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Concept Paper #3: Risk Assessment of Observational Data Session 1: Good Pharmacovigilance Practices

Concept Paper #3: Risk Assessment of Observational Data Session 1: Good Pharmacovigilance Practices. Linda S. Hostelley on behalf of PhRMA. PhRMA Supports FDA Efforts on Risk Management Risk Management is a Continuum Positive Benefit Risk is Key Benefits and Risks Drive RMP

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Concept Paper #3: Risk Assessment of Observational Data Session 1: Good Pharmacovigilance Practices

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  1. Concept Paper #3:Risk Assessment of Observational Data Session 1: Good Pharmacovigilance Practices Linda S. Hostelley on behalf of PhRMA

  2. PhRMA Supports FDA • Efforts on Risk Management • Risk Management is a Continuum • Positive Benefit Risk is Key • Benefits and Risks Drive RMP • Evidence-Based Decisions • Systems-Based Approach • Impact on Drug Development • Collaboration is Essential 2

  3. Session 1: Good Pharmacovigilance Practices Question 1: How can the quality of spontaneously reported case reports be improved? PhRMA Response: • PhRMA supports FDA’s efforts to improve the quality of individual spontaneously reported cases • Balance must exist between the significance of the clinical event reported and the intrusiveness of follow-up with the treating healthcare professional • Simplify reporting • Identify best practices • Educate all partners to understand the importance of adverse experience reporting and the importance of quality reports • Collaboration between industry, FDA, academia, healthcare and patient organizations is essential 3

  4. Session 1: Good Pharmacovigilance Practices Question 2: What are the possible advantages or disadvantages of applying data mining techniques to spontaneous report databases for the purpose of identifying safety signals? PhRMA Response: • Data mining techniques may be a useful adjunct to traditional pharmacovigilance methods • Data mining techniques provide a systematic, efficient approach to screening large adverse event databases for potential safety signals • Limitations of the underlying data and the data mining techniques must be fully appreciated to avoid false positive causality conclusions • Research efforts should be targeted to reduce false positives • Collaboration between industry and FDA to define best practices and to optimize use of data mining technologies in pharmacovigilance and clinical risk management 4

  5. Session 1: Good Pharmacovigilance Practices Question 3: What are the possible advantages or disadvantages of performing causality assessments at the individual case level? PhRMA Response: • Inadequacy of spontaneous report data is problematic • With exception of cases with positive re-challenge, little or no advantage in preparing causality assessment on an individual case • Lack methodology for reliable and consistent individual causality assessment • High likelihood of misinterpretation 5

  6. Session 1: Good Pharmacovigilance Practices Summary • PhRMA supports development of best practices for improving the quality of spontaneous reports and for developing the methodologies for application of data mining techniques • PhRMA supports education of all partners involved in post-marketing surveillance 6

  7. Session 1: Good Pharmacovigilance Practices Additional Question for the FDA • What criteria should be used to determine whether a Pharmacovigilance Plan describing pharmacovigilance efforts above and beyond post-marketing spontaneous reporting is warranted? 7

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