PAT — A Framework for Innovative Pharmaceutical
Development, Manufacturing, and Quality Assurance
Guidance for Industry
PAT — A Framework for Innovative
Pharmaceutical Development, Manufacturing,
and Quality Assurance
This guidance represents the Food
and Drug Administration's (FDA's) current thinking on this topic. It does not
create or confer any rights for or on any person and does not operate to bind
FDA or the public. You can use an alternative approach if the approach
satisfies the requirements of the applicable statutes and regulations. If you
want to discuss an alternative approach, contact the FDA staff responsible for
implementing this guidance. If you cannot identify the appropriate FDA staff,
call the appropriate number listed on the title page of this guidance.
This guidance is intended to describe a regulatory framework
(Process Analytical Technology, PAT) that will encourage the voluntary
development and implementation of innovative pharmaceutical development,
manufacturing, and quality assurance. Working with existing regulations, the
Agency has developed an innovative approach for helping the pharmaceutical
industry address anticipated technical and regulatory issues and questions.
This guidance is written for a broad industry audience in
different organizational units and scientific disciplines. To a large extent,
the guidance discusses principles with the goal of highlighting opportunities
and developing regulatory processes that encourage innovation. In this regard,
it is not a typical Agency guidance.
FDA's guidance documents, including this guidance, do not
establish legally enforceable responsibilities. Instead, guidances describe
the Agency's current thinking on a topic and should be viewed only as
recommendations, unless specific regulatory or statutory requirements are
cited. The use of the word should in Agency guidances means that
something is suggested or recommended, but not required.
The scientific, risk-based
framework outlined in this guidance, Process Analytical Technology or
PAT, is intended to support innovation and efficiency in pharmaceutical
development, manufacturing, and quality assurance. The framework is founded on
process understanding to facilitate innovation and risk-based regulatory
decisions by industry and the Agency. The framework has two components: (1) a
set of scientific principles and tools supporting innovation and (2) a strategy
for regulatory implementation that will accommodate innovation. The regulatory
implementation strategy includes creation of a PAT Team approach to chemistry
manufacturing and control (CMC) review and current good manufacturing practice
(CGMP) inspections as well as joint training and certification of PAT review
and inspection staff. Together with the recommendations in this guidance, our
new strategy is intended to alleviate concern among manufacturers that
innovation in manufacturing and quality assurance will result in regulatory
impasse. The Agency is encouraging manufacturers
to use the PAT framework described here to develop and implement
effective and efficient innovative approaches in pharmaceutical development,
manufacturing and quality assurance.
This guidance addresses new and abbreviated new (human and
veterinary) drug application products and specified biologics regulated by CDER
and CVM as well as nonapplication drug products. Within this scope, the
guidance is applicable to all manufacturers of drug substances, drug products,
and specified biologics (including intermediate and drug product components)
over the life cycle of the products (references to 21 CFR part 211 are merely
examples of related regulation). Within the context of this guidance, the term
manufacturers includes human drug, veterinary drug, and specified
biologic sponsors and applicants (21 CFR 99.3(f)).
We would like to emphasize that any decision on the part
of a manufacturer to work with the Agency to develop and implement PAT is a
voluntary one. In addition, developing and implementing an innovative PAT
system for a particular product does not mean that a similar system must be
developed and implemented for other products.
Conventional pharmaceutical manufacturing is generally
accomplished using batch processing with laboratory testing conducted on
collected samples to evaluate quality. This conventional approach has been
successful in providing quality pharmaceuticals to the public. However, today
significant opportunities exist for improving pharmaceutical development,
manufacturing, and quality assurance through innovation in product and process
development, process analysis, and process control.
Unfortunately, the pharmaceutical industry generally has
been hesitant to introduce innovative systems into the manufacturing sector for
a number of reasons. One reason often cited is regulatory uncertainty, which
may result from the perception that our existing regulatory system is
rigid and unfavorable to the introduction of innovative systems. For example, many
manufacturing procedures are treated as being frozen and many process changes
are managed through regulatory submissions. In addition, other scientific and
technical issues have been raised as possible reasons for this hesitancy.
