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Overview of Adaptive Designs for Confirmatory Trials in East 6.5 ASA Symposium Boston , 2019

Overview of Adaptive Designs for Confirmatory Trials in East 6.5 ASA Symposium Boston , 2019. Hrishikesh Kulkarni hrishikesh.kulkarni@cytel.com. East 6.5 (three new modules). Dose-response studies. Establish Proof-of-Concept (PoC)

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Overview of Adaptive Designs for Confirmatory Trials in East 6.5 ASA Symposium Boston , 2019

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  1. Overview of Adaptive Designs for Confirmatory Trials in East 6.5ASA SymposiumBoston, 2019 Hrishikesh Kulkarni hrishikesh.kulkarni@cytel.com

  2. East 6.5 (three new modules) ASA-Boston-2019

  3. Dose-response studies • Establish Proof-of-Concept (PoC) • change in dose desirable change in endpoint of interest • Dose finding step • Select one (or more) “good” dose levels for confirmatory Phase III once PoC has been established

  4. Traditional Approach • Proof-of-Concept: Conducted using (multiple) active arms and placebo • Selection of Target Dose: • statistically significant at the proof-of-concept stage • smallest of statistically significant doses but also clinically relevant • Dose-Response Modeling: • use data from PoC and earlier trials • find a statistical model capturing the effects of target dose on dose-response

  5. Traditional Approach • Straight-forward approach • However: • focuses on narrow dose range where sponsors can have faith that they will establish a clear dose-signal • dose-response model should itself play a greater role in choosing the right dose • focuses on modeling at the very end of the process

  6. Design Considerations – candidate models

  7. MCP + Mod = MCPMod • Design stage • Pre-specification of candidate dose-response models • Analysis stage (MCP-step) • Statistical test for dose-response signal. Model selection based on significant dose response models • Analysis stage (Mod-step) • Dose response and target dose estimation based on dose-response modeling Trial Design Stage Trial Analysis Stage

  8. A Novel Approach! • MCP-Mod • Combines multiple comparison and model based approaches • Robust to model misspecification • Flexible dose estimation • Result • More informative phase 2 designs, more solid basis for confirmatory study! • Endorsed by EMA!

  9. East MCPMod • Purpose – Design and analysis of Ph 2 Dose Response Studies • Design based on Optimal Allocation (D-Optimal/Target Dose/both) • Available for Normal, Binary and Count endpoints • For SAS users, Cytel’s Proc MCPMod already available for Analysis

  10. Adaptive SSR ASA-Boston-2019

  11. Population Enrichment • There are a few variations of PE designs; Currently planned for Survival Endpoint trials Binary and Count

  12. Clinical Trial Simulation • Define true underlying scenario(s) for endpoint(s), study design(s), decision rule(s) • Generate many repetitions • Summarize results • Use to choose and justify trial design • Demonstrates design performance for a span of potential true scenarios • Widely used in Drug Development

  13. Program Simulations • Dose Escalation followed by a cohort expansion study • Stage1: Dose escalation design (3+3, mTPI, CRM, BLRM) • Stage2: Single-arm cohort expansion • Frequentist or Bayesian GNG rules • Phase 2 oncology trial followed by Group Sequential • Stage1: Single-arm binomial, Simon’s two-stage, or 2-arm survival • Stage2: A group sequential design

  14. Drug Program Simulation • Define a sequence of clinical trial simulations, decision rules and design options for moving from one trial to the next • Aim to optimize the sequence of trials for a particular set of drug program objectives

  15. Initial Ph1b-Ph2b Development Plan STOP Ph1b Biomarker Dose- Finding Go Ph3 Go Go Ph2b with Clinical Endpoint Ph1b Biomarker PoC STOP STOP Key Objective Design Ph2b trial to maximize probability of Ph3 dose choice

  16. Program Design example

  17. East MAMS ASA-Boston-2019

  18. Graphical MCP (gMCP) • Multiple hypothesis testing using graphical method • Always easier to communicate with clinical teams than long, abstract and often counterintuitive decision tables • Example: Graphical illustration of the Bonferroni–Holm procedure • For Design and Analysis of Normal and Binary endpoint trials.

  19. Enhancements in 6.5 from 6.4 • BASE - Super Superiority • SEQUENTIAL - Equivalence • ADAPT/SURVADAPT - SSR for Non-Inferiority • MAMS- Binomial (both designs) • MAMS - Survival (only p-value combination design) • PREDICT– Weibull distribution • ESCALATE- mTPI-2 • ENDPOINTS- Mixed type, gMCP for Normal, binomial endpoints only. • SURVIVAL – Simulate with Surrogate Endpoints

  20. Thank-you!Questions…?YouTube - https://www.youtube.com/user/CytelVideos/playlists hrishikesh.kulkarni@cytel.com

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