28: Bayesian optimal interval design with prespecified preference in oncology combination trials

Music City Center 

The Bayesian optimal interval (BOIN) design framework, a model-assisted approach for identifying the maximum tolerated dose (MTD) in Phase I clinical trials, has become the standard method for dose-finding in oncology. In combination dose escalation studies, we usually have studied the safety profile of each drug used as monotherapy. BOIN combination design was proposed with all possible combinations explored. However, a practical preference based on prior clinical knowledge is often available for specific dose combinations or omitting certain doses. As a result, the BOIN combination design is usually not suitable for practical use. To address this need, we have developed and evaluated a generalized BOIN combination design that incorporates the preference (BOIN-CombP). Three categories of preference are considered including preferred, lower priority, and not considered. The performance of BOIN-CombP design has been evaluated by extensive simulations. The simulations demonstrated that the probability of selecting the correct MTD increases if it is among the preferred doses while the BOIN-CombP design achieves comparable toxicity control as the BOIN Combination design (BOIN-Comb).

dose finding

drug combination

interval design

maximum tolerated dose 

Biopharmaceutical Section