Conference Program

BOIN12: Bayesian Optimal Interval Phase I/II Trial Design for Utility-Based Dose Finding (303589)

*Ruitao Lin, MD Anderson Cancer Center 

Keywords: Bayesian quasi likelihood, dose desirability, dose finding, optimal biological dose, phase I/II trials, utility

For immunotherapy such as checkpoint inhibitors and CAR-T cell therapy, as the efficacy does not necessarily increase with the dose, the maximum tolerated dose (MTD) may not be the optimal dose for treating patients. For these novel therapies, the objective of dose-finding trials is to identify the optimal biological dose (OBD) that optimizes patients’ risk-benefit tradeoff. We propose a simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit tradeoff. The BOIN12 design makes the decision of dose escalation and de-escalation by simultaneously taking account of efficacy and toxicity, and adaptively allocates patients to the dose that optimizes the toxicity-efficacy tradeoff. We perform simulation studies to evaluate the performance of the BOIN12 design. Compared to existing phase I/II dose-finding designs, the BOIN12 design is simpler to implement, has higher accuracy to identify the OBD, and allocates more patients to the OBD.