Hegde Pooja, Rodriguez Brianna, Bell Alec, Hall Stephen D, Rougée Luc R A
Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana.
Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana.
Drug Metab Dispos. 2025 Feb;53(2):100030. doi: 10.1016/j.dmd.2024.100030. Epub 2024 Dec 12.
Current drug discovery screens to assess the drug-drug interaction (DDI) risk caused by time-dependent inhibition (TDI) of cytochrome P450 (CYP) 3A4 are known to overpredict or produce false positives that do not translate in vivo. Recent work identified that inclusion of the allosteric modulator progesterone (PGS), at a concentration of 45 μM to human liver microsomal incubations, generated in vitro TDI values that replicated clinical DDI predictions for 2 well established mechanism-based inhibitors. Further application of this approach across a diverse set of compounds was undertaken in this study, with 56 molecules reported in literature as time-dependent inhibitors in vitro tested in the human liver microsomal TDI kinetic assay in the absence and presence of 45 μM PGS. No TDI signal was observed for 15 molecules under control conditions despite literature reports. For the remaining compounds observed to have a TDI signal under control conditions, presence of PGS modified the inactivation efficiency for 36 compounds and eliminated the TDI signal for 5 compounds that were false positives. In vitro kinetic values were incorporated into mechanistic static and dynamic physiologically based pharmacokinetic models to project DDIs. TDI parameters established in the presence of PGS decreased the magnitude of overprediction while maintaining a high sensitivity (96% and 100%) for the detection of TDI with improved specificity (69% and 89%) when using mechanistic static and dynamic models, respectively. Inclusion of PGS into in vitro TDI assays provides a simple, rapid, and cost-effective solution for identifying true CYP3A4 TDIs and improving TDI-related DDI predictions. SIGNIFICANCE STATEMENT: The impact of the previously determined optimal concentration of the allosteric modulator progesterone (45 μM) was evaluated across a set of 56 compounds reported to be time-dependent inhibitors in vitro. In vitro generated values were incorporated into mechanistic static and physiologically based pharmacokinetic models to predict extent of drug-drug interactions and compared to clinical reports. Inclusion of progesterone into the assay identified in vitro false positives and improved risk predictions.
目前用于评估细胞色素P450（CYP）3A4的时间依赖性抑制（TDI）所导致的药物-药物相互作用（DDI）风险的药物发现筛选方法，已知存在过度预测或产生在体内无法转化的假阳性结果的情况。最近的研究发现，在人肝微粒体孵育体系中加入浓度为45μM的变构调节剂孕酮（PGS），所产生的体外TDI值能够重现针对2种已确立的基于机制的抑制剂的临床DDI预测结果。本研究对该方法在多种化合物中的进一步应用进行了探索，对文献报道的56种在体外为时间依赖性抑制剂的分子，在不存在和存在45μM PGS的情况下，在人肝微粒体TDI动力学试验中进行了测试。在对照条件下，尽管有文献报道，但15种分子未观察到TDI信号。对于其余在对照条件下观察到有TDI信号的化合物，PGS的存在改变了36种化合物的失活效率，并消除了5种假阳性化合物的TDI信号。体外动力学值被纳入基于机制的静态和动态生理药代动力学模型以预测DDI。在存在PGS的情况下确定的TDI参数降低了过度预测的程度，同时在使用机制静态和动态模型时，分别保持了对TDI检测的高灵敏度（96%和100%）以及提高了特异性（69%和89%）。在体外TDI试验中加入PGS为识别真正的CYP3A4 TDI和改善与TDI相关的DDI预测提供了一种简单、快速且经济高效的解决方案。意义声明：在一组56种据报道在体外为时间依赖性抑制剂的化合物中，评估了先前确定的变构调节剂孕酮的最佳浓度（45μM）的影响。将体外产生的值纳入基于机制的静态和生理药代动力学模型以预测药物-药物相互作用的程度，并与临床报告进行比较。在试验中加入孕酮可识别体外假阳性并改善风险预测。
