Scientific Data for Evidence-Based Drug Regulation

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