1. Scientific Data for Evidence- Based Drug Regulation Janet Woodcock, M.D. Director, Center for Drug Evaluation and Research Food and Drug Administration September 24, 2009

2. Agenda Background Scientific data in regulations, policy standards, and guidance Scientific data in decision-making Generating new scientific data Improving transparency

3. Background Pharmaceuticals are among the most tightly regulated products in the U.S. Manufacturing, human investigations, market access, label claims, advertising and promotion all regulated by the FDA Regulation based on scientific standards to the extent possible Drug regulation has always been controversial

4. Background (cont.) Many pharmaceutical standards are harmonized internationally It is very difficult for FDA regulations, guidance, and policy to keep pace with scientific innovation There is also much remaining uncertainty in the biological and social sciences

5. Scientific Data in Regulations Rulemaking process Currently can take 8 years at FDA Avoid using specific numbers in regulation (i.e., limits) if possible (specify in guidance) Science informs approach Example Pregnancy Labeling Rule (proposed) Data: Animal toxicology Pharmacologic data Human exposure Communications Science Data How to relay sensible information to clinicians and pregnant women on risks and benefits of using a drug?

6. Scientific Data in Policy Decisions How to approach the CFC withdrawal, mandated by the Montreal Protocol, for asthma inhalers? How do deal with stearate in drug products in the face of BSE? If there is a shortage of a medically necessary drug, how to decide if unapproved drugs are OK?

7. Scientific Data in Standards Many FDA standards are technical FDA will often defer to SDO’s that establish technical standards Many scientific standards for drugs established internationally through the International Conference on Harmonization of Technical Requirements for Pharmaceuticals (ICH) Toxicology testing Manufacturing standards Clinical procedures such as Good Clinical Practices NOT approval standards FDA will go through Good Guidance Practice Procedures to establish these ICH standards in the U.S.

8. Scientific Data in Guidance “Good Guidance Practices” Started by FDA Involves dissemination of draft, public comment, potentially workshops and public meetings, final guidance Large number of science-based guidances Not binding on outside parties or FDA: represent FDA’s best scientific judgment

9. Regulation, Policy, Standard and Guidance Development Transparent, data-driven processes Generally involve extensive input from the affected communities, including the scientific experts Frequently involves public workshops and scientific meetings Used as basis for decisions on specific product applications

10. Scientific Data in Decision-Making Individual applications are reviewed against scientific standards Massive amounts of scientific data often evaluated-generated and submitted by industry Investigational drug applications: 10,000 New drug applications: 140 Abbreviated new drug applications: 800 Manufacturing data: 5,000 submissions

11. Scientific Data in Decision Making 140 New Drug Applications (NDAs) Estimate that each NDA contains an average of 10GB of data FDA scientists review these data against the established regulations, policies, standards and guidance (guidance not binding) Reviewers document whether the data meet the FDA standards in each area

12. Example: Animal Toxicology For an average, chronically dosed oral medication that is a new molecular entity, there may be 12 formal toxicology studies performed (all specified internationally), each of which may be preceded by an informal dose ranging study Most of these will be submitted during the IND phase of development

13. Example: Generic Drugs 800 new applications per year Contain scientific data (per standards) on manufacturing, stability, impurities, and, if parenteral, microbiology For “pills”, will have both fed and fasting bioequivalence studies that have to pass limits established in regulations, using studies specified in guidances

14. Scientific Data in Decision-Making Standards for Drug Labels (package insert) Each label statement must be backed up by scientific data Data reviewed by FDA staff to ensure label accuracy Standards for Drug Advertising Claims must be supported by data Enforcement against transgressions – going beyond the data

15. New Scientific Data There are huge knowledge gaps throughout drug regulation Poor translation of basic science into actionable regulatory science Lack of understanding/data on real world outcomes of using drugs Lack of application of known communication science to drug labeling, promotion and advertising

16. Translation of Basic Science FDA Critical Path Initiative seeks to bridge gaps between basic science and drug developmental science Use of public-private partnerships to fill gaps Multiple successful partnerships ongoing Put all results into public domain

17. Example: Predictive Biomarkers in Toxicology Multiple drug companies had biomarkers for drug induced kidney toxicity Consortium sponsored by C-Path Institute brought 16 companies together to share knowledge Resulted in acceptance of new renal biomarkers by FDA and EMEA Now starting human testing

18. New Scientific Knowledge about Drug Use Outcomes FDA carrying out the Sentinel Initiative Use eHRs and other electronic health data (e.g., claims) to form a distributed network to do analyses about drug use outcomes Pilot starting this year Will be a powerful source of new data: intend to use public-private partnerships

19. Improving Transparency Broad availability for scrutiny, analysis, and replication of results is a hallmark of good science Transparency of drug regulatory process has improved, but still needs to be improved: Transparency of decision-making process Transparency of basis (scientific data) for decisions

20. Particular Challenges Animal toxicology and human data considered commercial confidential and not releasable These data could be invaluable in advancing the science of toxicology and of human clinical trials (and drug development) Arguably, all human data should be made publicly available in some form

21. Particular Challenges Not all FDA drug reviews are made available in a timely manner FDA lacks the staff to perform the needed redaction of trade secret/commercial confidential data FDA releases adverse event reporting data on a quarterly basis (receives about 250,000 important reports annually)

22. Transparency More needs to be done on data availability and transparency FDA has data that might be invaluable in advancing human health if it were available to researchers Resource and legal barriers exist

23. Summary Drug regulation in the United States is a extensively scientific data-driven process, from the development of standards to the review of applications against the standards Many of these scientific standards are internationally accepted More needs to be done on data access and transparency