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Pilot Risk-Ranking Model to Prioritize Manufacturing Sites for GMP Inspections

Pilot Risk-Ranking Model to Prioritize Manufacturing Sites for GMP Inspections. Advisory Committee for Pharmaceutical Science Manufacturing Subcommittee July 21, 2004 David J. Horowitz, Esq. Director, Office of Compliance Center for Drug Evaluation and Research.

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Pilot Risk-Ranking Model to Prioritize Manufacturing Sites for GMP Inspections

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  1. Pilot Risk-Ranking Model to Prioritize Manufacturing Sites for GMP Inspections Advisory Committee for Pharmaceutical Science Manufacturing Subcommittee July 21, 2004 David J. Horowitz, Esq. Director, Office of Compliance Center for Drug Evaluation and Research

  2. GMP Initiative Announcement:August 21, 2002 • Evaluate the currency of our drug quality programs so that FDA resources are used most effectively and efficiently to address the most significant public health risks. • In order to provide the most effective public health protection, FDA must match its level of effort against the magnitude of the risk. • Resource limitations prevent uniformly intensive coverage of all pharmaceutical products and production. Although the agency has been implementing risk-based programs, a more systematic and rigorous risk based approach will be developed.

  3. ICH Q9: Defining Risk • Preliminary working definitions (March 2004) from ICH EWG on Quality Risk Management (Q9): • Risk: Combination of the probability of occurrence of harm and the severity of that harm. ISO 14971 • Harm:Damage to health, including the damage that can occur from loss of product efficacy, safety, quality or availability • Focus on quality for our purposes

  4. ICH Q9: Defining Risk (cont’d) • Quality:Degree to which a set of inherent characteristics of a product, system or process fulfils requirements • Requirements: Needs or expectations that are stated, generally implied or obligatory by the patients or their surrogates (e.g. health care professionals, regulators and legislators) • Combining key terms: Risk to quality is the probability/severity that drug will fail to meet the needs/expectations of the patients and their surrogates

  5. Needs and Expectations of Patients/Surrogates • For drug quality, what are the needs/expectations of patients/ surrogates? • Clinical performance is the key: • “… delivery of efficacy and safety as described in the label, derived from the clinical trials.” • Janet Woodcock, M.D. • Availability • Price?

  6. Clinical Performance • Drug performs as described in the approved labeling • Delivers the relevant attributes of the drug in the clinical database on which the FDA approval decision was based • What are these attributes that can serve as surrogates for clinical performance?

  7. Clinical Performance Surrogates • A product’s clinical performance surrogates are its established quality attributes, including: • Identity/potency • Purity • Strength • Bioavailability/delivery (e.g., dissolution) • Labeling/packaging • Physical performance/appearance (including aspects that influence adherence and acceptability)

  8. Identify Predicted/Known Hazards to Quality Attributes: Risk Factors • Risks to pharmaceutical quality can be identified based on the probability and severity of adverse impact on these quality attributes • Explicitly include factors that mitigate probability/severity of adverse effects or factors that have a positive impact

  9. Risk to Quality Probability Severity Failure to meet Needs/Expectations of Patients/Surrogates HARM Loss of Quality Quality Attributes Probability/Severity of Adverse Impact on Quality Attributes

  10. Identifying Risk Factors • What hazards can adversely impact drug quality attributes/surrogates? • What processes and parameters are critical for quality attributes/surrogates? • What factors may affect the identified hazards and critical parameters/processes? • Other variables predictive of drug products with or without identified quality attributes?

  11. Probability/Severity of Adverse Impact on Quality Attributes Identify Risk Factors Data Limitations Quantify Incentives Prioritize Improvement Feedback Aggregate Rank Revise Model

  12. A RISK-BASED FRAMEWORK FOR PRIORITIZING SITES FOR cGMP INSPECTION SITE RISK POTENTIAL PRODUCT PROCESS FACILITY • Site risk potential (SRP): • A function of the risk potentials for the PRODUCT, PROCESS and FACILITY component risk factors. • The SRP is a weighted combination of the PRODUCT, PROCESS and FACILITY risk potentials • Semi-quantitative risk potentials represented as “high,” “medium,” or “low,” and are numerically discrete variables in calculations.

  13. Ranking Manufacturing Sites Based on Aggregated Risks • Risks associated with each manufacturing site can be aggregated and ranked against risk scores for other manufacturing sites • Goals • Systematically incorporate our current knowledge about drug quality risks • Prioritize sites for periodic systems-based inspections • Data limitations • Some predicted risk factors not captured • Challenge and opportunity • Create incentives for manufacturers

  14. Risk Ranking Model: Product Factors • What are the intrinsic properties of products such that deficiencies in quality, if any, would have more adverse public health impact than others? • Recall data identifies products or dosage forms associated with frequent and/or serious recalls

  15. Risk Ranking Model:Facility Factors • Are some manufacturing facilities (or manufacturers) more likely to produce a product with quality problems? • Effectiveness of quality systems • Inspectional record and compliance history • Exposure: volume produced at facility • Other characteristics? • Macher and Nickerson study

  16. Risk Ranking Model:Process Factors • Are some manufacturing processes, for particular product classes, more likely to go wrong than others? • Use expert elicitation to identify risk factors and weightings • Risk of contamination or mix-ups • Maintaining state of control of the process • Potential for process capability metrics?

  17. Continuous Improvement • The model can only be as good as the scientific/technical assumptions and data that are used to develop the risk scores • Multiple iterations and successive revisions will reflect growing knowledge base and extensive input from internal and external experts • Your input on prioritizing areas for improvement will be very helpful

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