Guidance for Industry 

PAT  A Framework for 

Innovative Pharmaceutical 

Development, Manufacturing, 

and Quality Assurance 

 
 
 
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 

Food and Drug Administration 

Center for Drug Evaluation and Research (CDER) 

Center for Veterinary Medicine (CVM) 

Office of Regulatory Affairs (ORA) 

 
Pharmaceutical CGMPs 
September 2004    
Guidance for Industry 

PAT  A Framework for 

Innovative Pharmaceutical 

Development, Manufacturing, 

and Quality Assurance 

 
 
Additional copies are available from: 

 
Office of Training and Communication 

Division of Drug Information, HFD-240 

Center for Drug Evaluation and Research 

Food and Drug Administration 

5600 Fishers Lane 

Rockville, MD 20857 

(Tel) 301-827-4573 

http://www.fda.gov/cder/guidance/index.htm 

and/or 

Communications Staff, HFV-12 

Center for Veterinary Medicine 

Food and Drug Administration 

7519 Standish Place, 

Rockville, MD 20855 

(Tel) 301-827-3800 

http://www.fda.gov/cvm/guidance/published.html 

 
 
 
 
U.S. Department of Health and Human Services 

Food and Drug Administration 

Center for Drug Evaluation and Research (CDER) 

Center for Veterinary Medicine (CVM) 

Office of Regulatory Affairs (ORA) 

September 2004 
Pharmaceutical CGMPs 
  Contains Nonbinding Recommendations  
 
TABLE OF CONTENTS 

 
I.  INTRODUCTION.................................................................................................................1
  
II.  GUIDANCE DEVELOPMENT PROCESS AND SCOPE ............................................... 2 

III.  BACKGROUND ................................................................................................................... 2 

IV.  PAT FRAMEWORK............................................................................................................ 4  

A.  Process Understanding ..................................................................................................................6 

B.  Principles and Tools.......................................................................................................................6 

1. PAT Tools ........................................................................................................................................7 

3. Risk-Based Approach.....................................................................................................................11 

4.  Integrated Systems Approach ........................................................................................................12 

5.  Real Time Release..........................................................................................................................12 

C.  Strategy for Implementation.......................................................................................................12 

V.  PAT REGULATORY APPROACH ................................................................................. 14 

BIBLIOGRAPHY....................................................................................................................... 16 

 
  Contains Nonbinding Recommendations  
1 
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.  
 
 
 
 
 
I.   INTRODUCTION 
 
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.  
 
 
                                                 
1 This guidance was prepared by the Office of Pharmaceutical Science in the Center for Drug Evaluation and 
Research (CDER) under the direction of Food and Drug Administration's Process Analytical Technology (PAT) 
Steering Committee with membership from CDER, Center for Veterinary Medicine (CVM), and Office of 
Regulatory Affairs (ORA).  
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II.  SCOPE 
 
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.    
 
 
III.  BACKGROUND 
 
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 
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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: 
 
x   The most up-to-date concepts of risk management and quality systems approaches  are 
incorporated into the manufacture of pharmaceuticals while maintaining product quality  
x   Manufacturers are encouraged to use the latest scientific advances in pharmaceutical 
manufacturing and technology 
x   The Agency's submission review and inspection programs operate in a coordinated and 
synergistic manner 
x   Regulations and manufacturing standards are applied consistently by the Agency and the 
manufacturer 
x   Management of the Agency's Risk-Based Approach encourages innovation in the 
pharmaceutical manufacturing sector  
x   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:  
 
x 	  Product quality and performance are ensured through the design of effective and efficient 
manufacturing processes 
x 	  Product and process specifications are based on a mechanistic understanding of how 
formulation and process factors affect product performance  
x 	  Continuous real time quality assurance  
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x	   Relevant regulatory policies and procedures are tailored to accommodate the most current 
level of scientific knowledge 
x	   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).2  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: 
  
x 	  The intended therapeutic objectives; patient population; route of administration; and 
pharmacological, toxicological, and pharmacokinetic characteristics of a drug  
x 	  The chemical, physical, and biopharmaceutic characteristics of a drug 
                                                 
2  For products regulated by the Center for Biologics Evaluation and Research  (CBER), manufacturers should 
contact CBER to discuss applicability of Process Analytical Technology.   
 
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  Contains Nonbinding Recommendations  
x   Design of a product and selection of product components and packaging based on drug 
attributes listed above 
x   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: 
 
x   What are the mechanisms of degradation, drug release, and absorption? 
x   What are the effects of product components on quality?  
x   What sources of variability are critical? 
x   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: 
 
x 	  Reducing production cycle times by using on-, in-, and/or at-line measurements and 
controls 
x 	  Preventing rejects, scrap, and re-processing 
x 	  Real time release 
x 	  Increasing automation to improve operator safety and reduce human errors  
x 	  Improving energy and material use and increasing capacity 
x 	  Facilitating continuous processing to improve efficiency and manage variability  
 	  For example, use of dedicated small-scale equipment (to eliminate certain scale-
up issues) 
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  Contains Nonbinding Recommendations  
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 Understanding 
 
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.  
 
B.  Principles and Tools 
 
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  
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  Contains Nonbinding Recommendations  
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: 
 
x   Multivariate tools for design, data acquisition and analysis  
x   Process analyzers 
x   Process control tools 
x   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  
 
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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. 
 
b.  Process Analyzers 
 
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 
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nondestructive measurements that contain information related to biological, physical, and 
chemical attributes of the materials being processed.  These measurements can be: 
 
x 	  at-line: Measurement where the sample is removed, isolated from, and analyzed 
in close proximity to the process stream.  
x 	  on-line: Measurement where the sample is diverted from the manufacturing 
process, and may be returned to the process stream.   
x 	  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. 
 
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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):  
 
x   Identify and measure critical material and process attributes relating to product 
quality 
x   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  
x   Design process controls that provide adjustments to ensure control of all critical 
attributes 
x   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 
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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 Validation3 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. 
 
2.  Risk-Based Approach  
 
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. 
                                                 
3 See guidance for industry and FDA staff,  General Principles of  Software Validation. 
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3.  Integrated Systems Approach 
 
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.  
 
4.  Real Time Release 
 
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.  
 
C.  Strategy for Implementation 
 
The Agency understands that to enable successful implementation of PAT, flexibility, 
coordination, and communication with manufacturers is critical.  The Agency believes that 
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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: 
 
x   A PAT team approach for CMC review and CGMP inspections 
x   Joint training and certification of PAT review, inspection and compliance staff 
x   Scientific and technical support for the PAT review, inspection and compliance staff 
x   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. 
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  Contains Nonbinding Recommendations  
130.300.4  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 Agencys 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:  
 
x   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.  
                                                 
4 FDA/ORA Compliance Policy Guide, Sec. 130.300, FDA Access to Results of Quality Assurance Program Audits 
and Inspections (CPG 7151.02). 
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x 	  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.  
x 	  A comparability protocol5 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)6 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. 
                                                 
5 FDA  guidance for industry, Comparability Protocols  Chemistry, Manufacturing, and Controls Information, 
issued February 2003.  Once finalized, it will represent the Agency's current thinking on this topic. 
  
6 FDA Field Management Directive 135. http://www.fda.gov/ora/inspect_ref/fmd/fmd135a.html. 
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  Contains Nonbinding Recommendations  
 
BIBLIOGRAPHY 
 
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.  PDA Journal of 

Pharmaceutical Science and Technology 54(3) Supplement TR33 

 
B.  Literature  
 
For additional information, refer to FDA's PAT Web page at http://www.fda.gov/cder/OPS/PAT.htm. 
 
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