Nonetheless, industry's hesitancy to broadly embrace innovation in
pharmaceutical manufacturing is undesirable from a public health perspective.
Efficient pharmaceutical manufacturing is a critical part of an effective U.S.
health care system. The health of our citizens (and animals in their care)
depends on the availability of safe, effective, and affordable medicines.
Pharmaceuticals continue to have an increasingly prominent
role in health care. Therefore pharmaceutical manufacturing will need to employ
innovation, cutting edge scientific and engineering knowledge, along with the
best principles of quality management to respond to the challenges of new
discoveries (e.g., novel drugs and nanotechnology) and ways of doing business
(e.g., individualized therapy, genetically tailored treatment). Regulatory
policies must also rise to the challenge.
In August 2002, recognizing the need to eliminate the
hesitancy to innovate, the Food and Drug Administration (FDA) launched a new
initiative entitled “Pharmaceutical CGMPs for the 21st Century: A
Risk-Based Approach.” This
initiative has several important goals, which ultimately will help improve the
American public's access to quality health care services. The goals are intended
to ensure that:
·
The most up-to-date concepts of risk management and quality
systems approaches are incorporated into the manufacture of
pharmaceuticals while maintaining product quality
·
Manufacturers are encouraged to use the latest scientific advances
in pharmaceutical manufacturing and technology
·
The Agency's submission review and inspection programs operate in
a coordinated and synergistic manner
·
Regulations and manufacturing standards are applied consistently
by the Agency and the manufacturer
·
Management of the Agency's Risk-Based Approach encourages
innovation in the pharmaceutical manufacturing sector
·
Agency resources are used effectively and efficiently to address
the most significant health risks
Pharmaceutical manufacturing continues to evolve with
increased emphasis on science and engineering principles. Effective use of the
most current pharmaceutical science and engineering principles and knowledge —
throughout the life cycle of a product — can improve the efficiencies of both
the manufacturing and regulatory processes. This FDA initiative is designed to
do just that by using an integrated systems approach to regulating
pharmaceutical product quality. The approach is based on science and
engineering principles for assessing and mitigating risks related to poor
product and process quality. In this regard, the desired state of
pharmaceutical manufacturing and regulation may be characterized as follows:
·
Product quality and performance are ensured through the design of
effective and efficient manufacturing processes
·
Product and process specifications are based on a mechanistic
understanding of how formulation and process factors affect product performance
·
Continuous real time quality assurance
·
Relevant regulatory policies and procedures are tailored to
accommodate the most current level of scientific knowledge
·
Risk-based regulatory approaches recognize
– the level of scientific understanding of how formulation
and manufacturing process factors affect product quality and performance
– the capability of process control strategies to prevent or
mitigate the risk of producing a poor quality product
This guidance, which is consistent with the Agency's August
2002 initiative, is intended to facilitate progress to this desired state.
This guidance was developed through a collaborative effort
involving CDER, the Center for Veterinary Medicine (CVM), and the Office of
Regulatory Affairs (ORA).
Collaborative activities included public discussions, PAT team building
activities, joint training and certification, and research. An integral part
of this process was the extensive public discussions at the FDA Science Board,
the Advisory Committee for Pharmaceutical Science (ACPS), the PAT-Subcommittee
of ACPS, and several scientific workshops. Discussions covered a wide range of
topics including opportunities for improving pharmaceutical manufacturing,
existing barriers to innovation, possible approaches for removing both real and
perceived barriers, and many of the principles described in this guidance.
IV. PAT Framework
The Agency considers PAT to be a system for designing, analyzing, and controlling
manufacturing through timely measurements (i.e., during processing) of critical
quality and performance attributes of raw and in-process materials and
processes, with the goal of ensuring final product quality. It is important to
note that the term analytical in PAT is viewed broadly to
include chemical, physical, microbiological, mathematical, and risk analysis
conducted in an integrated manner. The goal of PAT is to enhance understanding
and control the manufacturing process, which is consistent with our current
drug quality system: quality cannot be tested into products; it should be
built-in or should be by design. Consequently, the tools and principles described in this
guidance should be used for gaining process understanding and can also be used
to meet the regulatory requirements for validating and controlling the
manufacturing process.
