We consider a formal statistical design that allows simultaneous enrollment of a main cohort and a backfill cohort of patients in a dose-finding trial. The goal is to accumulate more information at various doses to facilitate dose optimization. The proposed design, called Bi3+3, combines the simple dose-escalation algorithm in the i3+3 design and a model-based inference under the framework of probability of decisions (POD), both previously published. As a result, Bi3+3 provides a simple algorithm for backfilling patients to lower doses in a dose-finding trial once these doses exhibit safety profile in patients. The POD framework allows dosing decisions to be made when some backfill patients are still being followed with incomplete toxicity outcomes, thereby potentially expediting the clinical trial. At the end of the trial, Bi3+3 uses both toxicity and efficacy outcomes to estimate an optimal biological dose (OBD). The proposed inference is based on a dose-response model that takes into account either a monotone or plateau dose-efficacy relationship, which are frequently encountered in modern oncology drug development. Simulation studies show promising operating characteristics of the Bi3+3 design in comparison to existing designs.

翻译：我们考虑一个正式的统计设计，允许在剂量确定试验中同时招募主要队列和补充队列的患者。其目标是积累更多的有关剂量的信息，以便促进剂量优化。所提出的 Bi3+3 设计将 i3+3 设计中的简单剂量逐级递增算法和基于模型的推断耦合起来，并结合了先前已发布的决策概率（POD）框架。因此，当一些在用药阶段行为正常的患者被随访但没有完全观察完毕，POD 框架允许在剂量确定试验中做出药物剂量决策，从而可能加速临床试验。最后，Bi3+3 在考虑到毒性和功效结果的基础上，利用剂量效应模型估计出最优生物剂量（OBD）。模拟研究显示，相对于现有设计，Bi3+3 设计具有有前途的操作特性。