Keywords: adaptive trial designs
Within the past few decades, drug combination therapy has been intensively studied in Oncology and other disease areas. Combination therapy of two or more agents may have additive or synergistic effect on efficacy and toxicity. The limited utility of single agents provides the impetus to co-develop the combinations early in the development plan. Moreover, investigation of multiple combinations (dual and triple) is often necessary to find the optimal therapy. This can significantly shorten the overall development time and bring potent regimens to patients quicker. In 2010, FDA has released a guidance to emphasize the importance of co-development of two or more investigational agents. However, dose finding with multiple combinations poses methodological challenges to trial design. It requires innovative adaptive trial designs to utilize available information efficiently. Traditional algorithm based dose-finding methods such as the 3+3 design are unable to provide such flexibility. We will present a novel Bayesian adaptive design to facilitate efficient dose finding with multiple combinations. The proposed model based methodology uses all available single agent and combination dose- dose limiting toxicity data proficiently to provide precise and clinically meaningful starting dose and dose escalation decisions by reducing patient risk. We’ll present a Phase I trial focusing co-development of dual and triple combinations with three investigational agents to illustrate the methodology.