been seeing, I find the progress of matters is rather academic and conceptual. There are general principles, principles of quality control, principles of management, principles of data analysis. The focus has been a discussion of the principles.

Somehow we have to get down to a demonstration of how these things work. And I believe I have said this before. What I think is really needed are some concrete examples. And I'm proposing that the FDA work in collaboration with industry, the drug manufacturers, both the generic and what is it called, the creative, the original --

PARTICIPANT: Innovators.

MEMBER SINGPURWALLA: -- the innovators -- actually I wouldn't like the word innovator if I was a generic drug manufacturer but I think to work in collaboration with them and come up with demonstrable examples of how these new ideas come to work.

Otherwise it becomes like a lecture in a business school where they talk about everything and need to follow up with case studies.

MEMBER HUSSAIN: The point is well made and I think well taken. That's a struggle because, for example, with the PAT arena, we have about seven submissions at different stages; one approved, one major complete PAT submission from start to finish. We actually have a comparability protocol in house right now. So -- but it's proprietary. We cannot share it.

And that's a struggle we often have is we are unable to share what we get because we're not allowed to share it. We are working with Pfizer, for example, through a collaborative discussion development agreement so you will see some publications coming out on some technologies through that collaboration.

We are in discussions with two other companies on starting a collaborative discussion development agreement so there will be publications but I think G.K. Raju made that point also. I think we have an acute need for a case study. Otherwise this remains theoretical and I agree with Gary in the sense we have been discussing concepts for the last two, three years.

But at least we have agreed on the concepts. It's time to move on to some tangible examples that are necessary. And we can do some through our research which we are doing at Purdue and others. But I think you really need a real life example. Somebody has to step up and say we want to share this.

MEMBER SINGPURWALLA: And there is a little bit more to that. Not only should there be an example but in the end, industry should come up to you, to the government, and say thank you, government, because you made us do these things. We have benefitted and these are things we would not have done on our own or it didn't occur to us. And you have paved the way and not only improved our profitability but improved the general state of the art.

I think you need something much more tangible so that industry can come back and compliment you if that's possible.

MEMBER HUSSAIN: I'll look at Helen. Let her answer that one.

(Laughter.)

CHAIR BOEHLERT: Ken?

MEMBER MORRIS: Yes, just -- we've talked about this and in terms of the reduction to practice, if you will, not in the patent sense, and we're doing things now not exactly in lock step with FDA but in terms of developing processes by -- in the quality by design sense that certainly will serve as a partial example, I think.

And even though it's not being done under the -- it's not being funded by FDA but they're participating in it so at least we'll get to the point of formulation of process design, I think, which should be a concrete example that will be publishable. And that's ongoing now. So -- but I realize that's only one and it's only partial but to the point.

MEMBER HUSSAIN: Okay. I think going on to some other set of questions, two has subparts. To facilitate momentum with the desired state, FDA is providing incentives by ensuring that use of new technologies and additional information about a minimum acceptable submission standard will not be regulatory requirements.

Gary raised that again. I think that's an important point. But will be opportunities for companies to demonstrate a higher level of process understanding and risk mitigation. And, therefore, a basis for regulatory flexibility. That is example to reduce the need for prior approval of supplements and so forth.

For implementation of these concepts a clear demarcation of "minimum" and optional information is necessary. And I think this was a significant point of discussion at our ICH Q8. And as ICH Q8 goes to Step 2 in November, you will see how we have tried to sort of address that.

But I thought I'll pose this question to you in the sense this is a significant challenge to sort of achieve this goal. And especially because the European and the U.S. systems were quite different. And the expectations in Europe were different than what we have, the minimal expectation.

So any thoughts that you can share or any insight that you can share on this would be very helpful. But let me just complete the question, Part B of that also.

Quality by design and manufacturing science are considered foundation for rationale risk-based decisions. Please recommend how these principles should be linked to risk to suggest failure mode effect analysis. So we're looking for general principles that, I think, you would wish us to keep in mind as we progress in this area.

MEMBER SINGPURWALLA: I think I can respond to Question B. Question B, of course, the failure modes and effects analysis is basically a technology mostly based on engineering or whatever subject matter discipline is at hand to essential work your way up towards probabilities of certain undesirable events.

And so those probabilities feed in to the decision, you know, to the decision tree. So the failure modes and effects analysis would be an event tree, which traces the course of events which lead to failure.

