Ajaz S. Hussain, Ph.D.
Current Affiliation: Chief Scientific Officer
Philip Morris International R&D, Neuchatel, Switzerland
Pharmaceutical Quality by Design: A Personal Review of Progress and Challenges
8th World Meeting on Pharmaceutics, Biopharmaceutics, and Pharmaceutical Technology
19th to 22nd March 2012, Istanbul, Turkey
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Reflections, a decade ago at FDA
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Reflections, a decade ago at FDA
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MIT PHARMACEUTICAL MANUFACTURING INITIATIVE (PHARMI)
OVERALL CYCLE TIMES:QC TESTING TIMES ARE SIGNIFICANT
0
5
10
15
20
25
TIME (Days)
A B C D E FPROCESS CASE STUDY
Overall Cycle Time Components
Process Time sQC Te sting Time s
•[PPT] Final Report on Process Analytical Technology and ... - FDA•www.fda.gov/ohrms/dockets/ac/04/.../2004-4080s1_09_Hussain.ppt•(Source: G. K. Raju, M.I.T. FDA Science Board Meeting, November 16, 2001).
Reflections, a decade ago at FDA
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MIT PHARMACEUTICAL MANUFACTURING INITIATIVE (PHARMI)
• Average Cycle time 95 days• Std dev(Cycle time) > 100 days• Exceptions increase cycle time by > 50 %• Exceptions increase variability by > 100%• Capacity Utilization of “System” LOW
PERFORMANCE MEASURE VALUE
Pharmaceutical Manufacturing:Impact of Exceptions(Detailed Analysis of 2 Products)
NEED FOR FUNDAMENTAL TECHNOLOGY
•[PPT] Final Report on Process Analytical Technology and ... - FDA•www.fda.gov/ohrms/dockets/ac/04/.../2004-4080s1_09_Hussain.ppt•(Source: G. K. Raju, M.I.T. FDA Science Board Meeting, November 16, 2001).
Reflections, a decade ago at FDA
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9
Pharma Manufacturing - Unmet Performance Expectations
Utilisation levels - 15% or less(but low levels masked).
Scrap and rework - we plan for 5-10%(accepted as necessary).
Time to effectiveness - takes years(not challenged).
Costs of quality - in excess of 20%(that's the way it is).
•[PPT] Final Report on Process Analytical Technology and ... - FDA•www.fda.gov/ohrms/dockets/ac/04/.../2004-4080s1_09_Hussain.ppt•(Source: FDA Science Board Meeting, November 16, 2001).
Shared vision for the 21st Century
Product quality and performance are achieved and assured by design of effective and efficient manufacturing processes
Product specifications are based on a mechanistic understanding of how formulation and process factors impact product performance
Manufacturers are able to effect continuous improvement and continuous "real time" assurance of quality
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Observing the current trends Recent industry comments suggest an ongoing struggle; for example, “QbD is in its infancy” or “not focused on QbD”
State of QbD Implementation: Adoption, Success and Challenges (McKinsey Report, 2011)
Negative perceptions - quality related recalls, warning letters, consent decrees, drug shortages, etc.
How should we measure progress of this initiative?
http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/AdvisoryCommitteeforPharmaceuticalScienceandClinicalPharmacology/UCM263468.pdf 3/19/2012 Ajaz S. Hussain, Ph.D. 7
How should we measure progress of this initiative?
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Number of guidance documents and the numerous conferences on the topic?
Industry comments (‘QbD is in its infancy’) or regulatory plans for implementing QbD by 2013?
Number of recalls, unresolved OOS investigations, warning letters and the resulting erosion of public trust?
