A physiologically-based algorithm for predicting internal dose of inhaled toluene: Applications for high dose to low dose and rodent to human extrapolations

The objective of this study was to develop a physiologically-based algorithm for predicting the steady-state internal dose of inhaled volatile organic chemicals (VOCs) in rats and humans at various exposure concentrations, using toluene as the model chemical. This was accomplished by the systematic development of the solution to the set of equations constituting pulmonary uptake and metabolic clearance, including the consideration of dose-dependent change in the free concentration of chemical at the metabolizing site (liver). The resulting algorithm, based on critical determinants of the internal dose during chronic exposure to VOCs (i.e., alveolar ventilation rate, blood flow rate to liver, blood: air partition coefficient, maximal velocity of metabolism, Michaelis affinity constant and free concentration of chemical at the metabolizing site) provides predictions of dose metrics (i.e., arterial blood concentration and rate of amount metabolized) identical to those of the full-fledged PBPK models. The algorithm was then applied to conduct high dose to low dose and rodent to human extrapolations of internal dose of inhaled toluene. The physiologically-based algorithm, developed in this study, for the first time facilitates the direct computation of steady-state internal dose for a variety of exposure concentrations of toluene, by consistently accounting for the non-linear processes.