Science Board FDA’s New Bioresearch Monitoring Initiative

1. Science Board FDA’s New Bioresearch Monitoring Initiative Dr. Janet Woodcock Deputy Commissioner for Operations Food and Drug Administration November 4, 2005

2. “BiMo” = Bioresearch Monitoring Program • Cross-cutting Agency program — all centers, Office of Regulatory Affairs, Office of the Chief Counsel, Office of the Commissioner • Standard-setting • Inspections • Review and compliance/enforcement with good laboratory practices (GLP) standards in animal safety studies • Good clinical practices (GCP) standards in human trials of FDA-regulated products • Human subject protection (HSP) closely associated with BiMo, accomplishes IRB inspections and sets standards

3. Objectives of BiMo Program • Protect human subjects in trials of FDA-regulated products • Ensure high-quality and integrity of data used to: • Support marketing applications • Support regulatory decision making • Provide evidence base for clinical use of regulated products

4. Status of FDA’s New BiMo Initiative • Begun December 2004 • Steering committee charter approved by FDA Management Council • Currently scoping out dimensions of issues • Part of FDA’s Critical Path Initiative

5. BiMo Initiative — Cross Cutting Co-Chairs: Janet Woodcock M.D. and David LePay M.D. Scientific Lead: Rachel Behrman, M.D. Project Manager: Terrie Crescenzi Representatives from all centers and relevant offices

6. BiMo Program Is Very Important • Proper conduct of trials to ensure human safety • Trust and confidence in animal safety studies, clinical research, and product development process depend on the integrity of process and supporting data • Regulatory program provides assurance of integrity but can inhibit innovation — ideally will be facilitative • Regulatory program must modernize as practices change

7. Evolution of Clinical Trial Practices During Last Few Decades • New trial methods and designs • New methods of data collection and processing (e.g., electronic data capture) • New arrangements between sponsors and various contractors, among investigators, among institutions, among IRBs, and rise of free-standing for-profit study centers • Great number of studies in children and other vulnerable populations • Approaches to studies using existing human specimens

8. Evolution of Clinical Trial Practices • Delegation to parties not directly regulated by the FDA • Larger trials where contribution of single site may be small, but where study-wide systems of data control and management may be very significant • Centralized and/or for-profit IRBs • Increased globalization • Increase in implanted/complex medical device trials

9. Does FDA’s Current Regulatory Program Fit Today’s Realities? • Must facilitate effective IRB oversight of evolving clinical trials arena to facilitate • IRB oversight of human subject protection • FDA oversight of IRB function • Must provide regulatory guidance and perhaps new regulatory scheme that encompasses modern trial arrangements and participants/contractors • Need common standards and regulatory requirements for electronic data handling — both domestic and international

10. Does Regulatory Program Fit Realities? (cont.) • Must be able to accommodate globalization of clinical trials • Must ensure comprehensive approach to protection of vulnerable populations • Need to provide additional guidance to all parties regarding various procedures and special circumstances

11. Internal Challenges for BiMo/HSP Program • Highly decentralized function • Units of varying size in review centers • Field force — only a few experts in any given district • Very small centralized group in OC • Non-automated environment • Relative lack of guidance and standards

12. Additional Challenges: Multiplicity of Stakeholders • Patients and doctors • Investigators/clinical research community • Data managers • Industry sponsors • FDA review staff • Compliance/enforcement staff • HHS and other government agencies/depts.

