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Benzene, a ubiquitous environmental pollutant, is known to cause leukemia and aplastic anemia in humans and hematotoxicity and myelotoxicity in rodents. Toxicity is thought to be exerted through oxidative metabolites formed in the liver, primarily via pathways mediated by cytochrome P450 2E1 (CYP2E1). Phenol, hydroquinone and trans-trans-muconaldehyde have all been hypothesized to be involved in benzene-induced toxicity. Recent reports indicate that benzene oxide is produced in vitro and in vivo and may be sufficiently stable to reach the bone marrow. Our goal was to improve existing mathematical models of microsomal benzene metabolism by including time course data for benzene oxide, by obtaining better parameter estimates and by determining if enzymes other than CYP2E1 are involved. Microsomes from male B6C3F1 mice and F344 rats were incubated with [(14)C]benzene (14 microM), [(14)C]phenol (303 microM) and [(14)C]hydroquinone (8 microM). Benzene and phenol were also incubated with mouse microsomes in the presence of trans-dichloroethylene, a CYP2E1 inhibitor, and benzene was incubated with trichloropropene oxide, an epoxide hydrolase inhibitor. These experiments did not indicate significant contributions of enzymes other than CYP2E1. Mathematical model parameters were fitted to rodent data and the model was validated by predicting human data. Model simulations predicted the qualitative behavior of three human time course data sets and explained up to 81% of the total variation in data from incubations of benzene for 16 min with microsomes from nine human individuals. While model predictions did deviate systematically from the data for benzene oxide and trihydroxybenzene, overall model performance in predicting the human data was good. The model should be useful in quantifying human risk due to benzene exposure and explicitly accounts for interindividual variation in CYP2E1 activity.

In vitro and in vivo butadiene (BD) metabolism data from laboratory animals were integrated into a rodent physiologically based pharmacokinetic (PBPK) model with flow- and diffusion-limited compartments. The resulting model describes experimental data from multiple sources under scenarios such as closed chamber inhalation and nose-only flow-through inhalation exposures. Incorporation of diurnal glutathione (GSH) variation allows accurate simulation of GSH changes observed in air control nose-only exposures and BD exposures. An isolated tissue model based on rate parameters determined in vitro predicts the decrease in epoxide concentrations in intact animals during the time lag between exsanguination and tissue removal for tissues capable of epoxide biotransformation, providing a better indication of in vivo dosimetry. Further refinements of the model are required relative to model predictions of an important BD metabolite, diepoxybutane.