Regulatory Affairs and Adaptive Designs

1. Regulatory Affairs and Adaptive Designs Greg Enas, PhD, RAC Director, Endocrinology/Metabolism US Regulatory Affairs Eli Lilly and Company

2. Key Messages • Adaptive designs open doors to realize the promise of translational medicine advocated by regulators • At each stage of drug development, regulators use a “lens” for their review of adaptive design proposals, protocols, and study results • Sponsors must not be shy about approaching regulatory agencies with adaptive design proposals, especially Phase 1 and 2. • Sponsors should thoughtfully consider adaptive design proposals as part of Phase 3, especially in the context of larger confirmatory program.

3. Outline • What’s important to regulators • When and with what should sponsors communicate with regulators • New horizons for adaptive designs in the regulatory context Note: US FDA administrative focus but regulatory science principles generalizeable

4. What’s Important to Regulators? • Probability that the wrong dose or the wrong drug is administered to the wrong patient at the wrong time must be known to be acceptably low • At each stage of drug development, regulators use a “lens” for their review • Meaning of any claims or conclusions made • Relationship between claims and evidence • Quality of the evidence • Totality of the evidence (e.g. “substantial”)

5. Meaning of Claims • Claims must be stated in terms of clearly defined hypotheses that convincingly dominate other plausible hypotheses • Regulatory scientific paradigm for confirmation of claims is constructed via hypothesis testing framework • H0: This agent should not be approved H1: This agent should be approved • Regulators adopted frequentist approach for drugs and biopharmaceuticals; Bayesian approach also acceptable for device approval

6. Relationship between Claims and Evidence • Clinical development program design • Individual study designs • Hypotheses to test and relationships to model • Sample size, Type 1 and 2 error limits, effect size, confidence interval width • Primary and secondary endpoints • Patient populations (inclusion, exclusion criteria) • Post accrual adaptations within and between patients (concomitant medications, rescue Rx, etc)

7. Relationship between Claims and Evidence (continued) • Designed to progressively discharge uncertainty related to desired claims • Start smaller / end bigger • Enriched proof of concept, then generalize • Start bigger / end smaller • Explore heterogeneity, then target • Biomarker and diagnostic test qualification • Overall and subgroup exploration / testing • Program-wise error rates (across studies)

8. Quality of the Evidence • Randomization and Blinding • Minimize unplanned changes post randomization • Certify that planned post randomization changes do not bias inferences • Transparency – tell regulators what you plan to do, then do what you say you will do and inform them that you did (or did not) do it the way you planned

9. Totality of the Evidence • Patient safety first ! Benefits (B) must outweigh risks (R) • If B<R then minimize exposure • If B>R then maximize exposure (or must B>>R ?) • If B = R then assume B<R • Total patient exposures needed to estimate R dictate how much needed when to estimate B • Adaptive designs may be driven by formal utility functions u(R, B) or other explicit considerations of total evidence • Substantial evidence of B>R for approval

10. Total Evidence can be generated via Adaptive Designs • Generally acceptable for early “learning” phase development programs in Phase 1 and 2 • Discouraged in confirmatory Phase 3 setting unless • exceptional circumstances (e.g. rare disease, special populations) • Additional (redundant?) fixed design studies dominate the confirmatory development plan

11. Clinical Development Planning with Regulators • Meaning of any claims or conclusions made • Target Product Profile (TPP) • Relationship between claims and evidence • Clinical development plan from “first in man” to approval • Study protocols and simulations supporting error rate control • Data Monitoring Committee charters, information control, and sponsor decision-making plan, statistical analysis plans • Quality of the evidence • Locked database documentation • DMC reports, information control results • Totality of the evidence (e.g. “substantial”) • Study reports/synopses, integrated summaries, etc.

12. Timing for Regulatory Communication • Communicate when you have the evidence needed to support your plans • As early as possible (e.g. Pre IND meetings or written feedback) • How much / how detailed depends on stage of development • If you want definitive regulatory action then provide fairly definitive proposals

13. New Regulatory Horizons • Exploratory INDs • End of Phase 2A meetings • Large, “simple”, “outcome” studies • Pre-approval Risk Management • Cardiovascular assessment of anti-diabetes drugs • FDA Amendments Act of 2007 • Risk Evaluation and Mitigation Strategy (REMS) • Observational • Comparative effectiveness

14. Regulator’s Perspective • Pro’s • Risk and benefit information can drive safe dose selection, patient populations to study, etc. • Stratified medicine via appropriately targeted labeling • Con’s • Summary test statistics and other inferential tools depend on a less certain and more complicated sample space • Chance of wrong decisions goes up • Longer, more intensive reviews needed

15. Time to Act is Now • Sponsors can develop adaptive design proposals that align with the regulator’s review lens at appropriate stages of drug development • Window of opportunity – don’t be shy about proposing adaptive designs. • Success in early phase development will support enhanced use in confirmatory phase development.