QbD has always been the foundation – are there gaps in the initiative that needs to be filled
Gaps that needs to be filled
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Precise vocabulary & communication
• QbD is the foundation• Objective is to make science visible
‘Initiatives’ and ‘on the ground’ quality
• Enhance efforts on effective root-cause investigations• Risk management
Pragmatic approach to design-space
• Continual improvement• Supporting innovation
Precise vocabulary & communication
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The phrase “quality cannot be tested into products, it has to be built in by design” describes the foundation for Process Validation in the pharmaceutical industry
In early 2000 an additional focus was placed on this foundational element and the phrase ‘quality by design’ was used for emphasis
The objective was to overcome ‘art’ vs. ‘science’ debate and to ‘make science more visible’ and effectively utilized for risk-based decisions
Design: Art or science?A decade ago, at FDA, we debated the utility of pharmaceutical development information in regulatory decisions; “art (practice) vs. science’
The natural sciences are concerned with how things are...design on the other hand is concerned with how things ought to be
Scientific design is based on scientific knowledge but utilizes a mix of both intuitive and non-intuitive design methods
Through the application of scientific knowledge in practical tasks, design ‘makes science visible’
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Cross, Nigel (2001). Designerly ways of knowing: design discipline versus design science. Design Issues, 17(3), pp. 49–55.
Make science visible
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Why? To provide assurance of quality, for demonstrating effective risk reduction, and justifying options for efficiency improvements
How? Recognizing that ‘uncertainty = risk + opportunity’ and that regulators are open to science-based risk reduction and to create flexibility to facilitate efficiency improvements
What? Science and practice of assuring effective quality risk management and efficiency improvement
Science and practice of
Quality risk reduction
• Risks such as in 483 observations & Warning letters, and multiple review cycles
• Improving assurance of identity, purity, strength, potency
• Justifying acceptable variability of critical quality attributes
• Capability for rapid root-cause investigations
Efficiency improvement
• Reducing development, production and regulatory cycle times & costs
• Timely implementation of post-approval changes needed to improve the business ‘bottom line’
• Reducing stress and uncertainty associated with regulatory inspections
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Initiative's and ‘on the ground quality’
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Currently there are a large number of high profile ‘quality issues’ such as product recalls and warning letters that have attracted publics’ attention
While at the same time several companies have significant initiatives related to QbD
Is there not a need to balance efforts to also improve assurance of effective quality risk management for current products?
Enhance the focus on effective quality risk management for current products
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Risks such as in 483 observations & warning letters, and multiple review cycles
Justifying acceptable variability of critical quality attributes
Capability for rapid and effective problem root-cause investigations
Capability for effective problem root-cause investigations
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Root-cause investigations often conclude with ‘root cause unknown’
How we set specifications can contribute to OOS simply because of inherent variability ( often ‘common cause variability)
Discussions in Nov 2001 at the FDA Science Board highlithed a potential weakens in how we currently set specifications
Resolution of OOS is often difficult, a reason for warning letter - escalating to a consent decree
OOS: Out of specification
Conflicts in risk management
Cognitive: Lack of agreement on causal links
Evaluative: Lack of agreement on trade-offs
Normative: Lack of agreement on values and fairness
Manifest depending on complexity, uncertainty and ambiguity in the problem to be solved
Risk Analysis (2002) 3/19/2012 Ajaz S. Hussain, Ph.D.
