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PubMed2003

Physiological modeling of inhalation kinetics of octamethylcyclotetrasiloxane in humans during rest and exercise.

In a recent pharmacokinetic study, six human volunteers were exposed by inhalation to 10 ppm (14)C-D(4) for 1 h during alternating periods of rest and exercise. Octamethylcyclotetrasiloxane (D(4)) concentrations were determined in exhaled breath and blood. Total metabolite concentrations were estimated in blood, while the amounts of individual metabolites were measured in urine. Here, we use these data to develop a physiologically based pharmacokinetic (PBPK) model for D(4) in humans. Consistent with PBPK modeling efforts for D(4) in the rat, a conventional inhalation PBPK model assuming flow-limited tissue uptake failed to adequately describe these data. A refined model with sequestered D(4) in blood, diffusion-limited tissue uptake, and an explicit pathway for D(4) metabolism to short-chain linear siloxanes successfully described all data. Hepatic extraction in these volunteers, calculated from model parameters, was 0.65 to 0.8, i.e., hepatic clearance was nearly flow-limited. The decreased retention of inhaled D(4) seen in humans during periods of exercise was explained by altered ventilation/perfusion characteristics during exercise and a rapid approach to steady-state conditions. The urinary time course excretion of metabolites was consistent with a metabolic scheme in which sequential hydrolysis of linear siloxanes followed oxidative demethylation and ring opening. The unusual properties of D(4) (high lipophilicity coupled with high hepatic and exhalation clearance) lead to rapid decreases in free D(4) in blood. The success of D(4) PBPK models with a similar physiological structure in both humans and rats increases confidence in the utility of the model for predicting human tissue concentrations of D(4) and metabolites during inhalation exposures.

Adjuvants, Immunologic↗
PubMed2003

Tissue dosimetry expansion and cross-validation of rat and mouse physiologically based pharmacokinetic models for trichloroethylene.

Trichloroethylene (TCE), a volatile liquid used as a degreasing agent, is a common environmental pollutant. In 2001, the EPA published a draft risk assessment for TCE that incorporates dosimetry predictions of physiologically based pharmacokinetic (PBPK) models. The current modeling effort represents an expansion and extensive tissue dosimetry validation of rodent PBPK models for TCE. The pharmacokinetics of TCE in male Sprague-Dawley (S-D) rats were characterized (1) during and after inhalation exposure to 50 or 500 ppm TCE, (2) following administration of 8 mg/kg TCE PO, and (3) following intra-arterial injection of 8 mg/kg TCE. Blood and tissues (including liver, kidney, fat, skeletal muscle, heart, spleen, gastrointestinal tract, and brain) were collected at selected time-points from 5 min up to 24 h post initial exposure. The fat compartment was modified to be diffusion-limited to predict the observed slow release of TCE from the fat. The addition of a deep liver compartment was necessary to accurately predict the slower hepatic clearance of TCE for all three exposure routes. Simulations of liver concentrations following gavage of male B6C3F1 mice with 300-2000 mg/kg TCE were also improved with the addition of a deep liver compartment. Liver predictions were calibrated and validated using a cross-validation technique novel to PBPK modeling. Splitting of compartments did not significantly affect predictions of TCE concentrations in the liver, fat, or venous blood. This model expansion and validation increases both the utility and our confidence in the current use of rodent TCE PBPK models in human health risk assessment.

Adipose Tissue↗
PubMed2004

Physiologically based pharmacokinetic model for developmental exposures to TCDD in the rat.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a potent developmental toxicant in rodents, and these effects occur at exposures similar to background human body burdens. A physiologically based pharmacokinetic (PBPK) model can aid in quantitatively describing the relationship between exposure, dose, and response. The aim of this work was the development a PBPK model to describe the relationship between maternal TCDD exposure and fetal TCDD concentrations during critical windows of susceptibility in the rat. This PBPK model is a modification of an eight-compartment model that describes the adult female rat. The modified model reduces the compartments from eight to four maternal compartments (liver, fat, placenta and rest of the body). Activation of the placental compartment and a separate fetal compartment occurs during gestation. The systemic circulation connects the maternal compartments. The physiological and biochemical parameters were obtained from the literature. The model validation used experimental data from acute and subchronic exposures prior to and during gestation. The simulations predict the TCDD tissue concentrations of the maternal compartments within the standard deviation of the experimental data. The model overestimates the fetal concentrations by approximately a factor of two at low subchronic exposures, but does predict the fetal tissue concentrations within the range of the experimental data at the higher exposures. This model may provide a framework for the development of a human PBPK model to estimate fetal TCDD concentrations in human health risk assessments.