13. Issues in Human Subject Protection • IRB System • Must modernize adverse event reporting to IRBs to accommodate major trend toward multicenter trials (Held Part 15 Hearing last summer) • Use of central IRBs — issued draft guidance Using a Centralized IRB Process, final guidance in clearance

14. Issues in Human Subject Protection (cont.) • Proposed rule: Institutional Review Board — Registration Requirements, published (with OHRP), FDA reviewing comments • FDA finalizing interim rule: 21 CFR 50.54 Subpart D — Additional Safeguards for Children in Clinical Investigations of FDA Regulated Products • Other rules and guidances in preparation

15. Issues in Human Subject Protection (cont.) • Risk-based approach optimization • Real-time inspection vs. retrospective • Risk-based algorithm for targeting inspections • Better technology approaches for tracking compliance

16. Current Issues in Clinical Trials Area — Regulations • Finalizing rule: Foreign Clinical Studies not Conducted Under an IND (21 CFR 312.120 • Will propose rule on reporting information related to falsification of clinical data • Developing revised rules on treatment use and charging under an IND

17. Current Issues in Clinical Trials Area — Guidance • Guidance on use of data monitoring committees • Guidances on conduct of clinical trials • Reviewing comments on guidance Computerized Systems Used in Clinical Trials

18. Current Issues In Clinical TrialsArea — Data Quality Need • Common definition of data quality • Methods to assess • Assessment of current system for data quality • Continuous improvement

19. A Shared Goal — High-Quality Clinical Trial Data • Support integrity of clinical research enterprise • Support confidence of public/patients in human studies • Provide evidentiary base for product approvals and medical practices

20. Clinical Trial Data Quality —A Shared Responsibility • Investigator/site • Sponsor • FDA • ?Academia; journal editors

21. Investigator/Site Responsibilities • Embodied in GCPs • Accurate protocol compliance, observations, timing, and data entry • Importance of study personnel • ? Patient adherence

22. Sponsor Responsibilities • Clear and achievable study plans and protocols • Investigator and site training • Monitoring and auditing • “Data clean up”

23. FDA Responsibilities • Regulatory oversight of trial protocols and adverse events • Site inspections: “Bioresearch monitoring” • Review of data: paper-based or electronic data audit • Guidance: Framework for best practices and compliance with regulations • Enforcement: sanctions against sloppy performers or fraud

24. Additional System-Wide Issues — Automation and Standardization • Computer program validation and integrity (FDA Part 11, etc.) • Data and format standardization • Standard format CRF (case report form) • Standardized terminologies • Standardization is best tool for decreasing variation

25. Definition of High-Quality Data? • 100 % Accurate • Fit for use • Meets protocol — specified parameters • Arbitrary “acceptable levels of variation” per explicit protocol specification?

26. Definition of High-Quality Data — Considerations • Allow risk management approach • Probability the “x” level of variation could affect conclusions/sensitivity analysis • Are all questions equally important? (Concomitant meds)

27. General Definition of Quality • Meets needs of customer • Sponsor • Regulator • Ultimately, patient and provider • What, exactly, are customer’s needs? • How to actually assess quality?

28. Frequent Operational Definition of Quality • Control variability • Acceptable variability differs by use/customer (specification) • ? Trade offs among efficiency, productivity, and control of variability • Need tools to assess and quantify

29. Generally — Quality is a System Property • Difficult to inspect “quality in” — i.e., monitoring, auditing • Need to build “quality in” (e.g., analogous to quality in other industries) • How to obtain within the healthcare system • What combination of FDA programs — education, guidance, collaboration, inspection, enforcement — will achieve the best results?

30. FDA Role in Overall System for Data Quality • Oversee whole enterprise — ensure that the system is working • Evaluate level of data quality problems across all studies/development programs • Not able to directly oversee each study — use risk management approach • High risk (experience, country, complexity, sponsor-investigator) • Quality assurance, not quality control

31. Are There Opportunities for Improvement in Current System? • Large number of resources expended on ensuring data quality • Overall system has not been explicitly examined • FDA currently evaluating; will need to include many others in process

32. Probable Opportunities • Automation, e.g. linked networks (e.g. CA BIG project) • Standardization • Establish common definitions of data quality • Systems-based approach at FDA

33. BiMo Initiative Work Plan • Continue to gather information from internal and external stakeholder groups • Identify short-term deliverables and complete (e.g. guidances) • Define desired states and develop longer term plan for achievement • Conduct workshops and create other opportunities for public input