Draft PQLI Summary Update Report, Version V04

Date: 14 September 2007

1. Introduction

This report represents initial draft output from the inaugural Product Quality Lifecycle Implementation (PQLI) session held in Arlington, Virginia, on 5-6th June 2007 during the ISPE conference. PQLI is a global industry-led three to five year initiative aimed at facilitating the implementation of ICH Q8, Q9, and ultimately Q10 guidance.

The report represents work in progress and is intended to form the basis of further industry and regulatory comment and discussion. Good progress has been made, but there remain many open questions and areas for further consideration.

Three topic areas, Design Space, Criticality, and Control Strategy were selected for specific focus and discussion, and feedback on these discussions is included in this report.

2. Overview of PQLI

2.1 Background

The Product Quality Implementation Lifecycle (PQLI) initiative was launched by ISPE to help industry identify global solutions to the challenges in implementing ICH guidance.

Through this initiative ISPE is spearheading the effort to help industry begin to define areas where they will be able to provide the technical framework for the implementation of key elements of Quality by Design (QbD), and to turn ICH Q8, Q9, and the imminent Q10 (Pharmaceutical Quality Systems), into a cross-functional and practical reality. The following outputs and work products are envisioned:

• An e-community for discussion (short term) 
• “White Papers” and similar publications (short term) 
• Baseline Guides or Good Practice Guides (long term) 
• An Encyclopedia of QbD (long term)

As stated in ICH Q8, the aim of pharmaceutical development studies is to design a manufacturing process that will consistently perform and consistently deliver a product of the intended quality. The information and knowledge gained from pharmaceutical development studies and manufacturing experience provide scientific understanding to support the establishment of the design space, manufacturing controls, and specifications.

Prior scientific and technical knowledge along with information from pharmaceutical development studies can be a basis for quality risk management. Appropriate use of quality risk management principles can be helpful in prioritizing the additional pharmaceutical development studies to collect such knowledge and to promote continuous improvement related to process efficiencies. Being able to clearly articulate process understanding and associated process controls can create a basis for flexible regulatory approaches.

Pharmaceutical manufacturing seeks to employ innovation, cutting edge scientific and engineering knowledge, and the best principles of quality management to achieve the following objectives:

• Product quality and performance achieved and assured by design of effective and efficient manufacturing processes. 
• Product specifications based on mechanistic understanding of how formulation and process factors impact product performance. 
• An ability to affect continuous improvement and continuous "real time" assurance of quality through out the entire lifecycle of a product.

2.3 The PQLI Vision

The ultimate vision for PQLI is to deliver to the industry a comprehensive and practical knowledge base of deliverables covering the application of QbD.

This report is a first step in realizing that vision.

The initiative embraces quality, science and engineering, and drug substance, drug product, and small and large molecules. It is intended that the output will be applicable and useful in the US, EU, Japan, and other regions and countries.

The main objective is to provide practical information to industry, while also providing the background that could be of value to regulators.

PQLI is neither in place of, nor in competition with, the ICH process and its goals. ISPE, as a global organization, provides a neutral environment where common technical issues can be discussed and addressed.

ISPE is dedicated to being a change agent, promoting industry innovation by working collaboratively with regulators, industry, suppliers, and academia worldwide. It will involve international experts in the fields of pharmaceutical science, manufacturing, quality assurance, regulations, and engineering. PQLI Task Teams will consist primarily of industry experts, but will seek advisory comments from regulators during the initiative.

The PQLI process will assure transparency via conferences, breakout and workshop sessions, e-communities and publications.

2.3 Quality by Design

Quality by Design is a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding based on sound science and quality risk management. This approach entails the following aspects:

• Defining the desired product performance, or more generally the Pharmaceutical Target Product Profile 
• Identifying those product characteristics that are Critical Quality Attributes (CQAs) 
• Identifying process parameters and material attributes that can affect CQAs 
• Creating or using an established Knowledge Space to establish one or more Design Space(s) and an appropriate Control Strategy that reliably deliver a product that meets requirements 
• Incorporating the approach into the business plan, product development plan, and assuring and enabling it through the Quality System to facilitate continual improvement throughout the product lifecycle

3. Selected Topic Areas

The intention of the Arlington conference was to provide an open forum to focus on topics of industry discussion or confusion that present hurdles to industry in reaching a common and pragmatic working understanding in these broad areas.

