All Times EDT
Keywords: Bayesian adaptive design, combination therapy, dose-finding, optimal biological dose, master protocol
Cancer is a heterogeneous disease. Even in cancer with the same histology from the same site, the etiology in terms of driver mutations, immune profiles, and malignant clones can be different among different patients. Thus, combination therapies are not only indicating but also imperative in seeking cure for cancers. In the past decades, combination chemotherapy, targeted therapy, and immunotherapy have shown improved efficacy compared to monotherapy. The development of combination therapy, however, is challenging because of the complex issues of selecting agents, dose, sequence, and study population, etc. to minimize toxicity and maximize efficacy. Statistical designs for identifying safe and efficacious combinations such as the Bayesian optimal interval design for combinations (BOIN-Comb), Utility-based BOIN, BOIN12, and Bayesian adaptive designs to identify the optimal biological dose will be discussed. Recent examples in developing combination targeted agents and immunotherapies will be reviewed. The applications of randomized trials, factorial designs, master protocols, umbrella, basket, and platform trials for the efficient development of combination therapies will also be illustrated.