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GastroPlus™ 房室模型两阶段全局灵敏度分析框架。

A framework for 2-stage global sensitivity analysis of GastroPlus™ compartmental models.

机构信息

Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, 98 Brett Road, Piscataway, NJ, 08854, USA.

Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ, 08854, USA.

出版信息

J Pharmacokinet Pharmacodyn. 2018 Apr;45(2):309-327. doi: 10.1007/s10928-018-9573-1. Epub 2018 Feb 8.

Abstract

Parameter sensitivity and uncertainty analysis for physiologically based pharmacokinetic (PBPK) models are becoming an important consideration for regulatory submissions, requiring further evaluation to establish the need for global sensitivity analysis. To demonstrate the benefits of an extensive analysis, global sensitivity was implemented for the GastroPlus™ model, a well-known commercially available platform, using four example drugs: acetaminophen, risperidone, atenolol, and furosemide. The capabilities of GastroPlus were expanded by developing an integrated framework to automate the GastroPlus graphical user interface with AutoIt and for execution of the sensitivity analysis in MATLAB. Global sensitivity analysis was performed in two stages using the Morris method to screen over 50 parameters for significant factors followed by quantitative assessment of variability using Sobol's sensitivity analysis. The 2-staged approach significantly reduced computational cost for the larger model without sacrificing interpretation of model behavior, showing that the sensitivity results were well aligned with the biopharmaceutical classification system. Both methods detected nonlinearities and parameter interactions that would have otherwise been missed by local approaches. Future work includes further exploration of how the input domain influences the calculated global sensitivity measures as well as extending the framework to consider a whole-body PBPK model.

摘要

基于生理的药代动力学(PBPK)模型的参数敏感性和不确定性分析对于监管提交变得越来越重要,需要进一步评估以确定是否需要进行全局敏感性分析。为了展示广泛分析的好处,使用 Morris 方法对 GastroPlus™模型(一种知名的商业可用平台)进行了全局敏感性分析,该模型使用了四种示例药物:对乙酰氨基酚、利培酮、阿替洛尔和呋塞米。通过开发一个集成框架来自动执行 GastroPlus 的图形用户界面,同时在 MATLAB 中执行敏感性分析,扩展了 GastroPlus 的功能。使用 Morris 方法对超过 50 个参数进行了全局敏感性分析,以筛选出显著因素,然后使用 Sobol 敏感性分析对变异性进行定量评估,分两个阶段进行了全局敏感性分析。这种两阶段方法大大降低了较大模型的计算成本,而不会牺牲对模型行为的解释,表明敏感性结果与生物制药分类系统很好地吻合。这两种方法都检测到了非线性和参数相互作用,如果使用局部方法,这些相互作用可能会被忽略。未来的工作包括进一步探索输入域如何影响计算的全局敏感性度量,以及扩展框架以考虑整个身体的 PBPK 模型。

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