Quantitative Clinical Pharmacology, Clinical Pharmacology and Safety Science, R&D BioPharmaceuticals, AstraZeneca, Boston, USA.
Safety and ADME Modelling, Clinical Pharmacology & Safety Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK.
Eur J Pharm Sci. 2019 Nov 1;139:105061. doi: 10.1016/j.ejps.2019.105061. Epub 2019 Aug 31.
Understanding the influence of ethnicity on drug exposure is key to patient safety and could minimize repetitive clinical studies. This analysis aimed to evaluate the ability of physiologically-based pharmacokinetic modelling to predict exposure of CYP2C19 substrates (lansoprazole, (es)citalopram, voriconazole) across Caucasian and East Asian populations. CYP2C19 abundance levels in Japanese and Chinese populations have been re-assessed based on clinical evidence. Model performance in each population was evaluated by predicted-over-observed AUC ratios and comparison of observed data with simulated plasma concentration profiles. Exposures in 84.4% (76 out of 90) of the clinical studies were predicted within 1.5-fold of observed values. The reported concentration-time profiles were well-captured within the 90% prediction intervals. With specified CYP2C19 phenotype, PBPK modelling is capable to predict systemic exposure of drugs largely metabolized by CYP2C19 in different ethnic populations. This study demonstrated PBPK modelling can be applied to assess genotype-dependent exposure difference across ethnicities.
了解种族对药物暴露的影响是患者安全的关键，并且可以最大限度地减少重复的临床研究。本分析旨在评估生理药代动力学模型在预测 CYP2C19 底物（兰索拉唑、（S）西酞普兰、伏立康唑）在白种人和东亚人群中的暴露情况的能力。根据临床证据，重新评估了日本人种和中国人群中的 CYP2C19 丰度水平。通过预测-观察 AUC 比值评估了每个群体中的模型性能，并比较了观察数据与模拟的血浆浓度曲线。在 90%的临床研究中，84.4%（76/90）的暴露量在观察值的 1.5 倍以内得到了预测。报告的浓度-时间曲线在 90%预测区间内得到了很好的捕捉。在指定 CYP2C19 表型的情况下，PBPK 模型能够预测主要由 CYP2C19 代谢的药物在不同种族人群中的全身暴露情况。这项研究表明，PBPK 模型可以用于评估不同种族人群中基因型依赖性暴露差异。