Quality is built into
pharmaceutical products through a comprehensive understanding of:
·
The intended therapeutic
objectives; patient population; route of administration; and pharmacological,
toxicological, and pharmacokinetic characteristics of a drug
·
The chemical, physical, and
biopharmaceutic characteristics of a drug
·
Design of a product and
selection of product components and packaging based on drug attributes listed
above
·
The design of manufacturing
processes using principles of engineering, material science, and quality
assurance to ensure acceptable and reproducible product quality and performance
throughout a product's shelf life
Using this approach of building
quality into products, this guidance highlights the necessity for process
understanding and opportunities for improving manufacturing efficiencies
through innovation and enhanced scientific communication between manufacturers
and the Agency. Increased emphasis on building quality into products
allows more focus to be placed on relevant multi-factorial
relationships among material, manufacturing process, environmental variables,
and their effects on quality. This enhanced focus provides a basis for
identifying and understanding relationships among various critical formulation
and process factors and for developing effective risk mitigation strategies
(e.g., product specifications, process controls, training). The data and
information to help understand these relationships can be leveraged through preformulation
programs, development and scale-up studies, as well as from improved analysis
of manufacturing data collected over the life of a product.
Effective innovation in development, manufacturing and
quality assurance would be expected to better answer questions such as the
following:
·
What are the mechanisms of degradation, drug release, and
absorption?
·
What are the effects of product components on quality?
·
What sources of variability are critical?
·
How does the process manage variability?
A desired goal of the PAT
framework is to design and develop well understood processes that will consistently
ensure a predefined quality at the end of the manufacturing process. Such
procedures would be consistent with the basic tenet of quality by design and
could reduce risks to quality and regulatory concerns while improving
efficiency. Gains in quality, safety and/or efficiency will vary depending on
the process and the product, and are likely to come from:
·
Reducing production cycle
times by using on-, in-, and/or at-line measurements and controls
·
Preventing rejects, scrap,
and re-processing
·
Real time release
·
Increasing automation to
improve operator safety and reduce human errors
·
Improving energy and material
use and increasing capacity
·
Facilitating continuous
processing to improve efficiency and manage variability
–
For example, use of dedicated
small-scale equipment (to eliminate certain scale-up issues)
This guidance
facilitates innovation in development, manufacturing and quality assurance by
focusing on process understanding. These concepts are applicable to all
manufacturing situations.
A process is generally
considered well understood when (1) all critical sources of variability are
identified and explained; (2) variability is managed by the process; and, (3)
product quality attributes can be accurately and reliably predicted over the
design space established for materials used, process parameters, manufacturing,
environmental, and other conditions. The ability to predict reflects a high
degree of process understanding. Although retrospective process capability data
are indicative of a state of control, these alone may be insufficient to gauge
or communicate process understanding.
A focus on process understanding can reduce the burden for
validating systems by providing more
options for justifying and qualifying systems intended to monitor and control
biological, physical, and/or chemical attributes of materials and processes.
In the absence of process knowledge, when proposing a new process analyzer, the
test-to-test comparison between an on-line process analyzer and a
conventional test method on collected samples may be the only available validation
option. In some cases, this approach may be too burdensome and may discourage
the use of some new technologies.
Transfer of laboratory
methods to on-, in-, or at-line methods may not necessarily be PAT. Existing
regulatory guidance documents and compendial approaches on analytical method
validation should be considered.
Structured product and process development on a small scale, using
experimental design and on- or in-line process analyzers to collect data in
real time, can provide increased insight and understanding for process development,
optimization, scale-up, technology transfer, and control. Process
understanding then continues in the production phase when other variables
(e.g., environmental and supplier changes) may possibly be encountered.
