Formaldehyde inhalation at 6 ppm and above causes nasal squamous cell carcinoma (SCC) in F344 rats. The human health implications of this effect are of significant interest since human exposure to environmental formaldehyde is widespread, though at lower concentrations than those that cause cancer in rats. In this article, which is part of a larger effort to predict the human cancer risks of inhaled formaldehyde, we describe biologically motivated quantitative modeling of the exposure-tumor response continuum in the rat. An anatomically realistic, three-dimensional fluid dynamics model of the F344 rat nasal airways was used to predict site-specific flux of formaldehyde from inhaled air into tissue, since both SCC and preneoplastic lesions develop in a characteristic site-specific pattern. Flux into tissue was used as a dose metric for two modes of action, direct mutagenicity and cytolethality-regenerative cellular proliferation (CRCP), which in turn were linked to key parameters of a two-stage clonal growth model. The direct mutagenicity mode of action was represented by a low dose linear dose-response model of DNA-protein cross-link (DPX) formation. An empirical J-shaped dose-response model and a threshold model fit to the empirical data were used for CRCP. In the clonal growth model, the probability of mutation per cell generation was a function of the tissue concentration of DPX while the rate of cell division was calculated from the CRCP data. Maximum likelihood methods were used to estimate parameter values. Survivor (a nontumor outcome) and tumor data for controls from the National Toxicology Program database and from two formaldehyde inhalation bioassays were used for likelihood calculations. The J-shaped dose-response for CRCP provided a better description of the SCC data than did the threshold model. Sensitivity analyses indicated that the rodent tumor response is due to the CRCP mode of action, with the directly mutagenic pathway having little, if any, influence. When evaluated in light of modeling and database uncertainties, particularly the specification of the clonal growth model and the dose-response data for CRCP, this work provides suggestive though not definitive evidence for a J-shaped dose-response for formaldehyde-mediated nasal SCC in the F344 rat.

Formaldehyde-induced nasal squamous cell carcinomas in rats and squamous metaplasia in rats and rhesus monkeys occur in specific regions of the nose with species-specific distribution patterns. Experimental approaches addressing local differences in formaldehyde uptake patterns and dose are limited by the resolution of dissection techniques used to obtain tissue samples and the rapid metabolism of absorbed formaldehyde in the nasal mucosa. Anatomically accurate, 3-dimensional computational fluid dynamics models of F344 rat, rhesus monkey, and human nasal passages were used to estimate and compare regional inhaled formaldehyde uptake patterns predicted among these species. Maximum flux values, averaged over a breath, in nonsquamous epithelium were estimated to be 2620, 4492, and 2082 pmol/(mm(2)-h-ppm) in the rat, monkey, and human respectively. Flux values predicted in sites where cell proliferation rates were measured as similar in rats and monkeys were also similar, as were fluxes predicted in a region of high tumor incidence in the rat nose and the anterior portion of the human nose. Regional formaldehyde flux estimates are directly applicable to clonal growth modeling of formaldehyde carcinogenesis to help reduce uncertainty in human cancer risk estimates.

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Physiologically based pharmacokinetic (PBPK) models are sophisticated dosimetry models that offer great flexibility in modeling exposure scenarios for which there are limited data. This is particularly of relevance to assessing human exposure to environmental toxicants, which often requires a number of extrapolations across species, route, or dose levels. The continued development of PBPK models ensures that regulatory agencies will increasingly experience the need to evaluate available models for their application in risk assessment. To date, there are few published criteria or well-defined standards for evaluating these models. Herein, important considerations for evaluating such models are described. The evaluation of PBPK models intended for risk assessment applications should include a consideration of: model purpose, model structure, mathematical representation, parameter estimation, computer implementation, predictive capacity and statistical analyses. Model purpose and structure require qualitative checks on the biological plausibility of a model. Mathematical representation, parameter estimation, computer implementation involve an assessment of the coding of the model, as well as the selection and justification of the physical, physicochemical and biochemical parameters chosen to represent a biological organism. Finally, the predictive capacity and sensitivity, variability and uncertainty of the model are analysed so that the applicability of a model for risk assessment can be determined. Published in 2007 by John Wiley & Sons, Ltd.

Low levels of benzene from sources including cigarette smoke and automobile emissions are ubiquitous in the environment. Since the toxicity of benzene probably results from oxidative metabolites, an understanding of the profile of biotransformation of low levels of benzene is critical in making a valid risk assessment. To that end, we have investigated metabolism of a low concentration of [14C]benzene (3.4 microM) by microsomes from human, mouse and rat liver. The extent of phase I benzene metabolism by microsomal preparations from 10 human liver samples and single microsomal preparations from both mice and rats was then related to measured activities of cytochrome P450 (CYP) 2E1. Measured CYP 2E1 activities, as determined by hydroxylation of p-nitrophenol, varied 13-fold (0.253-3.266 nmol/min/mg) for human samples. The fraction of benzene metabolized in 16 min ranged from 10% to 59%. Also at 16 min, significant amounts of oxidative metabolites were formed. Phenol was the main metabolite formed by all but two human microsomal preparations. In those samples, both of which had high CYP 2E1 activity, hydroquinone was the major metabolite formed. Both hydroquinone and catechol formation showed a direct correlation with CYP 2E1 activity over the range of activities present. A simulation model was developed based on a mechanism of competitive inhibition between benzene and its oxidized metabolites, and was fit to time-course data for three human liver preparations. Model calculations for initial rates of benzene metabolism ranging from 0.344 to 4.442 nmol/mg/min are directly proportional to measured CYP 2E1 activities. The model predicted the dependence of benzene metabolism on the measured CYP 2E1 activity in human liver samples, as well as in mouse and rat liver samples. These results suggest that differences in measured hepatic CYP 2E1 activity may be a major factor contributing to both interindividual and interspecies variations in hepatic metabolism of benzene. Validation of this system in vivo should lead to more accurate assessment of the risk of benzene's toxicity following low-level exposure.

