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10:00 A.M. – Noon 7 June 2004 ICH Quality Plenary Meeting.

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Presentation on theme: "10:00 A.M. – Noon 7 June 2004 ICH Quality Plenary Meeting."— Presentation transcript:

1 10:00 A.M. – Noon 7 June 2004 ICH Quality Plenary Meeting

2 Scope of this Meeting  Quality Topics Q1, Q3, Q4, Q5, Q8, Q9, QS proposal Q1, Q3, Q4, Q5, Q8, Q9, QS proposal  Focus of this meeting be limited to Q8, Q9, and the QS Scoping Document Other topics be discussed separately Other topics be discussed separately Q1 – Tuesday 8:00 a.m., meeting of the group of expertsQ1 – Tuesday 8:00 a.m., meeting of the group of experts Q3AR and Q3BR Q&A (further discussion; When? Who?)Q3AR and Q3BR Q&A (further discussion; When? Who?) Q4B – “Regulatory Acceptance of Pharmacopeial Interchangeability”Q4B – “Regulatory Acceptance of Pharmacopeial Interchangeability” Q5E –Discussions with S&E experts (comments on statements referring to non-clinical and clinical studies)Q5E –Discussions with S&E experts (comments on statements referring to non-clinical and clinical studies)

3 Meeting Agenda  A brief perspective on Q8 and Q9 To facilitate and structure our discussion on To facilitate and structure our discussion on General principles and scope of Q8 & Q9General principles and scope of Q8 & Q9 Understanding the connection and approaches for integration between Q8 and Q9Understanding the connection and approaches for integration between Q8 and Q9  Q8 Progress and Next Steps  Q9 Progress and Next Steps  QS Scoping Document – Need, Objective, Scope, Relation to Q8 & Q9, …?

4 Pharmaceutical Development  Multi-disciplinary complex process  Many choices/approaches for achieving the goal  Both industry and regulators wish to assure that Decisions are based on science to assure a product will perform its intended function for the required duration within a given environment Decisions are based on science to assure a product will perform its intended function for the required duration within a given environment This includes designing in the ability to maintain, test, and support the product throughout its total life cycle. This includes designing in the ability to maintain, test, and support the product throughout its total life cycle. “Building quality in” or “assuring quality is by design” “Building quality in” or “assuring quality is by design” Quality can not be tested into a product Quality can not be tested into a product

5 Opportunity  Over the last two decades we have learned how to solve complex multi-factorial problems Multivariate empirical methods (e.g., Response Surface Methods) Multivariate empirical methods (e.g., Response Surface Methods) Systems approaches Systems approaches  New measurement and information technologies Measurements that can predict performance Measurements that can predict performance  Such information is often filtered out of regulatory submissions “fear” or “regulatory uncertinty” “fear” or “regulatory uncertinty”  ICH Q8 can open the door for sharing and utilizing this information

6 Within the design space only - e.g.,other variables held constant

7 Predicting Dissolution Drug Substance Formulation Process Product NIR Disso Test Bio PK/PD Dissolution = f (Ex1, Ex2, P1, P2, PS…) Real Time Release Stability

8 Systems focus  Provides a structured approach Development efficiency Development efficiency Use of prior knowledge Use of prior knowledge Continuous learning Continuous learning Risk mitigation Risk mitigation Knowledge sharing Knowledge sharing Knowledge communication Knowledge communication  Efficient and optimal decisions Industry - Regulators Industry - Regulators

9 Drug and disease models use mathematical, statistical and pharmacological concepts to accumulate and quantify knowledge to improve decision-making. Traditional Model-based Decision-making approaches Data Hidden Intuition Empirical Subjective Knowledge Transparent logic Predictive Objective Donald Stanski, FDA

10 Appropriate Level of Regulatory Scrutiny  All regulators desire to apply an appropriate level of regulatory scrutiny to Risk/Benefit decisions Risk/Benefit decisions Specifications, controls, change management to ensure unchanged performanceSpecifications, controls, change management to ensure unchanged performance In absence of relevant information their decisions reflect available data (unable to generalize reliably) In absence of relevant information their decisions reflect available data (unable to generalize reliably)

11 Data based decisions: No Generalization Current CMC Submissions environmental raw material properties process conditions

12 Knowledge based decisions: Improved Ability to Generalize Pharmaceutical Development Knowledge environmental raw material properties process conditions Robust process Stable and Bioavailable product

13 Ability to Generalize…  Provides a basis for assuring appropriate regulatory oversight Review/assessment decisions Review/assessment decisions Submission commitments Submission commitments Communication (Review/Inspection) for appropriate risk coverage Communication (Review/Inspection) for appropriate risk coverage Continuous improvement Continuous improvement EfficiencyEfficiency Reducing variabilityReducing variability

14 An Example of our (FDA) Current Limited Ability to Generalize..  Change: Site of Manufacture (no other change) – Modified Release Tablet No IVIVC No IVIVC Bioequivalence study, up to 3 batches of accelerated stability data,… PASBioequivalence study, up to 3 batches of accelerated stability data,… PAS Significant body of data (?) – 1 batch Significant body of data (?) – 1 batch IVIVC IVIVC No BE study, rest the sameNo BE study, rest the same Changes in formulation – is the IVIVC still valid? [correlation may not be causal, therefore may not hold] Changes in formulation – is the IVIVC still valid? [correlation may not be causal, therefore may not hold]

15 Ability to Generalize …  Provides a “measure” of process understanding  Provides an objective means to evaluate reliability of data/information/knowledge submitted Predictive ability Predictive ability Extent of coverage (design space) and data density Extent of coverage (design space) and data density  Objective approach for risk coverage (regulatory oversight) Reliability of generalization – Post approval change management (Review – Inspection – Company QS) Reliability of generalization – Post approval change management (Review – Inspection – Company QS)

16 Process Understanding Post approval change Risk CMC regulatory oversight Company’s Quality system cGMP regulatory oversight ICH Q8 ICH Q9

17 Process Understanding Risk (P/R) CMC regulatory oversight Company’s Quality system cGMP regulatory oversight Post approval change Post approval change Process Understanding Risk CMC regulatory oversight Company’s Quality system cGMP regulatory oversight Post approval change Process Understanding Risk CMC regulatory oversight Company’s Quality system cGMP regulatory oversight ICH Q8 + Q9


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