Validation of a physiological modeling framework for simulating the toxicokinetics of chemicals in mixtures

The objective of this study was to investigate the usefulness of a physiologically based toxicokinetic (PBTK) modeling framework for simulating the kinetics of chemicals in mixtures of varying complexities and composition. The approach involved the simulation of the kinetics of components in two situations: (i) when one of the mixture components was substituted with another (i.e., benzene in the benzene (B)-toluene (T)-ethyl benzene (E)-m-xylene (X) mixture was substituted with dichloromethane (D)), and (ii) when another chemical was added to the existing four-chemical mixture model (i.e., when D was added to the existing BTEX mixture model). In both cases, differing compositions of mixtures were used to obtain simulations and to generate experimental data on kinetics for validation purposes. Since the quantitative and qualitative mechanisms of interaction among B, T, E, and X have already been established, the mechanisms of binary interactions between D and the BTEX components (e.g., competitive, noncompetitive, or uncompetitive metabolic inhibition) were investigated in the present study. The analysis of rat blood kinetic data (4-h inhalation exposures, 50-200 ppm each) to all binary combinations (D-B, D-T, D-E, and D-X) investigated in the present study was suggestive of competitive metabolic inhibition as the plausible interaction mechanism. By incorporating the newly estimated values of metabolic inhibition constant (K(i)) for each of these binary combinations within the five-chemical PBTK model (i.e., for the DBTEX mixture), the model adequately predicted the venous blood kinetics of chemicals in rats following a 4-h inhalation exposure to various mixtures (mixture 1:100 ppm of D and 50 ppm each of T, E, and X; mixture 2: 100 ppm each of D, T, E, and X; mixture 3: 100 ppm of D and 50 ppm each of B, T, E, and X; mixture 4: 100 ppm each of D, B, T, E, and X). The results of the present study suggest that the PBTK model framework is useful for conducting extrapolations of the kinetics of chemicals from one mixture to another differing in complexity and composition, based on mechanistic considerations of interactions elucidated at the binary level.