Therefore, continuous learning over the life cycle of a product is important.
Pharmaceutical
manufacturing processes often consist of a series of unit operations, each
intended to modulate certain properties of the materials being processed. To
ensure acceptable and reproducible modulation, consideration should be given to
the quality attributes of incoming materials and their process-ability for each
unit operation. During the last 3 decades, significant progress has been made
in developing analytical methods for chemical attributes (e.g., identity and
purity). However, certain physical and mechanical attributes of pharmaceutical
ingredients are not necessarily well understood. Consequently, the inherent,
undetected variability of raw materials may be manifested in the final
product. Establishing effective processes for managing physical attributes of
raw and in-process materials requires a fundamental understanding of attributes
that are critical to product quality. Such attributes (e.g., particle size and
shape variations within a sample) of raw and in-process materials may pose a
significant challenge because of their complexities and difficulties related to
collecting representative samples. For example, it is well known that powder
sampling procedures can be erroneous.
Formulation design
strategies exist that provide robust processes that are not adversely affected
by minor differences in physical attributes of raw materials. Because these
strategies are not generalized and are often based on the experience of a
particular formulator, the quality of these formulations can be evaluated only by
testing samples of in-process materials and end products. Currently, these
tests are performed off line after preparing collected samples for analysis.
Different tests, each for a particular quality attribute, are needed because
such tests only address one attribute of the active ingredient following sample
preparation (e.g., chemical separation to isolate it from other components).
During sample preparation, other valuable information pertaining to the
formulation matrix is often lost. Several new technologies are now available
that can acquire information on multiple attributes with minimal or no sample
preparation. These technologies provide an opportunity to assess multiple
attributes, often nondestructively.
Currently, most
pharmaceutical processes are based on time-defined end points (e.g.,
blend for 10 minutes). However, in some cases, these time-defined end points
do not consider the effects of physical differences in raw materials.
Processing difficulties can arise that result in the failure of a product to
meet specifications, even if certain raw materials conform to established
pharmacopeial specifications, which
generally address only chemical identity and purity.
Appropriate use of PAT
tools and principles, described below can provide relevant information relating
to physical, chemical, and biological attributes. The process understanding
gained from this information will enable process control and optimization, address
the limitation of the time-defined end points discussed above, and improve
efficiency.
1. PAT Tools
There are many tools available that enable process
understanding for scientific, risk-managed pharmaceutical development,
manufacture, and quality assurance. These
tools, when used within a system, can provide effective and efficient means for
acquiring information to facilitate process understanding, continuous
improvement, and development of risk-mitigation strategies. In the PAT
framework, these tools can be categorized according to the following:
·
Multivariate tools for design, data acquisition and analysis
·
Process analyzers
·
Process control tools
·
Continuous improvement and knowledge management tools
An appropriate combination of some, or all, of
these tools may be applicable to a single-unit operation, or to an entire
manufacturing process and its quality assurance.
a. Multivariate Tools for Design, Data
Acquisition and Analysis
From a physical, chemical, or
biological perspective, pharmaceutical products and processes are complex
multi-factorial systems. There are many development strategies that can be used
to identify optimal formulations and processes. The knowledge acquired in these
development programs is the foundation for product and process design.
This knowledge base can help to
support and justify flexible regulatory paths for innovation in manufacturing
and postapproval changes. A knowledge base can be of most benefit when it
consists of scientific understanding of the relevant multi-factorial
relationships (e.g., between formulation, process, and quality attributes), as
well as a means to evaluate the applicability of this knowledge in different
scenarios (i.e., generalization). This benefit can be achieved through the use
of multivariate mathematical approaches, such as statistical design of
experiments, response surface methodologies, process simulation, and pattern
recognition tools, in conjunction with knowledge management
systems. The applicability and reliability of knowledge in the form of
mathematical relationships and models can be assessed by statistical evaluation
of model predictions.
Methodological experiments based
on statistical principles of orthogonality, reference distribution, and
randomization, provide effective means for identifying and studying the effect
and interaction of product and process variables. Traditional one-factor-at-a-time
experiments do not address interactions among product and process variables.