Three key topic areas were selected for discussion and investigation:

• Critical vs. Non-Critical 
• Design Space 
• Control Strategy (Traditional vs. Non-Traditional approach based on QbD concepts)

A separate Task Team addressed each of the topics.

The three topics are closely linked but the full inter-relationship between them still remains to be fully investigated and defined. This linkage between the topics in the context of this summary report is illustrated in Figure 1, which has been used as the basis for the PQLI discussions.

Figure 1. Linkage between Topic Areas

Each of these topics is addressed in separate sections below. This report gives an overview summary only, and does not cover in detail all the areas discussed. Further work is in progress by the Task Teams as they continue to refine and develop further detail. The topics will also be further discussed at various ISPE conferences internationally.

4. Critical vs. Non-Critical

The discussions established that criticality is best considered in the context of the Knowledge Space of existing information, composed of existing information (prior knowledge) and new scientific information (data generated by the sponsor about the product and process).

The assessment and designation of criticality should be primarily based on impact on the safety and efficacy of the drug product to the patient.

The concepts of criticality can be used to describe any feature or material attribute, property or characteristic of a drug substance, component, raw material, drug product or device and/or any process attribute, parameter, condition or factor in the manufacture of a drug product based on the Knowledge Space of prior knowledge.

The assessment and designation of knowledge and how it relates to criticality should be based on a risk assessment process taking the following criteria into account:

• Probability – the likelihood of a consequence. 
• Severity – the magnitude of the impact of a consequence. 
• Detectability – the level or ability at which a consequence can be measured. 
• Sensitivity – the attenuation of interactions between multivariate dimensions.

The use of the concept of criticality reflects the elements of a process and their inter-relationship rather than a simple definition. Any use of descriptive adjectives to define criticality necessarily requires context. Critical outcomes may be attributed to multiple variables operating in concert. Note that the existence of a defined Control Strategy or test does not make any element inherently less critical.

A material or process attribute or parameter that is designated as critical has a direct or indirect impact on patient safety, therapeutic efficacy, in vivo pharmacokinetic or pharmacodynamic performance, patient compliance and product manufacturability for which failure to control within demonstrable acceptance criteria renders the product unacceptable for release.

4.1 Attributes and Parameters

The following are preliminary definitions representing current discussions and work in progress.

An attribute is a quality or characteristic inherent in or ascribed to something. It may be measurable properties of a material, or measurable characteristics of the process to make the material.

Critical Quality Attributes (CQAs) are physical, chemical, biological or microbiological properties or characteristics that need to be controlled (directly or indirectly) to ensure product quality. Examples in specific cases may include dissolution, potency, homogeneity, or purity. Even if a direct scientific link has not been conclusively established between the attribute and patient safety or product efficacy, but given there is common pharmaceutical knowledge that there may be a linkage then the attribute should be considered a Critical Quality Attribute.

Manufacturing or Non-Critical Attributes are those that do not directly affect product safety or efficacy from the perspective of the patient, but may affect, for example the commercial availability, affordability, environmental, or operator safety aspects of the process, or those associated with the delivery device or packaging.

A parameter is a measurable factor, such as temperature or pressure that contributes to the definition of a system. The process parameters determine the behavior of the system, and are frequently subject to variation in an experiment.

Critical Process Parameters are process parameters whose variability impact a quality attribute and therefore need to be controlled to ensure the process produces the desired quality. A Critical Process Parameter remains critical even if it is controlled. Critical Process Parameters, therefore, are those that have been demonstrated to have an effect on the Critical Quality Attributes of the drug substance or drug product.

Manufacturing or Non-Critical Process Parameters are parameters that have been demonstrated not to have an impact on the Critical Quality Attributes of the drug substance or drug product. These may have an impact on Manufacturing Attributes.

