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房室药代动力学模型中可饱和分布的影响:动力学与实际应用

Impact of saturable distribution in compartmental PK models: dynamics and practical use.

作者信息

Peletier Lambertus A, de Winter Willem

机构信息

Mathematical Institute, Leiden University, PB 9512, 2300 RA, Leiden, The Netherlands.

Janssen Research & Development, Janssen Prevention Center, Archimedesweg 6, 2333 CN, Leiden, The Netherlands.

出版信息

J Pharmacokinet Pharmacodyn. 2017 Feb;44(1):1-16. doi: 10.1007/s10928-016-9500-2. Epub 2017 Jan 3.

DOI:10.1007/s10928-016-9500-2
PMID:28050672
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5306145/
Abstract

We explore the impact of saturable distribution over the central and the peripheral compartment in pharmacokinetic models, whilst assuming that back flow into the central compartiment is linear. Using simulations and analytical methods we demonstrate characteristic tell-tale differences in plasma concentration profiles of saturable versus linear distribution models, which can serve as a guide to their practical applicability. For two extreme cases, relating to (i) the size of the peripheral compartment with respect to the central compartment and (ii) the magnitude of the back flow as related to direct elimination from the central compartment, we derive explicit approximations which make it possible to give quantitative estimates of parameters. In three appendices we give detailed explanations of how these estimates are derived. They demonstrate how singular perturbation methods can be successfully employed to gain insight in the dynamics of multi-compartment pharmacokinetic models. These appendices are also intended to serve as an introductory tutorial to these ideas.

摘要

我们探讨了药代动力学模型中可饱和分布对中央室和外周室的影响,同时假设返回中央室的回流是线性的。通过模拟和分析方法,我们展示了可饱和分布模型与线性分布模型在血浆浓度曲线上的特征性显著差异,这可为它们的实际应用提供指导。对于两种极端情况,即(i)外周室相对于中央室的大小,以及(ii)与从中央室直接消除相关的回流大小,我们推导出了明确的近似值,从而能够对参数进行定量估计。在三个附录中,我们详细解释了这些估计值是如何推导出来的。它们展示了如何成功运用奇异摄动方法来深入了解多室药代动力学模型的动态特性。这些附录也旨在作为这些概念的入门教程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/9ae5d521f964/10928_2016_9500_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/b5e8d1c838ea/10928_2016_9500_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/09faff696422/10928_2016_9500_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/e8a36de97cc5/10928_2016_9500_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/226b9a8a5b80/10928_2016_9500_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/f4347b132b0a/10928_2016_9500_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/8b229199d61e/10928_2016_9500_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/9ae5d521f964/10928_2016_9500_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/b5e8d1c838ea/10928_2016_9500_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/09faff696422/10928_2016_9500_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/e8a36de97cc5/10928_2016_9500_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/226b9a8a5b80/10928_2016_9500_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/f4347b132b0a/10928_2016_9500_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/8b229199d61e/10928_2016_9500_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/5306145/9ae5d521f964/10928_2016_9500_Fig7_HTML.jpg

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