We consider a dose-optimization design for first-in-human oncology trial that aims to identify a suitable dose for late-phase drug development. The proposed approach, called the Pharmacometrics-Enabled DOse OPtimization (PEDOOP) design, incorporates observed patient-level pharmacokinetics (PK) measurements and latent pharmacodynamics (PD) information for trial decision making and dose optimization. PEDOOP consists of two seamless phases. In phase I, patient-level time-course drug concentrations, derived PD effects, and the toxicity outcomes from patients are integrated into a statistical model to estimate the dose-toxicity response. A simple dose-finding design guides dose escalation in phase I. At the end of the phase I dose finding, a graduation rule is used to assess the safety and efficacy of all the doses and select those with promising efficacy and acceptable safety for a randomized comparison against a control arm in phase II. In phase II, patients are randomized to the selected doses based on a fixed or adaptive randomization ratio. At the end of phase II, an optimal biological dose (OBD) is selected for late-phase development. We conduct simulation studies to assess the PEDOOP design in comparison to an existing seamless design that also combines phases I and II in a single trial.

翻译：我们提出一种针对首次人体肿瘤学试验的剂量优化设计，旨在为后期药物开发确定合适剂量。该方法称为“基于药代动力学的剂量优化”（PEDOOP）设计，整合了观测到的患者个体药代动力学（PK）测量数据与潜在药效学（PD）信息，用于试验决策和剂量优化。PEDOOP包含两个无缝阶段：在第一阶段，将患者个体药物浓度时间曲线、推导的PD效应及毒性结果纳入统计模型，以估算剂量-毒性反应关系；采用简单剂量探索设计指导第一阶段剂量递增。第一阶段剂量探索结束时，通过毕业规则评估所有剂量的安全性与有效性，筛选出疗效可期且安全性可接受的剂量，进入与对照组的随机对照第二阶段试验。在第二阶段，患者根据固定或适应性随机化比例分配至选定剂量。第二阶段结束时，确定用于后期开发的最优生物学剂量（OBD）。我们通过模拟研究评估PEDOOP设计，并将其与另一种在同一试验中合并I-II期的现有无缝设计进行对比。