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14th International Workshop on Quantitative Structure-Activity Relationships in Environmental and Health Sciences (QSAR2010) - Part 2

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

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Pages 107-128 | Received 22 Jul 2010, Accepted 21 Oct 2010, Published online: 09 Mar 2011
 

Abstract

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.

Acknowledgements

Grants from NSERC-Canada (Operating grants) and ANSES (EST-2007-85) are acknowledged.

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