The terms Critical Quality Attribute and Critical Process Parameter are widely used and the consistent use of these are therefore strongly recommended. The use of the other additional terms introduced in this section is optional, and at the discretion of the regulated company or sponsor. It is recommended, however, that a consistent set of understandable terms be selected, such that the terminology used:

• Is well integrated into supporting knowledge systems, such as quality, regulatory, and management 
• Has defined applicability within development and manufacturing business units, and consistent with the day-to-day operations 
• Supports a science-based and risk-based approach to design and control, facilitating the adoption of a Quality-by-Design model 
• Is clearly explained and consistently applied in regulatory submissions

4.2 Lifecycle management

To assure alignment with the PQLI vision all aspects of the Knowledge Space should be used to assure product quality throughout the entire product lifecycle. This is accomplished in early development, and may include the use of a Parameter Attribute Matrix (PAM) along with Fishbone Analysis, and other tools if appropriate, to identify knowledge gaps.

As development progresses more detailed and rigorous risk assessment methods, such as Failure Mode and Effects Analysis (FMEA), Risk ranking matrices or Risk Prioritization matrices, may be applied to assist in the assignment of Criticality and to focus development efforts in refining the Knowledge Space. This in turn will assure a well-defined Design Space, which is aligned with current product and process understanding.

Studies should be focused on areas where scientific knowledge and judgment indicate a likely effect on product safety and efficacy. The level and rigor of development evaluation should vary depending upon the level of risk associated with a particular factor.

Changes in designation of an element (attribute or parameter) from critical to non-critical or vice-versa should be based on appropriate quality risk management methods, including risk assessments, and where appropriate demonstrated and documented by data. The approach and logic employed in the designation of criticality should be transparent and based on the Knowledge Space.

The knowledge of Criticality of attributes of the raw materials, in-process materials, drug substances, drug products, and process parameters should not be deemed equally important. From the perspective of patient safety, the CQAs of finished products are the most significant. Other aspects, such as the attributes of raw and in-process materials and process parameters, are the means to deliver these finished product CQAs.

5. Design Space

Design Space is defined in ICH Q8 as the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality. Working within the design space is not considered as a change. Movement out of the design space is considered to be a change and would normally initiate a regulatory post approval change process. Design space is proposed by the applicant and is subject to regulatory assessment and approval.

In statistical terminology, the Design Space is the intersection of Quality Attributes and Process Parameters that defines a response surface – a topographical map of the production process and the resulting product quality. Design Space is based on the Knowledge Space.

The development and refinement of the Design Space begins at product conceptualization (e.g. at definition of the Pharmaceutical Target Product Profile) and continues to evolve through the lifecycle of the product.

CQAs should drive the focus of the risk assessment and hence related experimentation, but process performance Manufacturing Attributes can often be studied in parallel.

5.1 Defining a Design Space

A Design Space is determined through an iterative process. The expected Critical Quality Attributes (CQAs) are defined and continually refined, using the established scientific Knowledge Space. Risk assessment tools are used to determine an experimental program that defines and sets the baseline for further enhancement and refinement of CQAs.

One of the first objectives in creation of a design space is to develop sufficient process understanding to describe the functional relationships between Process Parameters and Critical Quality Attributes. The functional relationships between Process Parameters and CQAs are best described with a predictive model based upon sound scientific principles, simulations, or experimentation.

In order to establish these functional relationships, the risk that a given Process Parameter will affect a specific CQA should be assessed. The risk can be assessed based upon prior knowledge that established a dependency between the CQA and one or more Process Parameters. If prior knowledge can establish a dependency, it is likely that experimentation to understand that relationship will lead to mitigation, reduction, or acceptance.

Multivariate experimental design (Design of Experiment (DOE)) is conducted, leading to a multivariate model and process understanding of all variables that impact Critical Quality Attributes, based on physical, chemical, microbiological, and engineering knowledge. The DOE ranges should be developed with formulation experts, analytical chemists, manufacturing, and engineering input, and should be based on reasonable operating ranges.

Should a distinct and non-interdependent parameter be identified a univariate analysis based on the established Knowledge Space is also possible

The process may include an evaluation of scale and equipment. The use of Scale-Up and Post Approval Changes (SUPAC) terminology will also allow clarity and provides a common lexicon for the equipment throughout the lifecycle of the product.

Laboratory or pilot scale studies may be conducted to evaluate feasibility and provide process understanding. If scale factors are not well understood, production scale experiments to further develop process understanding may be needed.