Experiments conducted during
product and process development can serve as building blocks of knowledge that grow to accommodate a higher degree of
complexity throughout the life of a product. Information from such structured
experiments supports development of a knowledge system for a particular product
and its processes. This information, along with information from other
development projects, can then become part of an overall institutional
knowledge base. As this institutional knowledge base grows in coverage (range
of variables and scenarios) and data density, it can be mined to determine
useful patterns for future development projects. These experimental databases
can also support the development of process simulation models, which can
contribute to continuous learning and help to reduce overall development time.
When used appropriately, these
tools enable the identification and evaluation of product and process variables
that may be critical to product quality and performance. The tools may also
identify potential failure modes and mechanisms and quantify their effects on
product quality.
Process
analysis has advanced significantly during the past several decades, due to an
increasing appreciation for the value of collecting process data. Industrial drivers of productivity, quality, and
environmental impact have supported major advancements in this area. Available tools have
evolved from those that predominantly take univariate process measurements,
such as pH, temperature, and pressure, to those that measure biological,
chemical, and physical attributes. Indeed some process analyzers provide
nondestructive measurements that contain information related to biological,
physical, and chemical attributes of the materials being processed. These
measurements can be:
·
at-line: Measurement where the sample is removed, isolated from,
and analyzed in close proximity to the process stream.
·
on-line: Measurement where the sample is diverted from the
manufacturing process, and may be returned to the process stream.
·
in-line: Measurement where the sample is not removed from the
process stream and can be invasive or noninvasive
Process analyzers typically
generate large volumes of data. Certain data are likely to be relevant for
routine quality assurance and regulatory decisions. In a PAT
environment, batch records should include scientific and procedural information
indicative of high process quality and product conformance. For example, batch
records could include a series of charts depicting acceptance ranges,
confidence intervals, and distribution plots (inter- and intrabatch) showing
measurement results. Ease of secure access to these data is important for real
time manufacturing control and quality assurance. Installed information
technology systems should accommodate such functions.
Measurements collected
from these process analyzers need not be absolute values of the attribute of
interest. The ability to measure relative differences in materials before
(e.g., within a lot, lot-to-lot, different suppliers) and during processing
will provide useful information for process control. A flexible process may be
designed to manage variability of the materials being processed. Such an
approach can be established and justified when differences in quality
attributes and other process information are used to control (e.g.,
feed-forward and/or feed-back) the process.
Advances in process analyzers make real time control and quality assurance during manufacturing feasible.
However, multivariate methodologies are often necessary to extract
critical process knowledge for real time control and quality assurance.
Comprehensive
statistical and risk analyses of the process are generally necessary to assess
the reliability of predictive mathematical relationships. Based on the
estimated risk, a simple correlation function may need further support or
justification, such as a mechanistic explanation of causal links among the
process, material measurements, and target quality specifications. For
certain applications, sensor-based measurements can provide a useful process
signature that may be related to the underlying process steps or
transformations. Based on the level of process understanding, these signatures
may also be useful for process monitoring, control, and end point determination
when these patterns or signatures relate to product and process quality.
Design and construction of the process equipment, the
analyzer, and their interfaces are critical to ensure that collected data are
relevant and representative of process and product attributes. Robust design,
reliability, and ease of operation are important considerations.
Installation of process analyzers
on existing process equipment in production should be done after risk analysis
to ensure this installation does not adversely affect process or product
quality.
A review of current standard practices (e.g., ASTM
International) for process analyzers can provide useful information and
facilitate discussions with the Agency. A few examples of such standards are
listed in the bibliography section. Additionally, standards forthcoming from
the ASTM Technical Committee E55 may provide complimentary information for
implementing the PAT Framework. We recommend that manufacturers developing a PAT
process consider a scientific, risk-based approach relevant to the intended use
of an analyzer for a specific process and its utility for understanding and
controlling the process.
c. Process Control Tools
It is important to emphasize that a strong link between
product design and process development is essential to ensure effective control
of all critical quality attributes. Process
monitoring and control strategies are intended to monitor the state of a
process and actively manipulate it to maintain a desired state. Strategies
should accommodate the attributes of input materials, the ability and
reliability of process analyzers to measure critical attributes, and the
achievement of process end points to ensure consistent quality of the output
materials and the final product.
