Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.
Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Str. 65, 88397, Biberach an der Riss, Germany.
J Pharmacokinet Pharmacodyn. 2020 Dec;47(6):527-542. doi: 10.1007/s10928-020-09704-1. Epub 2020 Aug 8.
CYP3A plays an important role in drug metabolism and, thus, can be a considerable liability for drug-drug interactions. Population pharmacokinetics may be an efficient tool for detecting such drug-drug interactions. Multiple models have been developed for midazolam, the typical probe substrate for CYP3A activity, but no population pharmacokinetic models have been developed for use with inhibition or induction. The objective of the current analysis was to develop a composite parent-metabolite model for midazolam which could adequately describe CYP3A drug-drug interactions. As an exploratory objective, parameters were assessed for potential cut-points which may allow for determination of drug-drug interactions when a baseline profile is not available. The final interaction model adequately described midazolam and 1'-OH midazolam concentrations for constitutive, inhibited, and induced CYP3A activity. The model showed good internal and external validity, both with full profiles and limited sampling (2, 2.5, 3, and 4 h), and the model predicted parameters were congruent with values found in clinical studies. Assessment of potential cut-points for model predicted parameters to assess drug-drug interaction liability with a single profile suggested that midazolam clearance may reasonably be used to detect inhibition (4.82-16.4 L/h), induction (41.8-88.9 L/h), and no modulation (16.4-41.8 L/h), with sensitivities for potent inhibition and induction of 87.9% and 83.3%, respectively, and a specificity of 98.2% for no modulation. Thus, the current model and cut-points could provide efficient and accurate tools for drug-drug liability detection, both during drug development and in the clinic, following prospective validation in healthy volunteers and patient populations.
CYP3A 在药物代谢中起着重要作用,因此可能是药物相互作用的一个重要因素。群体药代动力学可能是检测此类药物相互作用的有效工具。已经开发了多种咪达唑仑模型,咪达唑仑是 CYP3A 活性的典型探针底物,但没有针对抑制或诱导作用开发的群体药代动力学模型。当前分析的目的是开发一种用于咪达唑仑的复合母体-代谢物模型,该模型可以充分描述 CYP3A 药物相互作用。作为探索性目标,评估了参数是否存在潜在的临界点,以便在没有基线谱的情况下确定药物相互作用。最终的相互作用模型充分描述了咪达唑仑和 1'-OH 咪达唑仑在组成型、抑制和诱导 CYP3A 活性下的浓度。该模型显示出良好的内部和外部有效性,无论是全谱还是有限采样(2、2.5、3 和 4 小时),并且模型预测参数与临床研究中发现的值一致。评估模型预测参数的潜在临界点,以使用单一谱评估药物相互作用的风险,表明咪达唑仑清除率可合理用于检测抑制(4.82-16.4 L/h)、诱导(41.8-88.9 L/h)和无调节(16.4-41.8 L/h),对强效抑制和诱导的敏感性分别为 87.9%和 83.3%,特异性为 98.2%用于无调节。因此,当前的模型和临界点可以为药物相互作用的风险检测提供高效准确的工具,无论是在药物开发期间还是在临床实践中,都需要在健康志愿者和患者群体中进行前瞻性验证。