Literature DB >> 9169076

Physiologically based pharmacokinetic modeling of a ternary mixture of alkyl benzenes in rats and humans.

R Tardif1, G Charest-Tardif, J Brodeur, K Krishnan.   

Abstract

The objective of the present study was to develop a physiologically based pharmacokinetic (PBPK) model for a ternary mixture of alkyl benzenes [toluene (TOL), m-xylene (XYL), and ethylbenzene (EBZ)] in rats and humans. The approach involved the development of the mixture PBPK model in the rat and extrapolation to humans by substituting rat physiological parameters and blood:air partition coefficients in the model with those of humans, scaling maximal velocity for metabolism on the basis of body weight0.75 and keeping all other model parameters species-invariant. The development of the PBPK model for the ternary mixture in the rat was accomplished by initially validating or refining the existing PBPK models for TOL, XYL, and EBZ and linking the individual chemical models via the hepatic metabolism term. Accordingly, the Michaelis-Menten equation for each solvent was modified to test four possible mechanisms of metabolic interaction (i.e., no interaction, competitive inhibition, noncompetitive inhibition, and uncompetitive inhibition). The metabolic inhibition constant (Ki) for each binary pair of alkyl benzenes was estimated by fitting the binary chemical PBPK model simulations to previously published data on blood concentrations of TOL, XYL, and EBZ in rats exposed for 4 hr to a binary combination of 100 or 200 ppm of each of these solvents. Competitive metabolic inhibition appeared to be the most plausible mechanism of interaction at relevant exposure concentrations for all binary mixtures of alkyl benzenes in the rat (Ki,TOL-XYL = 0.17; Ki,TOL-EBZ = 0.79; Ki,XYL-TOL = 0.77; Ki,XYL-EBZ = 1.50; Ki,EBZ-TOL = 0.33; Ki,EBZ-XYL = 0.23 mg/L). Incorporating the Ki values obtained with the binary chemical mixtures, the PBPK model for the ternary mixture simulated adequately the time course of the venous blood concentrations of TOL, XYL, and EBZ in rats exposed to a mixture containing 100 ppm each of these solvents. Following the validation of the ternary mixture model in the rat, it was scaled to predict the kinetics of TOL, XYL, and EBZ in blood and alveolar air of human volunteers exposed for 7 hr to a combination of 17, 33, and 33 ppm, respectively, of these solvents. Model simulations and experimental data obtained in humans indicated that exposure to atmospheric concentrations of TOL, XYL, and EBZ that remain within the permissible concentrations for a mixture would not result in biologically significant modifications of their pharmacokinetics. Overall, this study demonstrates the utility of PBPK models in the prediction of the kinetics of components of chemical mixtures, by accounting for mechanisms of binary chemical interactions.

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Year:  1997        PMID: 9169076     DOI: 10.1006/taap.1996.8096

Source DB:  PubMed          Journal:  Toxicol Appl Pharmacol        ISSN: 0041-008X            Impact factor:   4.219


  22 in total

1.  Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling.

Authors:  G Truchon; R Tardif; G Charest-Tardif; A de Batz; P O Droz
Journal:  Int Arch Occup Environ Health       Date:  2012-03-13       Impact factor: 3.015

2.  Drug-drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 1: comparison of uniresponse and multiresponse designs using PopDes.

Authors:  Marylore Chenel; François Bouzom; Leon Aarons; Kayode Ogungbenro
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3.  Predictions of metabolic drug-drug interactions using physiologically based modelling: Two cytochrome P450 3A4 substrates coadministered with ketoconazole or verapamil.

Authors:  Nathalie Perdaems; Helene Blasco; Cedric Vinson; Marylore Chenel; Sarah Whalley; Fanny Cazade; François Bouzom
Journal:  Clin Pharmacokinet       Date:  2010-04       Impact factor: 6.447

4.  Exploring Mechanistic Toxicity of Mixtures Using PBPK Modeling and Computational Systems Biology.

Authors:  Patricia Ruiz; Claude Emond; Evad D McLanahan; Shivanjali Joshi-Barr; Moiz Mumtaz
Journal:  Toxicol Sci       Date:  2020-03-01       Impact factor: 4.849

5.  Global optimization of the Michaelis-Menten parameters using physiologically-based pharmacokinetic (PBPK) modeling and chloroform vapor uptake data in F344 rats.

Authors:  Marina V Evans; Christopher R Eklund; David N Williams; Yusupha M Sey; Jane Ellen Simmons
Journal:  Inhal Toxicol       Date:  2020-04-02       Impact factor: 2.724

6.  Visualization-based analysis for a mixed-inhibition binary PBPK model: determination of inhibition mechanism.

Authors:  Kristin K Isaacs; Marina V Evans; Thomas R Harris
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-06       Impact factor: 2.745

7.  Joint action and lethal levels of toluene, ethylbenzene, and xylene on midge (Chironomus plumosus) larvae.

Authors:  Xuefeng Li; Qixing Zhou; Yi Luo; Guang Yang; Tong Zhou
Journal:  Environ Sci Pollut Res Int       Date:  2012-11-28       Impact factor: 4.223

Review 8.  Considering the cumulative risk of mixtures of chemicals - a challenge for policy makers.

Authors:  Denis A Sarigiannis; Ute Hansen
Journal:  Environ Health       Date:  2012-06-28       Impact factor: 5.984

Review 9.  Evaluating pharmacokinetic and pharmacodynamic interactions with computational models in supporting cumulative risk assessment.

Authors:  Yu-Mei Tan; Harvey Clewell; Jerry Campbell; Melvin Andersen
Journal:  Int J Environ Res Public Health       Date:  2011-05-19       Impact factor: 3.390

10.  A mechanistic modeling framework for predicting metabolic interactions in complex mixtures.

Authors:  Shu Cheng; Frederic Y Bois
Journal:  Environ Health Perspect       Date:  2011-08-11       Impact factor: 9.031

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