And superimposed on that would be the probabilities of the various sub-events which lead to failure. And that probability will be fed into the decision-making paradigm. So those two are easily, you know, are easily put together as a package. And that's the right way to go.

So the question is a good one. And there is an answer to it.

CHAIR BOEHLERT: Gerry?

MR. MIGLIACCIO: Let's talk about A, Ajaz. I guess I have this -- it almost implies and A or a B, one or the other.

And when I think about the optional information, the optional information will come in degrees, not you either have it or you don't, you know, we can't look at the NDA as a line in the sand. So you may get some of that optional information in the NDA and six months later, you may get much more.

And so the regulatory flexibility granted with the NDA is at a certain level. And the regulatory flexibility granted six months down the road when we supplement with that greater process understanding becomes greater.

So I'm a little concerned about the clear demarcation statement that it's yes, there is some information that will be optional. But the degree also has to be understood. And I like Gary's if this, then that, you know? If we could put that map together.

If you get this, then that's the regulatory flexibility that comes along with it. And then if you get more of that, that's what comes along with that.

MEMBER GOLD: Gerry, I'm not clear -- I don't see it your way. I interpret that question as saying what more than we give presently would be advisable for improving our knowledge or improving the knowledge of the process that we provide to the FDA? And that I see this as not asking for necessarily more than we're giving now in order to get approval.

MR. MIGLIACCIO: No, in fact, we're not talking about, you stated more. We're saying different. The knowledge that we're providing is different. It's more science based, more risk based.

MEMBER GOLD: No, I understand. But I don't see that as asking for anything more in terms of more science or more knowledge than we're currently supplying in order to obtain an approval. There is nothing in that that I see that requires us to elaborate beyond the information we're providing currently.

However, if we do provide more information, then this presumably allows us to make changes with lower requirements, that is lower time limit requirements. So we may be able to go from a PAS to a CB30 or whatever. But I do not see that statement as saying we must provide more.

MR. MIGLIACCIO: No, and I didn't imply that we must. What I'm saying is that what we provide will be in degrees.

MEMBER GOLD: Yes, I certainly think that's possible.

MR. MIGLIACCIO: There's an impression sometimes in these discussions that it's all coming in the NDA. And it's not all coming in the NDA. It will be learned. It's a continuous learning process. It will be learned in the first six months of commercial manufacturing.

And, therefore, the flexibility has to be there to go back in with more process understanding and, of course, get greater regulatory flexibility.

MEMBER GOLD: But, Gerry, I've also seen instances where companies have more information available to them at the time of the filing that they don't believe they need to provide because the FDA has not called for it. And so they just hold it in their, you know, they hold in their own file.

MR. MIGLIACCIO: Because the perception now is if we supply it, it will extend the review period.

MEMBER GOLD: Correct. Or may extend the review period.

MR. MIGLIACCIO: That's correct.

MEMBER MORRIS: Is this trying to get, though, at the question we were talking about earlier which is, you know, instead now we have, you know, three batches and then you file? Or is this saying that there's no set number?

MEMBER HUSSAIN: No, I think -- well, let me give you an example that I think might be relevant here. I think Gary had some of that information in his slide in the sense, in particular on the generic side we have a tendency to be quite conservative in terms of actually requesting an executive batch record.

And in some cases or sometimes, that executive batch record is your sort in process control and so forth. So any change requires a supplement.

But that is because we often have limited information in how to establish specifications, one biobatch and so forth.

So that is the current way of thinking. That's fine.

What I might suggest is the optional type of information might be you have pharmaceutical development information and other information that provides much more flexibility that would not -- that would allow us to move away from that executive batch record as the sort of a basis of sort of establishing something to something more of process understanding basis.

So that's how we're sort of approaching it.

MEMBER HUSSAIN: Gary and Moheb, any thoughts on this?

(No response.)

MEMBER RAJU: Judy?

CHAIR BOEHLERT: Yes, G.K.?

MEMBER RAJU: On the two questions, Ajaz, I go B first and A second.

On B, I believe that the priority should be since manufacturing science and quality by design are both levels of performance and states of knowledge and can be changed by processes, that on B the priority should be on defining those levels and the processes that enhance it.

