title: Physiologically based pharmacokinetic modeling of benzene metabolism in mice through extrapolation from in vitro to in vivo.
abstract: Benzene (C6H6) is a highly flammable, colorless liquid. Ubiquitous exposures result from its presence in gasoline vapors, cigarette smoke, and industrial processes. Benzene increases the incidence of leukemia in humans when they are exposed to high doses for extended periods; however, leukemia risks in humans at low exposures are uncertain. The exposure-dose-response relationship of benzene in humans is expected to be nonlinear because benzene undergoes a series of metabolic transformations, detoxifying and activating, in the liver, resulting in multiple metabolites that exert toxic effects on the bone marrow. We developed a physiologically based pharmacokinetic model for the uptake and elimination of benzene in mice to relate the concentration of inhaled and orally administered benzene to the tissue doses of benzene and its key metabolites, benzene oxide, phe nol, and hydroquinone. As many parameter values as possible were taken from the literature; in particular, metabolic parameters obtained from in vitro studies with mouse liver were used since comparable parameters are also available for humans. Parameters estimated by fitting the model to published data were first-order rate constants for pathways lacking in vitro data and the concentrations of microsomal and cytosolic protein, which effectively alter overall enzyme activity. The model was constrained by using the in vitro metabolic parameters (maximum velocities, first-order rate constants, and saturation parameters), and data from multiple laboratories and experiments were used. Despite these constraints and sources of variability, the model simulations matched the data reasonably well in most cases, showing that in vitro metabolic constants can be successfully extrapolated to predict in vivo data for benzene metabolism and dosimetry. Therefore in vitro metabolic constants for humans can subsequently be extrapolated to predict the dosimetry of benzene and its metabolites in humans. This will allow us to better estimate the risks of adverse effects from low-level benzene exposures.
authors: CIIT Centers for Health Research, Research Triangle Park, North Carolina 27709-2137, USA.
authors: C E
authors: CE
authors: Cole
authors: H T
authors: HT
authors: Tran
authors: P M
authors: PM
authors: Schlosser
mesh_terms: D000280:Administration, Inhalation; D000465:Algorithms; D000818:Animals; D001554:Benzene / Q000737:chemistry / Q000378:metabolism* / Q000493:pharmacokinetics*; D001555:Benzene Derivatives / Q000737:chemistry / Q000378:metabolism / Q000493:pharmacokinetics; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D051379:Mice; D008954:Models, Biological; D018570:Risk Assessment
chemical_list: D001555:Benzene Derivatives; D001554:Benzene