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Two-stage model-based clinical trial design to optimize phase I development of novel anticancer agents

机译:基于模型的两阶段临床试验设计,可优化新型抗癌药的I期开发

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Background The phase I program of anticancer agents usually consists of multiple dose escalation studies to select a safe dose for various administration schedules. We hypothesized that pharmacokinetic and pharmacodynamic (PK–PD) modeling of an initial phase I study (stage 1) can be used for selection of an optimal starting dose for subsequent studies (stage 2) and that a post-hoc PK–PD analysis enhances the selection of a recommended dose for phase II evaluation. The aim of this analysis was to demonstrate that this two-stage model-based design, which does not interfere in the conduct of trials, is safe, efficient and effective. Methods PK and PD data of dose escalation studies were simulated for nine compounds and for five administration regimens (stage 1) for drugs with neutropenia as dose-limiting toxicity. PK–PD models were developed for each simulated study and were used to determine a starting dose for additional phase I studies (stage 2). The model-based design was compared to a conventional study design regarding safety (number of dose-limiting toxicities (DLTs)), efficiency (number of patients treated with a dose below the recommended dose) and effectiveness (precision of dose selection). Retrospective data of the investigational anticancer drug indisulam were used to show the applicability of the model-based design. Results The model-based design was as safe as the conventional design (median number of DLTs = 3) and resulted in a reduction of the number of patients who were treated with a dose below the recommended dose (−27%, power 89%). A post-hoc model-based determination of the recommended dose for future phase II studies was more precise than the conventional selection of the recommended dose (root mean squared error 8.3% versus 30%). Conclusions A two-stage model-based phase I design is safe for anticancer agents with dose-limiting myelosuppression and may enhance the efficiency of dose escalation studies by reducing the number of patients treated with a dose below the recommended dose and by increasing the precision of dose selection for phase II evaluation. Keywords Oncology - Phase I trial design - Optimal design - Dose escalation - Dose finding - Pharmacokinetics - Pharmacodynamics - Modeling and simulation
机译:背景技术抗癌药物的I期计划通常包括多剂量递增研究,以为各种给药方案选择安全剂量。我们假设初始I期研究(第1期)的药代动力学和药效学(PK-PD)模型可用于为后续研究(第2期)选择最佳起始剂量,事后PK-PD分析可增强为II期评估选择推荐剂量。该分析的目的是证明基于两阶段模型的设计是安全,高效和有效的,并且不会干扰试验的进行。方法模拟了以中性粒细胞减少症为剂量限制性毒性药物的9种化合物和5种给药方案(第1阶段)的剂量递增研究的PK和PD数据。为每个模拟研究开发了PK-PD模型,并用于确定其他I期研究(第2期)的起始剂量。将基于模型的设计与常规研究设计进行了比较,包括安全性(剂量限制毒性(DLT)的数量),效率(用低于推荐剂量的剂量治疗的患者数量)和有效性(剂量选择的准确性)。研究性抗癌药物治疗的回顾性数据用于显示基于模型的设计的适用性。结果基于模型的设计与常规设计一样安全(DLT的中位数= 3),并减少了剂量低于建议剂量(−27%,功效89%)的患者。基于事后模型的未来II期研究推荐剂量的确定比常规选择推荐剂量更为精确(均方根误差为8.3%对30%)。结论基于模型的两阶段I期设计对于具有剂量限制性骨髓抑制的抗癌药物是安全的,并且可以通过减少用药剂量低于建议剂量的患者人数并提高治疗的准确性来提高剂量递增研究的效率。用于II期评估的剂量选择。肿瘤学-一期试验设计-最佳设计-剂量递增-剂量寻找-药代动力学-药效动力学-建模与仿真

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