And the tools -- so the tools only have context in that -- only have meaning in that context. I do not want to say please recommend how these principles should be linked to risk tools yet. We have to focus on the characterization and the processes for it.

The tools can be a tool set just like we have a lot of tool sets. The links shouldn't be made too early because we haven't done the first step first. So let's keep the tools in a portfolio of tools and understand them, bring them in from outside the industry into ours.

Let's focus on our industry and defining what we do transparently based on principles of science. And then connect the tools. So that would be my thought on that.

And there's a scientific process to the tools, too.

MEMBER HUSSAIN: If I may --

MEMBER RAJU: Sure.

MEMBER HUSSAIN: -- suppose we remain with an empirical approach to this so we don't have a mechanistic understanding and so forth, so we are seeking causality or we're seeking correlation through an empirical model approach, say design of experiment, okay?

Now the number of potential factors that may be critical can be a large number depending on the process. And an approach could be is this is -- I'm basing this on the presentation by Amgen at Arden House, is you start with a failure mode effect analysis based on all your expert opinion information that's there based on historical know how to sort of tease out what may be the critical variables. And then design your experiments around that.

So that is sort of another way of looking at it. So that's -- there are many different options there because I think if somebody wants to do a design of experiments, they really have to manage the resources and their commitment very carefully. Otherwise that can get out of hand.

So that's one way of approaching that. But the other way of approaching that is through screening experiments early on and then sort of designing -- defining your design space and then doing a failure mode effect analysis. So you need to have flexibility of going either way.

MEMBER RAJU: So this is Bob Sweeney's work at Amgen?

MEMBER HUSSAIN: Right.

MEMBER RAJU: He did a nice job of saying this is the process. Here are the variables. And then he put fault modes into context.

MEMBER HUSSAIN: Correct.

MEMBER RAJU: Because he did that, it was a very good story.

MEMBER HUSSAIN: Yes.

MEMBER RAJU: But it's not clear that that's been done. And if it's not been done, then it has to be done first before we bring the FME -- the tool only has context within a goal and a process to get to that goal. So I think it works fine that way.

In terms of A, I have a somewhat similar answer but at this point because the demarcation, you said that what you get in a submission is variable. And you said you have some information, more information, sometimes you have less information, and sometimes you have different.

The criterion of what is more and what is important has not been laid in place yet. So it's somewhat dependent on the company and their interpretation and their strategy.

It seems like two things would help on A. First, you said it was minimum and optional.

Probably independent of the answer to A, to make sure that everybody believes -- that everybody in the FDA believes that and will implement that is extremely important because everybody -- I can hear a number of cases where people say I know Helen and Ajaz, they would believe that. But how do I know about the guy who is going to do my review? Or the person who is at the field, for example, which may not be relevant in this case.

So just making sure that what you believe in is somewhat uniform although we all, as human beings, we'll never be uniform.

Second, how about making it one of two possibilities? Making it the company's choice because it's still somewhat not fully characterized, to present to you here is minimum. And have here is the optional, what shall we do with it? Either submit them both and say you make a decision based on this and we can get a better deal based on this?

Or here is the optional. Can we discuss with you whether we should submit it or not?

So they make their first call on minimum versus optional. They decide to submit it. You start with the minimum and your specifications get changed based on that. But they don't pay the price for the optional because you say they wouldn't.

You get the minimum and the paying the price is more in the context of a reward. And it could be done informally first before it's formal. How about that? It seems like -- just think aloud now.

DR. NASR: If you allow me to make a simple comment here. I think this is very good discussion. But in my mind the issue before us is much simpler. And let me elaborate a little bit.

I think the existing system that we have is working. Why is it working? Because we have quality pharmaceuticals in the market. So the existing system is working.

So in the future, I think companies, sponsors, will have to follow one of two approaches. The existing regulatory process and the regulatory framework with the guidances in ICH and the submissions and the meeting or lack of or whatever.

And we will continue on and when you make a change, you have to come to us, we'll supplement. And we'll evaluate the supplement and we'll make recommendation. And you go ahead and you manufacture or not manufacture.

The future paradigm we are describing and sharing with you today and Ajaz, I think would agree with that over the years now is you share with us in advance, and advance means either at the NDA stage or shortly after or long after, your understanding of the manufacturing process, your ability to deal with the change, and then back to such a change on the critical quality attributes.