Interspecies extrapolations of tissue dose and tumor response have been a significant source of uncertainty in formaldehyde cancer risk assessment. The ability to account for species-specific variation of dose within the nasal passages would reduce this uncertainty. Three-dimensional, anatomically realistic, computational fluid dynamics (CFD) models of nasal airflow and formaldehyde gas transport in the F344 rat, rhesus monkey, and human were used to predict local patterns of wall mass flux (pmol/[mm(2)-h-ppm]). The nasal surface of each species was partitioned by flux into smaller regions (flux bins), each characterized by surface area and an average flux value. Rat and monkey flux bins were predicted for steady-state inspiratory airflow rates corresponding to the estimated minute volume for each species. Human flux bins were predicted for steady-state inspiratory airflow at 7.4, 15, 18, 25.8, 31.8, and 37 l/min and were extrapolated to 46 and 50 l/min. Flux values higher than half the maximum flux value (flux median) were predicted for nearly 20% of human nasal surfaces at 15 l/min, whereas only 5% of rat and less than 1% of monkey nasal surfaces were associated with fluxes higher than flux medians at 0.576 l/min and 4.8 l/min, respectively. Human nasal flux patterns shifted distally and uptake percentage decreased as inspiratory flow rate increased. Flux binning captures anatomical effects on flux and is thereby a basis for describing the effects of anatomy and airflow on local tissue disposition and distributions of tissue response. Formaldehyde risk models that incorporate flux binning derived from anatomically realistic CFD models will have significantly reduced uncertainty compared with risk estimates based on default methods.

Benzene, an important industrial solvent and constituent of unleaded gasoline, causes leukemia and aplastic anemia in humans. Mice are more sensitive than rats to benzene toxicity, though neither species has been shown to respond consistently with benzene-induced leukemia. Benzene biotransformation in liver to phenol, hydroquinone, catechol and/or muconaldehyde is thought to be necessary for its hematotoxicity and/or genotoxicity. Our goal is to develop a mathematical simulation model capable of describing the pathways and kinetics of benzene metabolism by rat and mouse liver microsomes and to assess the role of species metabolic differences in species sensitivity. Microsomes were incubated with 4 microM [U-14C]-benzene or 4 microM [U-14C]phenol. Metabolite production was quantified by extraction into ethyl acetate, HPLC separation and liquid scintillation spectroscopy. After 45 min, mouse liver microsomes converted 20% of the benzene to phenol, 31% to hydroquinone and 2% to catechol. Rat liver microsomes converted 23% of benzene to phenol, 8% to hydroquinone and 0.5% to catechol. Production of hydroquinone and catechol continued for 90 min for mouse liver microsomes, while production by rat liver microsomes had virtually ceased by 90 min. Muconic acid production by mouse liver microsomes was < 0.2% and < 0.04% from benzene and phenol respectively after 90 min. A quantitative simulation model was constructed to describe the in vitro metabolism of benzene, incorporating the reaction sequences: benzene-->phenol-->catechol-->trihydroxybenzene and phenol-->hydroquinone-->trihydroxybenzene. In the model, all of the reaction steps are assumed to be catalyzed by the same enzyme(s), cytochrome(s) P450, and benzene, phenol, hydroquinone and catechol in solution are all assumed to compete, through reversible binding, for the same reaction site(s) on cytochrome(s) P450. The simulation model accurately described both the benzene and phenol kinetic data, supporting this proposed mechanism. In particular, this model suggests that the observed inhibition of benzene on phenol metabolism, and of phenol on benzene metabolism, occurs through competition for a common reaction site, which can also bind catechol and hydroquinone.

This study presents a nonlinear system of delay differential equations to model the concentrations of five hormones important for regulation and maintenance of the menstrual cycle. Linear model components for the ovaries and pituitary were previously analyzed and reported separately. Results for the integrated model are now presented here. This model predicts serum levels of ovarian and pituitary hormones which agree with data in the literature for normally cycling women. In addition, the model indicates the existence and stability of an abnormal cycle. Hence, the model may be used to simulate the effects of external hormone therapies on abnormally cycling women as well as the effects of exogenous compounds on normally cycling women. Such simulations may be helpful in understanding the role of xenobiotics in fertility problems, in predicting successful hormone therapies, and for testing hormonal methods of birth control.