Effect of design specifications in dose-finding trials for combination therapies in oncology

Bayesian optimization design for finding a maximum tolerated dose combination in phase I clinical trials

The development of combination therapies has become commonplace because potential synergistic benefits are expected for resistant patients of single-agent treatment. In phase I clinical trials, the underlying premise is toxicity increases monotonically with increasing dose levels. This assumption cannot be applied in drug combination trials, however, as there are complex drug-drug interactions. Although many parametric model-based designs have been developed, strong assumptions may be inappropriate owing to little information available about dose-toxicity relationships. No standard solution for finding a maximum tolerated dose combination has been established. With these considerations, we propose a Bayesian optimization design for identifying a single maximum tolerated dose combination. Our proposed design utilizing Bayesian optimization guides the next dose by a balance of information between exploration and exploitation on the nonparametrically estimated dose-toxicity function, thereby allowing us to reach a global optimum with fewer evaluations. We evaluate the proposed design by comparing it with a Bayesian optimal interval design and with the partial-ordering continual reassessment method. The simulation results suggest that the proposed design works well in terms of correct selection probabilities and dose allocations. The proposed design has high potential as a powerful tool for use in finding a maximum tolerated dose combination.

Two-stage approach based on zone and dose findings for two-agent combination Phase I/II trials

In Phase I/II trials for a combination therapy of two agents, we ideally want to explore as many dose combinations as possible with limited sample size in Phase I and to reduce the number of untried dose combinations before moving to Phase II. Efficient collection of toxicity data in Phase I would eventually improve the accuracy of optimal dose combination identification in Phase II. In this paper, we develop a novel dose-finding method based on efficacy and toxicity outcomes for two-agent combination Phase I/II trials. We propose a "zone-finding stage" that determines the most admissible toxicity zone on the dose combination matrix and subsequently select the dose combination allocated to the next patient from that zone in Phase I. Upon completion of this zone-finding stage, we allocate the next patient to the dose combination determined by adaptive randomization of the admissible toxicity and efficacy dose combinations in Phase II. Simulation studies demonstrated the utility of the proposed zone-finding stage and proved that the operating characteristic of the proposed method was no worse than the existing method. The sensitivity of the proposed method, as well as the operating characteristic of this method when the efficacy outcome is delayed, was also examined.