And based on that understanding, you're sharing in the form of pharmaceutical development report or comparability protocol or whatever, we will give you the freedom to manage your own change.

So in my mind, it's very simple. You can stay put and do what we are doing now and continue to have quality pharmaceuticals in the market. Or if you want to follow the quality by design and the new approach, which we believe is beneficial to you, to us, and to the public, and that provide you with the regulatory relief that you have been asking for for years and years to manage your own manufacturing process.

So in my mind, it's fairly simple.

MR. MIGLIACCIO: Judy?

Moheb, do you accept that we will have some hybrid situations?

DR. NASR: We do. When I said comparability protocol, that's a hybrid.

MR. MIGLIACCIO: Yes.

DR. NASR: When you talked about supplements shortly after, that's a hybrid.

MR. MIGLIACCIO: Right. So we'll have --

DR. NASR: It's not a clear cut --

MR. MIGLIACCIO: Right.

DR. NASR: -- either or.

MR. MIGLIACCIO: Okay.

DR. NASR: And I think the third point that I failed to make, Gerry, and I'm glad you made this comment, is I think our role collectively is how to move from the existing system to the future paradigm.

So we're going to have two different regulatory approaches. I hope we don't call this two different quality system. One if more inferior that the other. We will have two different regulatory processes, the existing one and the one that fits better with the future paradigm.

And we should make products available to the public based on both processes. What we should work on collectively, because I think from what I'm hearing today and I heard before, we are in agreement, is how to move from the existing system to the future paradigm without penalizing industry or the public.

CHAIR BOEHLERT: Ken?

MEMBER MORRIS: Something that's bothering me a little is that, you know, what we've been talking about all along is that industry should essentially be telling FDA what it thinks it needs to do in order to justify its decisions in dosage form and process development manufacturing. Not dictating but saying here's what we think we should do -- which is sort of what we're saying in Part A.

And I don't have an answer to this. But what bothers me a little bit is that if that's what we're really saying, then in principle what you would expect is that the company would put together what it considers necessary for itself in terms of a development report and share that.

Now the question of what's minimum then really is almost a moot point because minimum would have been passed long before you got to that point. Because if you're going to do minimum, then you're using Moheb's other -- you're using your other eventuality where you're just following the old system.

So it seems like you've long passed -- that ship's sailed, I think.

MEMBER HUSSAIN: No, Ken, I think the point you're making is a good one. And I think the only -- I think the primary reason for asking this question is because this is the question that seems to come up again and again in our expert working group discussions.

And primarily I think I agree with Moheb in that at least in the U.S., with our peer review process, with our quality system, it's not an issue within the U.S. to manage this. I think we can easily manage this with the new way.

It's simply a question to sort of prepare ourselves for the future discussions in say Japan in November. Is, I think, Judy, if you would permit me, if John Berridge wants to come -- maybe I'll invite him to comment also on that -- my thoughts were that in a sense the uncertainty level seems to remain within the regulatory affairs, within the industry itself. The hesitation to share any information is there. So you still have that.

And what I'm hoping is we can find an opportunity to minimize that concern also at the same time I think get to the right decisions, ask the right questions, and get the right answers fairly quickly instead of going through an elaborate process.

There is a level of concern, hesitation out there, which is quite significant let me tell you, I'll share this. It's trying to minimize that.

DR. NASR: Before John comes in, I want to add one thing in response to G.K., who raised a very good point. Because what you heard from you that people out there are saying Ajaz, Helen, David, Janet, and so forth believe in this. How about the reviewers?

I think, I hope I made it clear today that the Office of New Drug Chemistry has made a commitment to change the way we do our work and reorganize in a way to facilitate the implementation of the new paradigm.

And this is not just me talking. I think we have senior leadership here of the Office in attendance and the Office is committed to do that. It is not just Helen and Ajaz.

MEMBER RAJU: And if you look at this presentation you made and the one you made at Arden House, the amount of changes you are making in the new drug chemistry seems to be really rapidly different from a year ago. I've never seen that kind of momentum in any place before. It's clear.

CHAIR BOEHLERT: John?

DR. BERRIDGE: Yes. So I don't want -- I don't think there is any point in my repeating the points that have been made. But I think there's one other thing to consider about the communication and the way we get the new paradigm across.