Risk management: Simple to ambiguous problems
Routine operation• Agency staff• Discourse:
Internal• Simple
Scientific risk-assessment necessary• Conflict:
Cognitive• Agency staff &
external experts• Discourse:
Cognitive• Complex
Risk balancing necessary• Risk assessment
necessary• Conflict:
Cognitive and Evaluative
• Agency staff, external experts, stakeholders
• Discourse: Reflective
• Uncertain
Risk tradeoff analysis and deliberations necessary • Risk assessment
and balancing necessary
• Conflict: Cognitive, Evaluative, Normative
• Agency staff, external experts, stakeholders, public representatives
• Discourse: Participatory
• Ambiguous
Risk Analysis (2002)
Causal links identified & quantified
Difficult to identify and quantify causal links
Low confidence in causal links
Variable interpretation of identical data
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Resolving conflicts for effective risk management
Cognitive conflict: Improving understanding and acceptance of causal links
Evaluative conflict: Improving understanding of uncertainty inherent in the current approach and/or agreement on acceptable level of uncertainty
Ideally done by ‘making science visible’ when in good compliance status; after a warning letter focus on options that minimize evaluative conflict
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Making science visible during review phase
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A decade ago, in the US, pharmaceutical development information was not considered useful for CMC review
Currently ICH Q8 has been implemented in the NDA review process and by 2013 will be implemented for ANDAs
ICH Q8 introduced the concept of ‘design space’ to facilitate continual improvement; an option to reduce uncertainty and post-approval supplements
Pragmatic implementation of ICH Q8 (including design space) is necessary
http://www.fda.gov/Drugs/DevelopmentApprovalProcess/HowDrugsareDevelopedandApproved/ApprovalApplications/AbbreviatedNewDrugApplicationANDAGenerics/ucm292533.htm?source=govdelivery
Pragmatic implementation of ICHQ8
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Objective: scientific understanding to identify critical to quality attributes, variability in these attributes; to set controls and specifications
Specific information to improve decisions (e.g., risk-based)
Design space development – a focus on anticipated or planned efficiency improvements in the post approval phase can be a useful guide
Scientific design is based on scientific knowledge but utilizes a mix of both intuitive and non-intuitive design methods
Regulatory submissions: Pharmaceutics & Pharmaceutical Technology
Design thinking (often implicit)
Reasoning about uncertainty (blind spot?)
Making estimates (implicit)
Need to explicitly state the underlying theories and generate testable predictions
http://www.unusualleading.com/wp-content/uploads/2009/12/HBR-on-Design-Thinking.pdf
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What is scientific and what is not?
Francis Bacon’s Scientific Method
Karl Popper’s Falsification Theory
Thomas Kuhn’s Paradigm Shifts
The theoretical underpinnings of the methods must yield testable predictions by means of which the theory could be falsified
There should be a known rate of error that can be used in evaluating the results.
The methods should preferably be published in a peer-reviewed journal.
The methods should be generally accepted within the relevant scientific community
The U.S. Supreme Court: An Evolved Theory of Science (2000)
http://www.fjc.gov/public/pdf.nsf/lookup/sciman00.pdf/$file/sciman00.pdf
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Quality: Testable predictions? (illustrative)
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For the selected formulation, plus established raw-material acceptance criteria and control of process equipment, variability in content uniformity is expected to be within X% regardless of manufacturing site (e.g., Chicago vs. Louisiana)
Change in the supplier of excipients, using the established acceptance criteria, is expected to have an insignificant impact on shelf-life.
The established SOP and training procedures will result in X% deviations in first 1Q 2012 and the rate of deviations will reduce to Y% by end of 4Q 2012.
Pharmacokinetic/ pharmacodynamics modeling
• Utilizes theories and methods from physics, mathematics and engineering
• Examples• Transform theory from mathematics• Transport phenomena from
engineering and physics• Linear systems analysis from
engineering systems theory• Control theory from electrical
engineering
Pharmacometics (a multidisciplinary field)
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Impact of Pharmacometrics on drug approval decisions
Pharmacometric analyses are an increasingly important component NDA and BLA submissions to the US FDA (End of Phase II Meetings)
During 2000–2008 the number of reviews with an impact on approval and labeling increased significantly
Selection of pediatric dosing regimens, approval of regimens that had not been directly studied in clinical trials and provision of evidence of effectiveness to support a single pivotal trial.
Clinical Pharmacokinetics (October 2011)3/19/2012 Ajaz S. Hussain, Ph.D. 26
Concluding remarks
A decade ago, at FDA, we debated the utility of pharmaceutical development information in regulatory decisions; “art (practice) vs. science’
Through the application of scientific knowledge in practical tasks, design ‘makes science visible’’
A pragmatic approach based on explicit description of ‘theory’ underpinning assurance of product quality is essential
“Without theory, there is no learning.” -William E Deming
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