Design and optimization of
drug formulations and manufacturing processes within the PAT framework can
include the following steps (the sequence of steps can vary):
·
Identify and measure critical material and process attributes
relating to product quality
·
Design a process measurement system to allow real time or near real
time (e.g., on-, in-, or at-line) monitoring of all critical attributes
·
Design process controls that provide adjustments to ensure
control of all critical attributes
·
Develop mathematical relationships between product quality
attributes and measurements of critical material and process attributes
Within the PAT framework, a process end point is not a
fixed time; rather it is the achievement of the desired material attribute.
This, however, does not mean that process time is not considered. A range of
acceptable process times (process window) is likely to be achieved during the
manufacturing phase and should be evaluated, and considerations for addressing
significant deviations from acceptable process times should be developed.
Where PAT spans the entire manufacturing process, the fraction of in-process materials and final
product evaluated during production could be substantially greater than what is
currently achieved using laboratory testing. Thus, an opportunity to use more
rigorous statistical principles for a quality decision is provided. Rigorous
statistical principles should be used for defining acceptance criteria for end
point attributes that consider measurement and sampling strategies.
Multivariate Statistical Process Control can be feasible and valuable to
realizing the full benefit of real time measurements. Quality decisions should
be based on process understanding and the prediction and control of relevant
process/product attributes. This is one way to be consistent with relevant
CGMP requirements, as such control procedures that validate the performance of
the manufacturing process (21 CFR 211.110(a)).
Systems that promote
greater product and process understanding can provide a high assurance of
quality on every batch and provide alternative, effective mechanisms to demonstrate
validation (per 21 CFR 211.100(a), i.e., production and process controls are
designed to ensure quality). In a PAT framework, validation can be demonstrated
through continuous quality assurance where a process is continually monitored,
evaluated, and adjusted using validated in-process measurements, tests,
controls, and process end points.
Risk-based approaches are suggested for validating PAT software systems. The recommendations
provided by other FDA guidances, such as General Principles of Software
Validation
should be considered. Other useful information can be obtained from consensus
standards, such as ASTM.
d. Continuous Improvement and Knowledge
Management
Continuous learning through data collection and
analysis over the life cycle of a product is important. These data can
contribute to justifying proposals for postapproval changes. Approaches and
information technology systems that support knowledge acquisition from such
databases are valuable for the manufacturers and can also facilitate scientific
communication with the Agency.
Opportunities
need to be identified to improve the usefulness of available relevant product
and process knowledge during regulatory decision making. A knowledge base can
be of most benefit when it consists of scientific understanding of the relevant
multi-factorial relationships (e.g., between formulation, process, and quality
attributes) as well as a means to evaluate the applicability of this knowledge
in different scenarios (i.e., generalization). Today's information technology infrastructure makes the development and
maintenance of this knowledge base practical.
Within an established
quality system and for a particular manufacturing process, one would expect an
inverse relationship between the level of process understanding and the risk of
producing a poor quality product. For processes that are well understood,
opportunities exist to develop less restrictive regulatory approaches to manage
change (e.g., no need for a regulatory submission). Thus, a focus on process
understanding can facilitate risk-based regulatory decisions and innovation.
Note that risk analysis and management is broader than what is discussed
within the PAT framework and may form a system of its own.
The fast pace of innovation
in today's information age necessitates integrated systems thinking for
evaluating and timely application of efficient tools and systems that satisfy
the needs of patients and the industry. Many of the advances that have
occurred, and are anticipated to occur, are bringing the development,
manufacturing, quality assurance, and information/knowledge management
functions so closely together that these four areas should be coordinated in an
integrated manner. Therefore, upper
management support for these initiatives is critical for successful
implementation.