All experience gained during the life cycle of a process will be available to confirm or address process understanding.

5.2 The Role of Risk Assessment

Risk assessment tools such as Failure Mode and Effect Analysis (FMEA) or Cause & Effect Matrices should be used to provide systematic and comprehensive risk assessment when defining the Design Space. These tools, when used effectively, allow the leveraging of the established Knowledge Space of Subject Matter Experts (SMEs), and can ensure that a rigorous review of relevant risks has been completed. SMEs with contrasting backgrounds will have a tendency to stress different risks and aspects and improve the quality of the overall risk assessment output.

The output from a systematic risk assessment such as a Cause & Effect Matrix will allow a team of SMEs to agree on the highest risk relationships between Process Parameters and Quality Attributes and will lead to discussions on how best to design experiments to better understand the functional relationships.

Risk Assessment information should be kept current throughout the product or process lifecycle and used to expand the Knowledge Space for future products with similar processing steps.

6. Control Strategy

Control Strategy is defined as the input material controls, process controls and monitors, and finished product tests, as appropriate, that are proposed and justified in order to ensure product quality.

The Control Strategy will ensure the product is manufactured within the Design Space to meet all Critical Quality Attributes and other business-driven Quality Attributes (e.g. that affect cost or manufacturability, but are not directly related to efficacy and patient safety.

The Control Strategy should be a comprehensive plan for ensuring that the final product meets the requirements of the patient by ensuring the manufacturing process remains within the Design Space.

The Control Strategy requires the establishment of the Knowledge Space, which will have been used to determine the level of criticality. Aspects of this strategy may include:

• Key raw material and excipient properties 
• Key processing parameters 
  • Set points 
  • Processing times 
• Process Analytical Technology (PAT) 
• Product testing requirements.

6.1 Proposed Control Strategy Model

A Control Strategy is based on linking pharmaceutical development to the manufacturing process, and engineering controls of process equipment. Control Strategy as a term can mean different things to different functions. In particular, engineers often use the term Control Strategy to mean how plant and equipment is controlled to enable manufacture. The Control Strategy in this context should be linked back to product development and ultimately patient efficacy and safety.

Although the primary driver for development of a control strategy will be assurance of product quality, (and hence safety, and efficacy), the control strategy that is implemented may also address other aspects such as the health and safety of operators, protection of the environment, manufacturability, supply related issues, efficiency, and profitability of the business.

Figure 2 shows how the patient safety and efficacy aspects may be separated from the business aspects.

Figure 2. Control Strategy Matrix

This six box matrix shows three vertical levels to provide links from development scientist via manufacturing to process engineering control, and two horizontal levels to provide clarity between patient and business requirements.

The matrix also shows what should be included in a submission, and what should only provide supporting or general background information. This supporting information is not normally needed for pharmaceutical reviewers but may be included in some cases, for example if the control includes new technology. This information may also be the subject of inspection by regulatory agencies.

6.2 Developing a Control Strategy

Development of a Control Strategy for a product is an iterative activity, as the Knowledge Space and the resulting Design Space are established and process understanding evolves. Since process understanding will continue to develop during the product lifecycle, so the Control Strategy may also evolve.

The complete process for manufacture of the product should be considered, starting with the manufacture of the drug substance through packaging and labeling. For example, there may be several unit operations or process steps in the manufacturing process that influence a CQA. This may lead to the identification of a CQA of the in-process material that relates to the CQA of the final product. The identification of these CQAs for in process material may, in turn, lead to the identification of one or more CPPs that should be controlled such that the CQA of the in process material meets in-process specifications.

Process parameters required to be measured and controlled to achieve other business requirements should also be identified at this step.

Additional controls intended to meet other business requirements should also be identified and integrated into the overall control strategy. In practice controlling plant and equipment (either automatically or manually) will address both streams together.

6.3. Control Strategy throughout the Product Lifecycle

Quality Risk Management approaches as described in ICH Q9 should be applied throughout the product lifecycle, and integrated into the Quality System (see ICH Q10). Risk assessments should be performed at each product lifecycle phase to identify risks to product efficacy and patient safety, and as input into developing a Control Strategy.

