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Updated: Oct 4, 2025

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
Published on: April 12, 2019
A physiologically based kinetic modeling of ethyl tert-butyl ether in humans-An illustrative application of
Saori Watanabe-Matsumoto1, Kikuo Yoshida1, Yuriko Meiseki1
1Division of Risk Assessment, Center for Biological Safety Research, National Institute of Health Sciences.
Abstract:
Although physiologically based kinetic (PBK) modeling is informative for the risk assessment of industrial chemicals, chemical-specific input values for partition coefficients and metabolic parameters, including Vmax and Km are mostly unavailable; however, in silico methods, such as quantitative structure-property relationship (QSPR) could fill the absence. To assess the PBK model validity using necessary toxicokinetic (TK) parameters predicted by QSPR, the PBK model of ethyl tert-butyl ether (ETBE) as a model substance was constructed, in which the values of the partition coefficients, Vmax, and Km of ETBE were predicted using those of the related chemicals previously reported in the literature, and toxicokinetics of inhaled ETBE were stochastically estimated using the Monte Carlo simulation. The calculated ETBE concentrations in venous blood were comparable to the measured values in humans, implying that the reproducibility of ETBE toxicokinetics in humans was established in this PBK model. The Monte Carlo simulation was used to conduct uncertainty and sensitivity analyses of the dose metrics in terms of maximum blood concentration (Cmax) and area under the blood concentration-time curve (AUC) and the estimated Cmax and AUC were highly and moderately reliable, respectively. Conclusively, the PBK model validity combined with in silico methods of QSPR was demonstrated in an ETBE model substance. QSPR-PBK modeling coupled with the Monte Carlo simulation is effective for estimating chemical toxicokinetics for which input values are unavailable and for evaluating the estimation validity.
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