title: Physiologically-based pharmacokinetic modeling of benzene in humans: a Bayesian approach.
abstract: Benzene is myelotoxic and leukemogenic in humans exposed at high doses (>1 ppm, more definitely above 10 ppm) for extended periods. However, leukemia risks at lower exposures are uncertain. Benzene occurs widely in the work environment and also indoor air, but mostly below 1 ppm, so assessing the leukemia risks at these low concentrations is important. Here, we describe a human physiologically-based pharmacokinetic (PBPK) model that quantifies tissue doses of benzene and its key metabolites, benzene oxide, phenol, and hydroquinone after inhalation and oral exposures. The model was integrated into a statistical framework that acknowledges sources of variation due to inherent intra- and interindividual variation, measurement error, and other data collection issues. A primary contribution of this work is the estimation of population distributions of key PBPK model parameters. We hypothesized that observed interindividual variability in the dosimetry of benzene and its metabolites resulted primarily from known or estimated variability in key metabolic parameters and that a statistical PBPK model that explicitly included variability in only those metabolic parameters would sufficiently describe the observed variability. We then identified parameter distributions for the PBPK model to characterize observed variability through the use of Markov chain Monte Carlo analysis applied to two data sets. The identified parameter distributions described most of the observed variability, but variability in physiological parameters such as organ weights may also be helpful to faithfully predict the observed human-population variability in benzene dosimetry.
authors.affiliation: Department of Mathematics and Center for Research in Scientific Computation, North Carolina State University, Raleigh, USA.
authors.forename: Karen
authors.initials: K
authors.lastname: Yokley
authors.forename: Hien T
authors.initials: HT
authors.lastname: Tran
authors.forename: Kaija
authors.initials: K
authors.lastname: Pekari
authors.forename: Stephen
authors.initials: S
authors.lastname: Rappaport
authors.forename: Vesa
authors.initials: V
authors.lastname: Riihimaki
authors.forename: Nat
authors.initials: N
authors.lastname: Rothman
authors.forename: Suramya
authors.initials: S
authors.lastname: Waidyanatha
authors.forename: Paul M
authors.initials: PM
authors.lastname: Schlosser
mesh_terms: D000704:Analysis of Variance; D001499:Bayes Theorem; D001554:Benzene / Q000008:administration & dosage / Q000493:pharmacokinetics* / Q000633:toxicity; D004785:Environmental Pollutants / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000633:toxicity; D006801:Humans; D007938:Leukemia / Q000209:etiology; D008390:Markov Chains; D008433:Mathematics; D008954:Models, Biological; D009010:Monte Carlo Method; D018570:Risk Assessment; D012680:Sensitivity and Specificity
chemical_list: D004785:Environmental Pollutants; D001554:Benzene