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

Guidance for Industry1

 

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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Contains Nonbinding Recommendations

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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Contains Nonbinding Recommendations

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 

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Contains Nonbinding Recommendations

• 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).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: 

 

• 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 

 

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

• 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 scaleup 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 online 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 onor 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 timedefined 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 

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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: 

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. 

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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): 

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 

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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 multifactorial 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: 

• 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. 

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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 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. 

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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•

 

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 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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16

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.