Physiological modeling of the toxicokinetic interactions in a quaternary mixture of aromatic hydrocarbons.

The available data on binary interactions are yet to be considered within the context of mixture risk assessments because of our inability to predict the effect of a third or fourth chemical in the mixture on the interacting binary pairs. Physiologically based toxicokinetic (PBTK) models represent a framework that can be potentially used for predicting the impact of multiple interactions on component kinetics at any level of complexity. The objective of this study was to develop and validate an interaction-based PBTK model for simulating the toxicokinetics of the components of a quaternary mixture of aromatic hydrocarbons [benzene (B), toluene (T), ethylbenzene (E), m-xylene (X)] in the rat. The methodology consisted of: (1) obtaining and refining the validated individual chemical PBTK models from the literature, (2) interconnecting all individual chemical PBTK models at the level of liver on the basis of the mechanism of binary chemical interactions (e.g., competitive, noncompetitive, or uncompetitive metabolic inhibition), and (3) comparing the a priori predictions of the interaction-based model to corresponding experimental data on venous blood concentrations of B, T, E, and X during mixture exposures. The analysis of blood kinetics data from inhalation exposures (4 h, 50-200 ppm each) of rats to all binary combinations of B, T, E, and X was suggestive of competitive metabolic inhibition as the plausible interaction mechanism. The metabolic inhibition constant (K(i)) for each binary combination was quantified and incorporated within the mixture PBTK model. The binary interaction-based PBTK model predicted adequately the inhalation toxicokinetics of all four components in rats following exposure to mixtures of BTEX (50 ppm each of B, T, E, and X, 4 h; 100 ppm each of B, T, E and X, 4 h; 100 ppm B + 50 ppm each of T, E, and X, 4 h). The results of the present study suggest that data on interactions at the binary level alone are required and sufficient for predicting the kinetics of components in complex mixtures.