A Bayesian phase I-II clinical trial design to find the biological optimal dose on drug combination.

In recent years, combined therapy shows expected treatment effect as they increase dose intensity, work on multiple targets and benefit more patients for antitumor treatment. However, dose -finding designs for combined therapy face a number of challenges. Therefore, under the framework of phase I-II, we propose a two-stage dose -finding design to identify the biologically optimal dose combination (BODC), defined as the one with the maximum posterior mean utility under acceptable safety. We model the probabilities of toxicity and efficacy by using linear logistic regression models and conduct Bayesian model selection (BMS) procedure to define the most likely pattern of dose-response surface. The BMS can adaptively select the most suitable model during the trial, making the results robust. We investigated the operating characteristics of the proposed design through simulation studies under various practical scenarios and showed that the proposed design is robust and performed well.