Animals↗
PubMed2006

An updated physiologically based pharmacokinetic model for hexachlorobenzene: incorporation of pathophysiological states following partial hepatectomy and hexachlorobenzene treatment.

Physiologically based pharmacokinetic (PBPK) modeling is generally used for describing xenobiotic disposition in animals and humans with normal physiological conditions. We describe here an updated PBPK model for hexachlorobenzene (HCB) in male F344 rats with the incorporation of pathophysiological conditions. Two more features contribute to the distinctness of this model from the earlier published versions. This model took erythrocyte binding into account, and a particular elimination process of HCB, the plasma-to-gastrointestinal (GI) lumen passive diffusion (i.e., exsorption), was incorporated. Our PBPK model was developed using data mined from multiple pharmacokinetic studies in the literature, and then modified to simulate HCB disposition under the conditions of our integrated pharmacokinetics/liver foci bioassay. This model included plasma, erythrocytes, liver, fat, rapidly and slowly perfused compartments, and GI lumen. To account for the distinct characteristics of HCB absorption, the GI lumen was split into an upper and a lower part. HCB was eliminated through liver metabolism and the exsorption process. The pathophysiological changes after partial hepatectomy, such as alterations in the liver and body weights and fat volume, were incorporated in our model. With adjustment of the transluminal diffusion-related parameters, the model adequately described the data from the literature and our bioassay. Our PBPK model simulation suggests that HCB absorption and exsorption processes depend on exposure conditions; different exposure conditions dictate different absorption and exsorption rates. This model forms a foundation for our further exploration of the quantitative relationship between HCB exposure and development of preneoplastic liver foci.

Animals↗
PubMed1992

Structure and parameterization of pharmacokinetic models: their impact on model predictions.

There has been an increasing interest in physiologically based pharmacokinetic (PBPK) models in the area of risk assessment. The use of these models raises two important issues: (1) How good are PBPK models for predicting experimental kinetic data? (2) How is the variability in the model output affected by the number of parameters and the structure of the model? To examine these issues, we compared a five-compartment PBPK model, a three-compartment PBPK model, and nonphysiological compartmental models of benzene pharmacokinetics. Monte Carlo simulations were used to take into account the variability of the parameters. The models were fitted to three sets of experimental data and a hypothetical experiment was simulated with each model to provide a uniform basis for comparison. Two main results are presented: (1) the difference is larger between the predictions of the same model fitted to different data sets than between the predictions of different models fitted to the dame data; and (2) the type of data used to fit the model has a larger effect on the variability of the predictions than the type of model and the number of parameters.

Animals↗
PubMed1993

Pharmacokinetic modeling of trichloroethylene and trichloroacetic acid in humans.

The development and application of appropriate physiologically based pharmacokinetic (PBPK) models of chemical contaminants will provide a rational basis for risk assessment extrapolation. Trichloroethylene (TCE) is a widespread contaminant found in soil, groundwater, and the atmosphere. Exposures to TCE and its metabolites have been found to be carcinogenic in rodents. In this study, a PBPK model for TCE and its major metabolite, trichloroacetic acid (TCA), is developed for humans. The model parameters, estimated from the relevant published literature on human exposures to TCE and its metabolites, are described. Key parameters describing the metabolism of TCE and the kinetics of TCA were estimated by optimization. The optimization was accomplished by simultaneously matching model predictions to observations of TCE concentrations in blood and exhaled breath, TCA plasma concentrations, and urinary TCA excretion from five published studies. The optimized human PBPK model provides an excellent description of TCE and TCA kinetics. The predictions were especially good for TCA plasma concentrations following repeated TCE inhalation, an exposure scenario similar to that occurring in the workplace. The human PBPK model can be used to estimate dose metrics resulting from TCE exposures and is therefore useful when considering the estimation of human health risks associated with such exposures.

