EMR 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, 69600, Oullins, France.
Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France.
Invest New Drugs. 2020 Dec;38(6):1796-1806. doi: 10.1007/s10637-020-00953-y. Epub 2020 May 25.
The attrition rate of anticancer drugs during the clinical development remains very high. Interspecies extrapolation of anticancer drug pharmacodynamics (PD) could help to bridge the gap between preclinical and clinical settings and to improve drug development. Indeed, when combined with a physiologically-based-pharmacokinetics (PBPK) approach, PD interspecies extrapolation could be a powerful tool for predicting drug behavior in clinical trials. The present study aimed to explore this field for anticipating the clinical efficacy of a new Bcl-2 inhibitor, S 55746, for which dose ranging studies in xenografted mice and clinical data from a phase 1 trial involving cancer patients were available. Different strategies based on empirical or more mechanistic assumptions (based on PBPK-PD modelling) were developped and compared: the Rocchetti approach (ROC); the Orthogonal Rocchetti approach (oROC), a variant of ROC based on an orthogonal regression; the Consistent across species approach, bringing out an efficacy parameter assumed to be consistent across species; and the Scaling species-specific parameters approach, assuming the concentration-efficacy link is the same in mice as in humans, after allometric scaling. Empirical approaches (ROC and oROC) gave similar predictive performances and seemed to overestimate the active S 55746 dose compared to mechanistic approaches, while strategies elaborated from semi-mechanistic concepts and PBPK-PD modelling did not seem to be invalidated by clinical efficacy data. Also, empirical methods only predict a single dose level for the subsequent clinical studies, whereas mechanism-based strategies are more informative about the dose response relationship, highlighting the potential interest of such approaches in drug development.
抗癌药物在临床开发过程中的损耗率仍然非常高。种间外推抗癌药物药效学(PD)可以帮助弥合临床前和临床环境之间的差距,并改善药物开发。事实上,当与基于生理学的药代动力学(PBPK)方法结合使用时,PD 种间外推可以成为预测临床试验中药物行为的有力工具。本研究旨在探索这一领域,以预测新型 Bcl-2 抑制剂 S 55746 的临床疗效,该抑制剂在异种移植小鼠中进行了剂量范围研究,并在涉及癌症患者的 1 期临床试验中获得了临床数据。开发并比较了基于经验或更基于机制假设(基于 PBPK-PD 建模)的不同策略:罗切蒂方法(ROC);正交罗切蒂方法(oROC),是基于正交回归的 ROC 的变体;跨物种一致性方法,提出了一种假定在物种间一致的疗效参数;以及种特异性参数缩放方法,假设在所有ometric 缩放后,小鼠和人类中的浓度-疗效关联是相同的。经验方法(ROC 和 oROC)给出了相似的预测性能,并且似乎高估了活性 S 55746 剂量,而基于半机制概念和 PBPK-PD 建模的策略似乎没有被临床疗效数据否定。此外,经验方法仅预测后续临床研究的单个剂量水平,而基于机制的策略更能说明剂量反应关系,突出了这些方法在药物开发中的潜在兴趣。