Adaptive Cohort Size Determination Method for Bayesian Optimal Interval Phase I/II Design to Shorten Clinical Trial Duration

TL;DR

This paper introduces an adaptive cohort size determination method for Bayesian Phase I/II clinical trials, aiming to shorten trial duration while maintaining accuracy in dose optimization.

Contribution

It presents a novel adaptive method for cohort size expansion based on ongoing toxicity and efficacy data, improving trial efficiency.

Findings

Reduced trial duration by approximately 20% on average

Maintained accuracy in dose selection

Demonstrated effectiveness through simulation

Abstract

Recently, the strategy for dose optimization in oncology has shifted to conduct Phase 2 randomized controlled trials with multiple doses. Optimal biologic dose selection from Phase 1 trial data to determine candidate doses for Phase 2 trials has been gaining attention. This study proposes a novel adaptive cohort size determination method for optimal biologic dose-finding to accelerate trials. The cohort size expansion is determined adaptively depending on the toxicity and efficacy data of the ongoing trial. In a simulation, the proposed method shortened the trial duration and maintained accuracy. The trial duration was reduced by an average of approximately 20% compared with the non-adaptive cohort size determination design. The cohort size expansion is demonstrated using a simple example.