Carcinogens↗
PubMed1995

A trichloroethylene risk assessment using a Monte Carlo analysis of parameter uncertainty in conjunction with physiologically-based pharmacokinetic modeling.

A Monte Carlo simulation is incorporated into a risk assessment for trichloroethylene (TCE) using physiologically-based pharmacokinetic (PBPK) modeling coupled with the linearized multistage model to derive human carcinogenic risk extrapolations. The Monte Carlo technique incorporates physiological parameter variability to produce a statistically derived range of risk estimates which quantifies specific uncertainties associated with PBPK risk assessment approaches. Both inhalation and ingestion exposure routes are addressed. Simulated exposure scenarios were consistent with those used by the Environmental Protection Agency (EPA) in their TCE risk assessment. Mean values of physiological parameters were gathered from the literature for both mice (carcinogenic bioassay subjects) and for humans. Realistic physiological value distributions were assumed using existing data on variability. Mouse cancer bioassay data were correlated to total TCE metabolized and area-under-the-curve (blood concentration) trichloroacetic acid (TCA) as determined by a mouse PBPK model. These internal dose metrics were used in a linearized multistage model analysis to determine dose metric values corresponding to 10(-6) lifetime excess cancer risk. Using a human PBPK model, these metabolized doses were then extrapolated to equivalent human exposures (inhalation and ingestion). The Monte Carlo iterations with varying mouse and human physiological parameters produced a range of human exposure concentrations producing a 10(-6) risk.

Administration, Inhalation↗
PubMed1997

A physiologically-based pharmacokinetic model assessment of methyl t-butyl ether in groundwater for a bathing and showering determination.

Methyl t-butyl ether (MTBE) is a gasoline additive that has appeared in private wells as a result of leaking underground storage tanks. Neurological symptoms (headache, dizziness) have been reported from household use of MTBE-affected water, consistent with animal studies showing acute CNS depression from MTBE exposure. The current research evaluates acute CNS effects during bathing/showering by application of physiologically-based pharmacokinetic (PBPK) techniques to compare internal doses in animal toxicity studies to human exposure scenarios. An additional reference point was the delivered dose associated with the acute Minimum Risk Level (MRL) for MTBE established by the Agency for Toxic Substances and Disease Registry. A PBPK model for MTBE and its principal metabolite, t-butyl alcohol (TBA) was developed and validated against published data in rats and humans. PBPK analysis of animal studies showed that acute CNS toxicity after MTBE exposure can be attributed principally to the parent compound since the metabolite (TBA) internal dose was below that needed for CNS effects. The PBPK model was combined with an exposure model for bathing and showering which integrates inhalation and dermal exposures. This modeling indicated that bathing or showering in water containing MTBE at 1 mg/L would produce brain concentrations approximately 1000-fold below the animal effects level and twofold below brain concentrations associated with the acute MRL. These findings indicate that MTBE water concentrations of 1 mg/L or below are unlikely to trigger acute CNS effects during bathing and showering. However, MTBE's strong odor may be a secondary but deciding factor regarding the suitability of such water for domestic uses.

Animals↗
PubMed2005

Using physiologically-based pharmacokinetic modeling to address nonlinear kinetics and changes in rodent physiology and metabolism due to aging and adaptation in deriving reference values for propylene glycol methyl ether and propylene glycol methyl ether acetate.