During manufacture product and process history should form a basis for risk reviews to determine continued appropriateness of the Control Strategy.

A robust change management process should be implemented to ensure that the Control Strategy remains in place and effective as changes occur, and do not therefore inadvertently impact CPPs.

7. Glossary

Control Strategy: the input material controls, process controls and monitors, and finished product tests, as appropriate, that are proposed and justified in order to ensure product quality.

Critical Quality Attribute: a physical, chemical, biological or microbiological property or characteristic that needs to be controlled (directly or indirectly) to ensure product quality.

Critical Process Parameter: a process parameter whose variability impacts a quality attribute and therefore needs to be controlled to ensure the process produces the desired quality. A critical process parameter remains critical even if it is controlled.

Design Space: the multidimensional combination and interaction of input variables (e.g. material attributes) and process parameters that have been demonstrated to provide assurance of quality. Working within the design space is not considered as a change. Movement out of the design space is considered to be a change and would normally initiate a regulatory post-approval change process. Design space is proposed by the applicant and is subject to regulatory assessment and approval.

Knowledge Space: The sum of existing information composed of prior knowledge, the body of scientific information and data about the product and process.

Pharmaceutical Target Product Profile: a prospective and dynamic summary of the quality characteristics of a drug product that ideally will be achieved to ensure that the required quality, hence safety and efficacy, of a drug product is realised. It forms the basis of design for the development of the product.

Quality by Design: a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding based on sound science and quality risk management.

Quality Risk Management: a systematic process for the assessment, control, communication and review of risks to the quality of the drug (medicinal) product across the product lifecycle.

8. References

• ICH Q8 Pharmaceutical Development 
• ICH Q9 Quality Risk Management 
• ICH Q10 Quality Systems 
• FDA Pharmaceutical cGMPs for the 21st Century - A Risk-Based Approach. Final Report 
• Quality by Design: An Overview by John Berridge, Ph.D.

TASK TEAMS

Critical vs. Non-Critical 

• Roger Nosal, Pfizer (chair)
• Joanne Barrick, Lilly 
• Chris Brook, GSK 
• John Donaubauer, Abbott 
• John Groskoph, Pfizer 
• Jay Lakshman, Novartis 
• Wim Oostra, Organon 
• Tom Schultz, Johnson & Johnson 
• Steve Simmons, Wyeth 
• Shailesh Singh, Wyeth 
• Mani Sundararajan, AstraZeneca

Traditional vs. QbD Control Strategies

• Line Lundsberg, NNE Pharmaplan (chair) 
• Bruce Davis, AstraZeneca 
• Graham Cook, Wyeth 
• Tom Garcia, Pfizer 
• Hedinn Valthorsson, Novartis 
• Mette Bryder, Lundbeck 
• Michael Hahn, Lundbeck 
• Ray Bolton, AstraZeneca 
• Steve Tyler, Abbott 
• Jeff Kinzer, Merck 
• Sue Busse, Lilly 
• Gordon Muirhead, GSK

Design Space

• John Lepore, Merck (chair) 
• Theodora Kourti, GSK 
• Alastair Coupe, Pfizer 
• Vincent McCurdy, Pfizer 
• Richard Saunders, Wyeth 
• Kim Vukovinsky, Pfizer 
• William Spanogle, Johnson & Johnson 
• Steve Laurenz, Abbott 
• Kevin Siebert, Lilly 
• Jim Spavins, Pfizer 
• Tim Watson, Pfizer

PQLI Chair
Ron Branning
Dr. David W. Selby, PhD (co-chair)

Steering Committee
Dr. Robert G. Baum, PhD
Dr. John C. Berridge, PhD - Advisor
Bruce S. Davis
Paul D'Eramo
Charles P. Hoiberg, PhD
Dr. George P. Millili, PhD
Gert Moelgaard
Joseph X. Phillips, Sr. - Advisor
Dr. Russ F. Somma, PhD
Robert W. Tribe - Advisor

Task Team Leads
John Lepore
Dr. Line Lundsberg
Roger Nosal
Dr. Christopher Potter
Dr. Thomas W. Schultz, PhD
James C. Spavins

Technical Writer
Sion Wyn