In recent years, the use of adaptive design methods based on accrued data of on-going trials have become very popular for dose response trials in early clinical development due to their flexibility (EMEA, 2002). In this paper, we developed a hybrid frequentist-Bayesian continual reassessment method (CRM) in conjunction with utility-adaptive randomization for clinical trial designs with multiple endpoints. The proposed hyperlogistic function family with multiple parameters gives users flexibility for probability modeling. CRM reassesses a dose-response relationship based on accrued data of the on-going trial, which allows investigators to make decisions based on a constantly updated dose-response model. The proposed utility-adaptive randomization for multiple-endpoint trials allows more patients to be assigned to superior treatment groups. The performance of the proposed method was examined in terms of its operating characteristics through computer simulations.