Reference values, including an oral reference dose (RfD) and an inhalation reference concentration (RfC), were derived for propylene glycol methyl ether (PGME), and an oral RfD was derived for its acetate (PGMEA). These values were based on transient sedation observed in F344 rats and B6C3F1 mice during a two-year inhalation study. The dose-response relationship for sedation was characterized using internal dose measures as predicted by a physiologically-based pharmacokinetic (PBPK) model for PGME and its acetate. PBPK modeling was used to account for changes in rodent physiology and metabolism due to aging and adaptation, based on data collected during Weeks 1, 2, 26, 52, and 78 of a chronic inhalation study. The peak concentration of PGME in richly perfused tissues (i.e., brain) was selected as the most appropriate internal dose measure based on a consideration of the mode of action for sedation and similarities in tissue partitioning between brain and other richly perfused tissues. Internal doses (peak tissue concentrations of PGME) were designated as either no-observed-adverse-effect levels (NOAELs) or lowest-observed-adverse-effect levels (LOAELs) based on the presence or the absence of sedation at each time point, species, and sex in the two-year study. Distributions of the NOAEL and LOAEL values expressed in terms of internal dose were characterized using an arithmetic mean and standard deviation, with the mean internal NOAEL serving as the basis for the reference values, which was then divided by appropriate uncertainty factors. Where data were permitting, chemical-specific adjustment factors were derived to replace default uncertainty factor values of 10. Nonlinear kinetics, which was predicted by the model in all species at PGME concentrations exceeding 100 ppm, complicate interspecies, and low-dose extrapolations. To address this complication, reference values were derived using two approaches that differ with respect to the order in which these extrapolations were performed: (1) default approach of interspecies extrapolation to determine the human equivalent concentration (PBPK modeling) followed by uncertainty factor application, and (2) uncertainty factor application followed by interspecies extrapolation (PBPK modeling). The resulting reference values for these two approaches are substantially different, with values from the latter approach being seven-fold higher than those from the former approach. Such a striking difference between the two approaches reveals an underlying issue that has received little attention in the literature regarding the application of uncertainty factors and interspecies extrapolations to compounds where saturable kinetics occur in the range of the NOAEL. Until such discussions have taken place, reference values based on the former approach are recommended for risk assessments involving human exposures to PGME and PGMEA.

Administration, Inhalation↗
PubMed2006

Physiologically-based pharmacokinetic modeling of benzene in humans: a Bayesian approach.

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.

Analysis of Variance↗
PubMedDate not supplied

A simple index for representing the discrepancy between simulations of physiological pharmacokinetic models and experimental data.

The objective of this study was to develop an index that would provide a quantitative measure of the degree of discrepancy between simulations of physiologically based pharmacokinetic (PBPK) models and experimental data. The approach we developed involves the calculation of the root mean square of the error (representing the difference between the individual simulated and experimental values for each sampling point in a time course curve), and dividing it by the root mean square of the experimental values. The resulting numerical values of discrepancy measures for several data sets (each corresponding to an end point) obtained in a single experimental study are then combined on the basis of a weighting proportional to the number of data points contained in each data set. Such consolidated discrepancy indices obtained from several experiments (e.g., exposure scenarios, doses, routes, species) are averaged to get an overall discrepancy index, referred to as the PBPK index. This empirical index reflects the overall, weighted average percent difference between the a priori PBPK model simulations and experimental data. The proposed methodology is illustrated using previously published experimental and simulated data on dichloromethane pharmacokinetics in humans. The application of this kind of a "quantitative" method should help remove the ambiguity in communicating the degree of concordance or discrepancy between PBPK model simulations and experimental data.

Animals↗
PubMed2004

Physiologically based pharmacokinetics in drug development and regulatory science: a workshop report (Georgetown University, Washington, DC, May 29-30, 2002).

A 2-day workshop on "Physiologically Based Pharmacokinetics (PBPK) in Drug Development and Regulatory Science" came to a successful conclusion on May 30, 2002, in Washington, DC. More than 120 international participants from the environmental and predominantly pharmaceutical industries, Food and Drug Administration (FDA), and universities attended this workshop, organized by the Center for Drug Development Science, Georgetown University, Washington, DC. The first of its kind specifically devoted to the subject, this intensive workshop, comprising 7 plenary presentations and 10 breakout sessions addressed 2 major objectives: (1) to "define demonstrated and potential contributions of PBPK in drug development and regulatory science," and (2) to "assess current PBPK methodologies with the identification of their limitations and outstanding issues." This report summarizes the presentations and recommendations that emerged from the workshop, while providing key references, software, and PBPK data sources in the appendices. The first day was initially devoted to presentations setting the stage and providing demonstrated applications to date. This was followed by breakout sessions that considered further opportunities and limitations, and which extended into Day 2 to deal with developments in methodologies and tools. Although the primary emphasis was on pharmacokinetics, consideration was also given to its integration specifically with mechanism-based pharmacodynamics.

Animals↗
PubMed2005

Comparison of the use of a physiologically based pharmacokinetic model and a classical pharmacokinetic model for dioxin exposure assessments.