One of the things we discussed in the expert working group is to build on the model that was designed, and Joe will probably be very familiar with this, that was adopted by the Q7A Team, which was actually to construct an education process that could be rolled out around the world, that would use a common set of training materials that would be available to regulators and industry alike that would clearly articulate exactly what it was we wanted to achieve and the implications thereof.

I think that would actually strengthen the understanding and remove the degree of uncertainty and I'm almost bound to say fear that exists. And I think an element of the fear is driven by the unknown.

So the development of a training program, you mentioned particularly regulatory affairs colleagues who haven't been quite as intimately involved in this process as maybe their scientific counterparts, if we can get that adopted and pushed out, I think that would be also a very valuable process for removing some of the concerns that have been expressed this afternoon.

MEMBER HUSSAIN: I think that's an important point. And there are a number of aspects, if I may see the Committee's thoughts and recommendations on this.

Helen and I have sort of discussed this at length in the sense we have met with a number of companies, one on one basis. They have shared some of their ideas of how this report might be and how the case studies might develop and what the criteria should be and so forth.

I think meeting each company one at a time clearly is what we are going for, but we're not getting something in the public domain which would be an example, the case studies, and so forth.

The proposal might be to the Committee just to consider maybe we form a working group under this Committee to actually get to some of this tangible outcomes quickly because I think we need a framework to work on this.

So if the Committee would agree, I would propose that I think we might, following this meeting, start the dialogue and put a working group under this Committee to work on some of these aspects.

CHAIR BOEHLERT: Any comments on that proposal?

MEMBER SINGPURWALLA: It's a good idea as long as I don't have to be on it.

(Laughter.)

CHAIR BOEHLERT: Okay. Are we either ready --

MEMBER HUSSAIN: Okay. I think there are a number of activities going on in ONDC and OGD and we actually just talked about that. We have Office of Biotechnology Products also gearing up for a number of things. And if you saw the pharmaceutical technology report, you saw what Keith Beverly is doing.

But at this meeting, we didn't have time to bring him on board also. But what do you think, what advice, or what recommendations do you have for Moheb and Gary that might help move them further?

I think they're doing a tremendous job already. I think there is still aspects of communication, coordination, and so forth that will occur. But anything you can add would be a real help.

DR. FACKLER: Judy? For a number of companies, somebody mentioned just a minute ago the unknown. A delay in an approval has a series economic impact on a company. And submitting more information than we have been doing historically to an organization that confesses to being hopelessly understaffed seems like a prescription for delaying one's approval.

MEMBER HUSSAIN: Hopefully it is not more information. It is less data, more knowledge, and then more concise. Hopefully we can transition to that.

DR. FACKLER: Well, and that's what I think needs to be clarified to companies in general is that not just a reassurance that things will go smoother or faster but some -- certainly a concrete example would be a good thing but it's too ill defined right now, I think, for companies to risk changing something that they can measure right now.

You know you make a submission and you have a fairly good understanding for when you might get the first review back or the first approval. And it's the unknown that really is causing I think a lot of hesitation in companies.

MEMBER HUSSAIN: If I may, sort of building on that, I think the whole thing begs for some concrete examples, criteria, and so forth. That's what the next step logical is. And I think to get there a working group might be the best option to do that.

And maybe I'll follow up with Judy and try to assemble a group under this Committee that will report to this Committee.

CHAIR BOEHLERT: And Pat?

MEMBER DeLUCA: Yes, I got the impression that in the submissions that there was information that was lacking. And the reviewers had to, at times, try to tease out information or try to even decipher what the rationale was for doing something.

And I'm just wondering if that in moving from the existing system to the new paradigm that the filings should include from the companies the rationale, the summary, and then plans for improvement on the process that's going to take place?

So it's just not, you know, the process improvement should not be optional. It should be something that is expected even after approval.

(Laughter.)

MR. MIGLIACCIO: Judy?

CHAIR BOEHLERT: Gerry?

MR. MIGLIACCIO: In the ideal case that there are no undesirable sources of variability in the process, why would you change it in the ideal case?

MEMBER DeLUCA: Well, you wouldn't change it. I mean the only thing is is that you should have some idea is there a way to improve the process. But saying that that's going to work but at least you have some strategy that you can look into and investigate. And either prove or disprove it. If it is possible to improve the process, then there is some effort to improve it.

MR. MIGLIACCIO: An examination for example?

