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考虑酶丰度的相关性:一项评估生理药代动力学中全局敏感性分析影响的模拟研究。

Accounting for inter-correlation between enzyme abundance: a simulation study to assess implications on global sensitivity analysis within physiologically-based pharmacokinetics.

机构信息

Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Via Ferrata 5, Pavia, 27100, Italy.

Centre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, The University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.

出版信息

J Pharmacokinet Pharmacodyn. 2019 Apr;46(2):137-154. doi: 10.1007/s10928-019-09627-6. Epub 2019 Mar 23.

Abstract

Physiologically based pharmacokinetic (PBPK) models often include several sets of correlated parameters, such as organ volumes and blood flows. Because of recent advances in proteomics, it has been demonstrated that correlations are also present between abundances of drug-metabolising enzymes in the liver. As the focus of population PBPK has shifted the emphasis from the average individual to theoretically conceivable extremes, reliable estimation of the extreme cases has become paramount. We performed a simulation study to assess the impact of the correlation between the abundances of two enzymes on the pharmacokinetics of drugs that are substrate of both, under assumptions of presence or lack of such correlations. We considered three semi-physiological models representing the cases of: (1) intravenously administered drugs metabolised by two enzymes expressed in the liver; (2) orally administered drugs metabolised by CYP3A4 expressed in the liver and gut wall; (3) intravenously administered drugs that are substrates of CYP3A4 and OATP1B1 in the liver. Finally, the impact of considering or ignoring correlation between enzymatic abundances on global sensitivity analysis (GSA) was investigated using variance based GSA on a reduced PBPK model for repaglinide, substrate of CYP3A4 and CYP2C8. Implementing such correlations can increase the confidence interval for population pharmacokinetic parameters (e.g., AUC, bioavailability) and impact the GSA results. Ignoring these correlations could lead to the generation of implausible parameters combinations and to an incorrect estimation of pharmacokinetic related parameters. Thus, known correlations should always be considered in building population PBPK models.

摘要

生理相关药代动力学(PBPK)模型通常包含多组相关参数,如器官体积和血流。由于蛋白质组学的最新进展,已经证明肝脏中药物代谢酶的丰度之间也存在相关性。由于群体 PBPK 的重点已经从个体平均值转移到理论上可以想象的极端情况,因此对极端情况的可靠估计变得至关重要。我们进行了一项模拟研究,以评估两种酶丰度之间相关性对同时作为这两种酶底物的药物药代动力学的影响,假设存在或不存在这种相关性。我们考虑了三个半生理模型,分别代表以下情况:(1)静脉给予的药物由肝脏中表达的两种酶代谢;(2)口服给予的药物由肝脏和肠壁中表达的 CYP3A4 代谢;(3)静脉给予的药物由 CYP3A4 和肝脏中的 OATP1B1 作为底物。最后,我们使用 CYP3A4 和 CYP2C8 底物瑞格列奈的简化 PBPK 模型进行基于方差的全局敏感性分析(GSA),研究了考虑或忽略酶丰度之间相关性对 GSA 的影响。实施这些相关性可以增加群体药代动力学参数(例如 AUC、生物利用度)的置信区间,并影响 GSA 结果。忽略这些相关性可能导致产生不合理的参数组合,并对药代动力学相关参数的不正确估计。因此,在构建群体 PBPK 模型时,应始终考虑已知的相关性。

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