In epidemiologic studies, exposure assessments of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) assume a fixed elimination rate. Recent data suggest a dose-dependent elimination rate for TCDD. A physiologically based pharmacokinetic (PBPK) model, which uses a body-burden-dependent elimination rate, was developed previously in rodents to describe the pharmacokinetics of TCDD and has been extrapolated to human exposure for this study. Optimizations were performed using data from a random selection of veterans from the Ranch Hand cohort and data from a human volunteer who was exposed to TCDD. Assessment of this PBPK model used additional data from the Ranch Hand cohort and a clinical report of two women exposed to TCDD. This PBPK model suggests that previous exposure assessments may have significantly underestimated peak blood concentrations, resulting in potential exposure misclassifications. Application of a PBPK model that incorporates an inducible elimination of TCDD may improve the exposure assessments in epidemiologic studies of TCDD.

Body Burden↗
PubMed2006

Use of a physiologically based pharmacokinetic model for rats to study the influence of body fat mass and induction of CYP1A2 on the pharmacokinetics of TCDD.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a highly lipophilic chemical that distributes into adipose tissue, especially at low doses. However, at high doses TCDD sequesters in liver because it induces cytochrome P450 1A2 (CYP1A2) that binds TCDD. A physiologically based pharmacokinetic (PBPK) model was developed that included an inducible elimination rate of TCDD in the Sprague-Dawley rat. Objectives of this work were to characterize the influence of induction of CYP1A2 and adipose tissue mass fraction on the terminal elimination half-life (t1/2) of TCDD using this PBPK model. When the model assumes a fixed elimination of TCDD, t1/2 increases with dose, due to hepatic sequestration. Because experimental data indicate that the t1/2 of TCDD decreases with dose, the model was modified to include an inducible elimination rate. The PBPK model was then used to compare the t1/2 after an increase of adipose tissue mass fraction from 6.9 to 70%. The model suggests that at low exposures, increasing adipose tissue mass increases the terminal t1/2. However, at higher exposures, as CYP1A2 is induced, the relationship between adipose tissue mass and t1/2 reaches a plateau. This demonstrates that an inducible elimination rate is needed in a PBPK model in order to describe the pharmacokinetics of TCDD. At low exposures these models are more sensitive to parameters related to partitioning into adipose tissue.

Adipose Tissue↗
PubMed1994

Physiologically based pharmacokinetics and cancer risk assessment.

Physiologically based pharmacokinetic (PBPK) modeling involves mathematically describing the complex interplay of the critical physicochemical and biological determinants involved in the disposition of chemicals. In this approach, the body is divided into a number of biologically relevant tissue compartments, arranged in an anatomically accurate manner, and defined with appropriate physiological characteristics. The extrapolation of pharmacokinetic behavior of chemicals from high dose to low dose for various exposure routes and species is possible with this approach because these models are developed by integrating quantitative information on the critical determinants of chemical disposition under a biological modeling framework. The principal application of PBPK models is in the prediction of tissue dosimetry of toxic moiety (e.g., parent chemical, reactive metabolite, macromolecular adduct) of a chemical. Such an application has been demonstrated with dichloromethane, a liver and lung carcinogen in the B6C3F1 mouse. The PBPK model-based risk assessment approach estimated a cancer risk to people of 3.7 x 10(-8) for a lifetime inhalation exposure of 1 micrograms/m3, which is lower by more than two orders of magnitude than that calculated by the U.S. Environmental Protection Agency using the linearized multistage model (for low-dose extrapolation) and body surface correction factor (for interspecies scaling). The capability of predicting the target tissue exposure to toxic moiety in people with PBPK models should help reduce the uncertainty associated with the extrapolation procedures adopted in conventional dose-response assessment.

Animals↗
PubMed1994

Applications of physiologic pharmacokinetic modeling in carcinogenic risk assessment.

