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首页> 外文期刊>Frontiers in Pharmacology >The application of global sensitivity analysis in the development of a physiologically based pharmacokinetic model for m-xylene and ethanol co-exposure in humans
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The application of global sensitivity analysis in the development of a physiologically based pharmacokinetic model for m-xylene and ethanol co-exposure in humans

机译:全局敏感性分析在人体-二甲苯和乙醇共同暴露的生理学药代动力学模型开发中的应用

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Global sensitivity analysis (SA) was used during the development phase of a binary chemical physiologically based pharmacokinetic (PBPK) model used for the analysis of m -xylene and ethanol co-exposure in humans. SA was used to identify those parameters which had the most significant impact on variability of venous blood and exhaled m -xylene and urinary excretion of the major metabolite of m -xylene metabolism, 3-methyl hippuric acid. This analysis informed the selection of parameters for estimation/calibration by fitting to measured biological monitoring (BM) data in a Bayesian framework using Markov chain Monte Carlo (MCMC) simulation. Data generated in controlled human studies were shown to be useful for investigating the structure and quantitative outputs of PBPK models as well as the biological plausibility and variability of parameters for which measured values were not available. This approach ensured that a priori knowledge in the form of prior distributions was ascribed only to those parameters that were identified as having the greatest impact on variability. This is an efficient approach which helps reduce computational cost.
机译:在基于二元化学生理学的药代动力学(PBPK)模型的开发阶段,使用了全球敏感性分析(SA),该模型用于分析人体内的二甲苯和乙醇共同暴露。 SA用于确定对静脉血和呼出的二甲苯的变异性以及间二甲苯代谢的主要代谢产物3-甲基马尿酸的尿排泄影响最大的那些参数。该分析通过使用马尔可夫链蒙特卡洛(MCMC)模拟拟合贝叶斯框架中的测得的生物监测(BM)数据,为评估/校准参数选择提供了依据。研究表明,在受控人体研究中产生的数据可用于研究PBPK模型的结构和定量输出,以及无法获得测量值的参数的生物学真实性和可变性。这种方法确保了先验分布形式的先验知识仅归因于那些被认为对变异性影响最大的参数。这是一种有助于降低计算成本的有效方法。

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