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An integrated QSAR-PBPK modelling approach for predicting the inhalation toxicokinetics of mixtures of volatile organic chemicals in the rat

机译:一种集成的QSAR-PBPK建模方法,用于预测大鼠中挥发性有机化合物混合物的吸入毒物动力学

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The objective of this study was to predict the inhalation toxicokinetics of chemicals in mixtures using an integrated QSAR-PBPK modelling approach. The approach involved: (1) the determination of partition coefficients as well as V max and Km based solely on chemical structure for 53 volatile organic compounds, according to the group contribution approach; and (2) using the QSAR-driven coefficients as input in interaction-based PBPK models in the rat to predict the pharmacokinetics of chemicals in mixtures of up to 10 components (benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene, and styrene). QSAR-estimated values of V max varied compared with experimental results by a factor of three for 43 out of 53 studied volatile organic compounds (VOCs). K m values were within a factor of three compared with experimental values for 43 out of 53 VOCs. Cross-validation performed as a ratio of predicted residual sum of squares and sum of squares of the response value indicates a value of 0.108 for V max and 0.208 for K m. The integration of QSARs for partition coefficients, V max and K m, as well as setting the K m equal to K i (metabolic inhibition constant) within the mixture PBPK model allowed to generate simulations of the inhalation pharmacokinetics of benzene, toluene, m-xylene, o-xylene, p-xylene, ethylbenzene, dichloromethane, trichloroethylene, tetrachloroethylene and styrene in various mixtures. Overall, the present study indicates the potential usefulness of the QSAR-PBPK modelling approach to provide first-cut evaluations of the kinetics of chemicals in mixtures of increasing complexity, on the basis of chemical structure.View full textDownload full textKeywordsmixtures, PBPK model, pharmacokinetics, QSAR-PBPK model, toxicokineticsRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/1062936X.2010.548350
机译:这项研究的目的是使用集成的QSAR-PBPK建模方法预测混合物中化学物质的吸入毒性动力学。该方法涉及:(1)根据基团贡献,仅根据53种挥发性有机化合物的化学结构确定分配系数以及V max 和K m 方法(2)使用QSAR驱动的系数作为大鼠基于相互作用的PBPK模型的输入,以预测多达10种组分(苯,甲苯,间二甲苯,邻二甲苯,对二甲苯)的混合物中化学药品的药代动力学,乙苯,二氯甲烷,三氯乙烯,四氯乙烯和苯乙烯)。在研究的53种挥发性有机化合物(VOC)中,有43种的QSAR估计值V max 与实验结果相比变化了3倍。与53种挥发性有机化合物中的43种的实验值相比,K m 值在三分之一以内。以预测的残差平方和与响应值的平方和之比进行交叉验证时,V max 的值为0.108,K m 的值为0.208。 QSAR对分配系数V max 和K m 的积分,以及将K m 设置为等于K i <混合物PBPK模型中的(代谢抑制常数)可以模拟各种混合物中苯,甲苯,间二甲苯,邻二甲苯,对二甲苯,乙苯,二氯甲烷,三氯乙烯,四氯乙烯和苯乙烯的吸入药代动力学。总体而言,本研究表明QSAR-PBPK建模方法在基于化学结构的基础上提供对复杂性不断增加的混合物动力学的第一手评估的潜在有用性。查看全文下载全文关键词混合物,PBPK模型,药代动力学,QSAR-PBPK模型,毒物动力学相关变量var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,service_compact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,更多”,发布:“ ra -4dff56cd6bb1830b“};添加到候选列表链接永久链接http://dx.doi.org/10.1080/1062936X.2010.548350

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