The Agency recognizes the importance of having an
integrated systems approach to the regulation of PAT. Therefore, the Agency
developed a new regulatory strategy that includes a PAT team approach to joint
training, certification, CMC review, and CGMP inspections.
Real time release is
the ability to evaluate and ensure the acceptable quality of in-process and/or
final product based on process data. Typically, the PAT component of real
time release includes a valid combination of assessed material attributes
and process controls. Material attributes can be assessed using direct and/or
indirect process analytical methods. The combined process measurements and other
test data gathered during the manufacturing process can serve as the basis for real
time release of the final product and would demonstrate that each batch
conforms to established regulatory quality attributes. We consider real time
release to be comparable to alternative analytical procedures for
final product release.
Real time release as defined in this guidance builds on parametric
release for heat terminally sterilized drug products, a practice in the United
States since 1985. In real time release, material attributes as well as
process parameters are measured and controlled.
The Agency's approval should be obtained prior to
implementing real time release for products that are the subject of market
applications or licenses. Process understanding, control strategies, plus on-,
in-, or at-line measurement of critical attributes that relate to product
quality provides a scientific risk-based approach to justify how real time
quality assurance is at least equivalent to, or better than, laboratory-based
testing on collected samples. Real time release as defined in this guidance
meets the requirements of testing and release for distribution (21 CFR
211.165).
With real time quality assurance, the desired quality attributes are ensured through continuous assessment
during manufacture. Data from production batches can serve to validate
the process and reflect the total system
design concept, essentially supporting validation with each manufacturing batch.
The Agency understands that to
enable successful implementation of PAT, flexibility, coordination, and
communication with manufacturers is critical. The Agency believes that current
regulations are sufficiently broad to accommodate these strategies.
Regulations can effectively support innovation when clear, effective, and
meaningful communication exists between the Agency and industry, for example,
in the form of meetings or informal communications.
The first component of the PAT
framework described above addresses many of the uncertainties with respect to
innovation and outlines broad principles for addressing anticipated scientific
and technical issues. This framework should assist a manufacturer in proposing
and adopting innovative manufacturing and quality assurance. The Agency
encourages such proposals and has developed a regulatory strategy to consider
such proposals. The Agency's regulatory strategy includes the following:
·
A PAT team approach for CMC review and CGMP inspections
·
Joint training and certification of PAT review, inspection and
compliance staff
·
Scientific and technical support for the PAT review, inspection
and compliance staff
·
The recommendations provided in this guidance
Ideally, PAT principles and tools should be introduced
during the development phase. The advantage of using these principles and tools
during development is to create opportunities to improve the mechanistic basis
for establishing regulatory specifications. Manufacturers are encouraged to use the PAT framework to develop
and discuss approaches for establishing mechanistic-based regulatory
specifications for their products. The recommendations provided in this
guidance are intended to alleviate concerns with approval or inspection when
adopting the PAT framework.
In the course of implementing the PAT
framework, manufacturers may want to evaluate the suitability of a PAT tool on
experimental and/or production equipment and processes. For example, when
evaluating experimental on- or in-line process analyzers during production, it
is recommended that risk analysis of the impact on product quality be conducted
before installation. This can be accomplished within the facility's quality
system without prior notification to the Agency. Data collected using an
experimental tool should be considered research data. If research is conducted
in a production facility, it should be under the facility's own quality
system.
When using new measurement tools,
such as on- or in-line process analyzers, certain data trends, intrinsic to a currently
acceptable process, may be observed. Manufacturers should scientifically
evaluate these data to determine how or if such trends affect quality and
implementation of PAT tools. FDA does not
intend to inspect research data collected on an existing product for the
purpose of evaluating the suitability of an experimental process analyzer or
other PAT
tool. FDA's routine inspection of a firm's manufacturing process that
incorporates a PAT tool for research purposes will be based on current
regulatory standards (e.g., test results from currently approved or acceptable
regulatory methods). Any FDA decision to inspect research data would be based
on exceptional situations similar to those outlined in Compliance Policy Guide Sec. 130.300. Those data used to support validation or
regulatory submissions will be subject to inspection in the usual manner.