MEMBER DeLUCA: That's right. I mean it's not compulsory that you improve it. It's just that did you have a plan or some strategy for improving it?

MEMBER HUSSAIN: I think we probably will touch upon this tomorrow also. I think the key aspect is in terms of a decision to approve, I think in some ways you have to look at that as a decision of an acceptable risk assessment that allows the product to come out. Sometimes you have to have special decision-making criteria for a very essential drug and so forth.

But generally a decision to approve means you have met the safety and efficacy standard. And in many ways continuous improvement the way I see it is is an improvement to improve efficiency, improvement to bring new technologies, simply from a business case.

But at the same time, there is a category of changes which are necessary. The process is not capable of meeting those standards that we approve. Tremendous failure and so forth.

So when the process is not capable, there has to be a way to sort of improve that. And we do it through enforcement action today, concern degree and so forth. So there is a category change which the FDA will come back to ask you for the change.

So -- but the other type of changes are, I think, are continuous improvement, to a large extent efficiency improvements. With that, I think -- oh sorry. Go ahead.

MEMBER RAJU: There are two presentations. The Office of New Drugs' presentation was extremely impressive. One of the best I've seen. The whole science into the mission and the science principles were very powerful, knowledge gaining, bringing in pharmaceutical development.

I will echo, however, that probably process capability shouldn't be in there. It should instead be process stability because it's too early. Process capability comes later. It should be stable first.

But if you include process stability, it would fit in beautifully.

In terms of the overall piece, if you say special cause analysis before you go to statistics, that's a beautiful place to bring in the FMEA actually. That's the right tool for that.

So this is actually quite strong. I'd be curious to hear your good scientific principles sometime in an offline.

In terms of the Office of Generic Drugs, this is the first time that I've learned about the size of the submissions and how long it takes. It doesn't seem acceptable from a social point of view. I was really worried as a citizen.

I think there should be a synergy of leveraging the old innovator drug's knowledge back here. But then there's a whole other dimension of resources and prioritization that's beyond probably the scope of this Committee or at least me that is extremely important that there has to be something done about.

MEMBER HUSSAIN: G.K., just a comment on, I think it's a matter of semantics and vocabulary. I think process capability often we use it in the new drug side from a slightly different perspective in a sense. How we often -- I'm very familiar with how we set dissolution specifications. I use that as an example.

If you have say ten batches that you have used in the clinical setting, so you have ten clinical batches over the clinical drug year. What we often will do is, I think, the decision to set a specification and an acceptance criteria, mostly acceptance criteria would be to maybe fail a couple of batches. That's what we often refer to. But it's not truly a calculated process capability.

CHAIR BOEHLERT: Garnet, did you have a comment?

MEMBER PECK: Just what I'm thinking about is an overview without coming with specific recommendations or answers to Question 2 and 3.

I feel that you have given in the beginning of Question 2 a great preamble. You have a number of suggestions here about what might be done within a particular organization to demonstrate that they understand the process, that they probably understand the product, the system required to put together the product, which then would allow the Agency to have this flexibility in terms of the regulatory affairs.

I couldn't come up with something better than minimal or optimal. I think there's got to be another way of expressing that. I don't think that's the right way to do it. But there's got to be some demarcation.

But if we can have some feeling for PAT guidance, ICH newer thoughts, and we start to apply these, it seems to me that we would have a total confidence in all avenues that we were proceeding in be it new drug or be it generic.

And I think the generic situation is a tough one because of the number of filings. That is -- this number, I hadn't seen this year's number and it's getting pretty large.

But you are attempting to present, if you will, the possibilities of regulatory flexibility with better understanding of the process and the product.

CHAIR BOEHLERT: Anyone else?

(No response.)

CHAIR BOEHLERT: Ajaz, are you satisfied with what you've heard?

MEMBER HUSSAIN: No, I think this was a very valuable discussion.

CHAIR BOEHLERT: Okay.

MEMBER HUSSAIN: And I think I was just kicking myself for not bringing a piece of paper and pen to take some notes but the transcript will have that.

But again, thank you very much for the discussions.

CHAIR BOEHLERT: Okay. Well, I'd like to thank everybody as well. And if that's it, then we will adjourn for this evening and reconvene tomorrow morning at 8:30.

(Whereupon, the above-entitled meeting was concluded at 5:10 p.m.)