Cytochrome P450 (CYP) enzyme kinetics often do not conform to Michaelis-Menten assumptions, and time-dependent inactivation (TDI) of CYPs displays complexities such as multiple substrate binding, partial inactivation, quasi-irreversible inactivation, and sequential metabolism. Additionally, in vitro experimental issues such as lipid partitioning, enzyme concentrations, and inactivator depletion can further complicate the parameterization of in vitro TDI. The traditional replot method used to analyze in vitro TDI datasets is unable to handle complexities in CYP kinetics, and numerical approaches using ordinary differential equations of the kinetic schemes offer several advantages. Improvement in the parameterization of CYP in vitro kinetics has the potential to improve prediction of clinical drug-drug interactions (DDIs). This manuscript discusses various complexities in TDI kinetics of CYPs, and numerical approaches to model these complexities. The extrapolation of CYP in vitro TDI parameters to predict in vivo DDIs with static and dynamic modeling is discussed, along with a discussion on current gaps in knowledge and future directions to improve the prediction of DDI with in vitro data for CYP catalyzed drug metabolism.

中文翻译：

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时间依赖性酶失活：体外数据的数值分析和药物相互作用的预测。


细胞色素 P450 (CYP) 酶动力学通常不符合 Michaelis-Menten 假设，CYP 的时间依赖性失活 (TDI) 表现出复杂性，例如多底物结合、部分失活、准不可逆失活和顺序代谢。此外，脂质分配、酶浓度和灭活剂消耗等体外实验问题可能会使体外 TDI 的参数化进一步复杂化。用于分析体外 TDI 数据集的传统重绘方法无法处理 CYP 动力学的复杂性，而使用动力学方案的常微分方程的数值方法具有多种优势。 CYP 体外动力学参数化的改进有可能改善临床药物相互作用 (DDI) 的预测。本手稿讨论了 CYP 的 TDI 动力学的各种复杂性，以及模拟这些复杂性的数值方法。讨论了通过静态和动态模型外推 CYP 体外 TDI 参数来预测体内 DDI，并讨论了当前的知识差距和未来方向，以利用 CYP 催化药物代谢的体外数据改进 DDI 的预测。