V. PAT
REGULATORY Approach
One goal of this guidance is
to tailor the Agency's usual regulatory scrutiny to meet the needs of PAT-based
innovations that (1) improve the scientific basis for establishing regulatory
specifications, (2) promote continuous improvement, and (3) improve
manufacturing while maintaining or improving the current level of product
quality. To be able to do this, manufacturers should communicate relevant
scientific knowledge to the Agency and resolve related technical issues in a
timely manner. Our goal is to facilitate a consistent scientific regulatory
assessment involving multiple Agency offices with varied responsibilities.
This guidance provides a broad perspective on our proposed PAT
regulatory approach. Close communication between the manufacturer and the Agency’s PAT review and inspection staff will
be a key component in this approach. We anticipate that communication between
manufacturers and the Agency may continue over the life cycle of a product and
that communication will be in the form of meetings, telephone conferences, and
written correspondence.
We have posted much of the information you will need on our
PAT Web page located at
http://www.fda.gov/cder/OPS/PAT.htm. Please
refer to the Web page to keep abreast of important information. We recommend
general correspondence related to PAT be directed to the FDA PAT Team.
Manufacturers can contact the PAT Team regarding any PAT questions at:
PAT@cder.fda.gov. Address any written
correspondence to the address provided on the PAT Web page. All written
correspondence should be identified clearly as PROCESS ANALYTICAL TECHNOLOGY
or PAT.
All marketing applications,
amendments, or supplements to an application should be submitted to the
appropriate CDER or CVM division in the usual manner. When consulting with the
Agency, manufacturers may want to discuss not only specific PAT plans, but also
thoughts on a possible regulatory path. Information generated from research on
an existing process, along with other process knowledge, can be used to
formulate and communicate implementation plans to Agency staff.
In general, PAT implementation
plans should be risk based. We are proposing the following possible
implementation plans, where appropriate:
·
PAT can be implemented under the facility's own quality system.
CGMP inspections by the PAT Team or PAT certified Investigator can precede or
follow PAT implementation.
·
A supplement (CBE, CBE-30 or PAS) can be submitted to the Agency
prior to implementation, and, if necessary, an inspection can be performed by a
PAT Team or PAT certified Investigator before implementation.
·
A comparability protocol can
be submitted to the Agency outlining PAT research, validation and
implementation strategies, and time lines. Following approval of this comparability
protocol by the Agency, one or a combination of the above regulatory
pathways can be adopted for implementation.
To
facilitate adoption or approval of a PAT process, manufacturers may request a preoperational
review of a PAT manufacturing facility and process by the PAT Team (see
ORA Field Management Directive No.135) by contacting the FDA
Process Analytical Technology Team at the address given above.
It should be noted that when
certain PAT implementation plans neither affect the current process nor require
a change in specifications, several options can be considered. Manufacturers
should evaluate and discuss with the Agency the most appropriate option for
their situation.
A. Useful Standards
1. ASTM Standards
E2363-04: Standard Terminology
related to PAT
D 3764 - 01: Standard Practice for
Validation of Process Stream Analyzer Systems.
D 4855 - 97: Standard Practice for
Comparing Test Methods.
D 6299 - 02: Standard Practice for
Applying Statistical Quality Assurance Techniques to Evaluate Analytical
Measurement System Performance.
E 456-02: Standard Terminology
Relating to Quality and Statistics
E1325-02: Standard Terminology
Relating to Design of Experiments.
2. Parenteral Drug
Association
PDA. May/June 2000. Technical
Report No. 33: Evaluation, Validation and Implementation of New
Microbiological Testing Methods. PAT — A Framework for Innovative Pharmaceutical
Development, Manufacturing, and Quality Assurance
For products regulated by the Center for Biologics
Evaluation and Research (CBER), manufacturers should contact CBER to discuss
applicability of Process Analytical Technology.