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Learn about adaptive designs for confirmatory trials, including proof-of-concept, dose finding, and dose-response modeling. Explore traditional and novel approaches like MCP-Mod, endorsed by EMA for Phase 2 studies.
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Overview of Adaptive Designs for Confirmatory Trials in East 6.5ASA SymposiumBoston, 2019 Hrishikesh Kulkarni hrishikesh.kulkarni@cytel.com
East 6.5 (three new modules) ASA-Boston-2019
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
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
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
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
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!
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
Adaptive SSR ASA-Boston-2019
Population Enrichment • There are a few variations of PE designs; Currently planned for Survival Endpoint trials Binary and Count
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
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
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
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
East MAMS ASA-Boston-2019
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.
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
Thank-you!Questions…?YouTube - https://www.youtube.com/user/CytelVideos/playlists hrishikesh.kulkarni@cytel.com