The use of physiologically based pharmacokinetic (PBPK) models has been proposed as a means of estimating the dose of the reactive metabolites of carcinogenic xenobiotics reaching target tissues, thereby affording an opportunity to base estimates of potential cancer risk on tissue dose rather than external levels of exposure. In this article, we demonstrate how a PBPK model can be constructed by specifying mass-balance equations for each physiological compartment included in the model. In general, this leads to a system of nonlinear partial differential equations with which to characterize the compartment system. These equations then can be solved numerically to determine the concentration of metabolites in each compartment as functions of time. In the special case of a linear pharmacokinetic system, we present simple closed-form expressions for the area under the concentration-time curves (AUC) in individual tissue compartments. A general relationship between the AUC in blood and other tissue compartments is also established. These results are of use in identifying those parameters in the models that characterize the integrated tissue dose, and which should therefore be the primary focus of sensitivity analyses. Applications of PBPK modeling for purposes of tissue dosimetry are reviewed, including models developed for methylene chloride, ethylene oxide, 1,4-dioxane, 1-nitropyrene, as well as polychlorinated biphenyls, dioxins, and furans. Special considerations in PBPK modeling related to aging, topical absorption, pregnancy, and mixed exposures are discussed. The linkage between pharmacokinetic models used for tissue dosimetry and pharmacodynamic models for neoplastic transformation of stem cells in the target tissue is explored.

Animals↗
PubMed1996

Biomarkers of environmental benzene exposure.

Environmental exposures to benzene result in increases in body burden that are reflected in various biomarkers of exposure, including benzene in exhaled breath, benzene in blood and urinary trans-trans-muconic acid and S-phenylmercapturic acid. A review of the literature indicates that these biomarkers can be used to distinguish populations with different levels of exposure (such as smokers from nonsmokers and occupationally exposed from environmentally exposed populations) and to determine differences in metabolism. Biomarkers in humans have shown that the percentage of benzene metabolized by the ring-opening pathway is greater at environmental exposures than that at higher occupational exposures, a trend similar to that found in animal studies. This suggests that the dose-response curve is nonlinear; that potential different metabolic mechanisms exist at high and low doses; and that the validity of a linear extrapolation of adverse effects measured at high doses to a population exposed to lower, environmental levels of benzene is uncertain. Time-series measurements of the biomarker, exhaled breath, were used to evaluate a physiologically based pharmacokinetic (PBPK) model. Biases were identified between the PBPK model predictions and experimental data that were adequately described using an empirical compartmental model. It is suggested that a mapping of the PBPK model to a compartmental model can be done to optimize the parameters in the PBPK model to provide a future framework for developing a population physiologically based pharmacokinetic model.

Air Pollutants↗
PubMed1996

Reassessing benzene risks using internal doses and Monte-Carlo uncertainty analysis.

Human cancer risks from benzene have been estimated from epidemiological data, with supporting evidence from animal bioassay data. This article reexamines the animal-based risk assessments using physiologically based pharmacokinetic (PBPK) models of benzene metabolism in animals and humans. Internal doses (total benzene metabolites) from oral gavage experiments in mice are well predicted by the PBPK model. Both the data and the PBPK model outputs are also well described by a simple nonlinear (Michaelis-Menten) regression model, as previously used by Bailer and Hoel [Metabolite-based internal doses used in risk assessment of benzene. Environ Health Perspect 82:177-184 (1989)]. Refitting the multistage model family to internal doses changes the maximum-likelihood estimate (MLE) dose-response curve for mice from linear-quadratic to purely cubic, so that low-dose risk estimates are smaller than in previous risk assessments. In contrast to Bailer and Hoel's findings using interspecies dose conversion, the use of internal dose estimates for humans from a PBPK model reduces estimated human risks at low doses. Sensitivity analyses suggest that the finding of a nonlinear MLE dose-response curve at low doses is robust to changes in internal dose definitions and more consistent with epidemiological data than earlier risk models. A Monte-Carlo uncertainty analysis based on maximum-entropy probabilities and Bayesian conditioning is used to develop an entire probability distribution for the true but unknown dose-response function. This allows the probability of a positive low-dose slope to be quantified: It is about 10%. An upper 95% confidence limit on the low-dose slope of excess risk is also obtained directly from the posterior distribution and is similar to previous q1* values. This approach suggests that the excess risk due to benzene exposure may be nonexistent (or even negative) at sufficiently low doses. Two types of biological information about benzene effects--pharmacokinetic and hematotoxic--are examined to test the plausibility of this finding. A framework for incorporating causally relevant biological information into benzene risk assessment is introduced, and it is shown that both pharmacokinetic and hematotoxic models appear to be consistent with the hypothesis that sufficiently low concentrations of inhaled benzene do not create and excess risk.

Administration, Oral↗