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Investigation of the potential impact of benchmark dose and pharmacokinetic modeling in noncancer risk assessment.

There has been relatively little attention given to incorporating knowledge of mode of action or of dosimetry of active toxic chemical to target tissue sites in the calculation of noncancer exposure guidelines. One exception is the focus in the revised reference concentration (RfC) process on delivered dose adjustments for inhaled materials. The studies reported here attempt to continue in the spirit of the new RfC guidelines by incorporating both mechanistic and delivered dose information using a physiologically based pharmacokinetic (PBPK) model, along with quantitative dose-response information using the benchmark dose (BMD) method, into the noncancer risk assessment paradigm. Two examples of the use of PBPK and BMD techniques in noncancer risk assessment are described: methylene chloride, and trichloroethylene. Minimal risk levels (MRLs) based on PBPK analysis of these chemicals were generally similar to those based on the traditional process, but individual MRLs ranged from roughly 10-fold higher to more than 10-fold lower than existing MRLs that were not based on PBPK modeling. Only two MRLs were based on critical studies that presented adequate data for BMD modeling, and in these two cases the BMD models were unable to provide an acceptable fit to the overall dose-response of the data, even using pharmacokinetic dose metrics. A review of 10 additional chemicals indicated that data reporting in the toxicological literature is often inadequate to support BMD modeling. Three general observations regarding the use of PBPK and BMD modeling in noncancer risk assessment were noted. First, a full PBPK model may not be necessary to support a more accurate risk assessment; often only a simple pharmacokinetic description, or an understanding of basic pharmacokinetic principles, is needed. Second, pharmacokinetic and mode of action considerations are a crucial factor in conducting noncancer risk assessments that involve animal-to-human extrapolation. Third, to support the application of BMD modeling in noncancer risk assessment, reporting of toxicity results in the toxicological literature should include both means and standard deviations for each dose group in the case of quantitative endpoints, such as relative organ weights or testing scores, and should report the number of animals affected in the case of qualitative endpoints.

Animals↗

A hybrid computational fluid dynamics and physiologically based pharmacokinetic model for comparison of predicted tissue concentrations of acrylic acid and other vapors in the rat and human nasal cavities following inhalation exposure.

To assist in interspecies dosimetry comparisons for risk assessment of the nasal effects of organic acids, a hybrid computational fluid dynamics (CFD) and physiologically based pharmacokinetic (PBPK) dosimetry model was constructed to estimate the regional tissue dose of inhaled vapors in the rat and human nasal cavity. Application to a specific vapor would involve the incorporation of the chemical-specific reactivity, metabolism, partition coefficients, and diffusivity (in both air and tissue phases) of the vapor. This report describes the structure of the CFD-PBPK model and its application to a representative acidic vapor, acrylic acid, for interspecies tissue concentration comparisons to assist in risk assessment. By using the results from a series of short-term in vivo studies combined with computer modeling, regional nasal tissue dose estimates were developed and comparisons of tissue doses between species were conducted. To make these comparisons, the assumption was made that the susceptibilities of human and rat olfactory epithelium to the cytotoxic effects of organic acids were similar, based on similar histological structure and common mode of action considerations. Interspecies differences in response were therefore assumed to be driven primarily by differences in nasal tissue concentrations that result from regional differences in nasal air flow patterns relative to the species-specific distribution of olfactory epithelium in the nasal cavity. The results of simulations with the seven-compartment CFD-PBPK model suggested that the olfactory epithelium of the human nasal cavity would be exposed to tissue concentrations of acrylic acid similar to that of the rat nasal cavity when the exposure conditions are the same. Similar analysis of CFD data and CFD-PBPK model simulations with a simpler one-compartment model of the whole nasal cavities of rats and humans provides comparable results to averaging over the compartments of the seven-compartment model. These results indicate that the general structure of the hybrid CFD-PBPK model applied in this assessment would be useful for target tissue dosimetry and interspecies dose comparisons for a wide variety of vapors. Because of its flexibility, this CFD-PBPK model is envisioned to be a platform for the construction of case-specific inhalation dosimetry models to simulate in vivo exposures that do not involve significant histopathological damage to the nasal cavity.

Acrylates↗

Human physiologically based pharmacokinetic model for propofol.

BACKGROUND: Propofol is widely used for both short-term anesthesia and long-term sedation. It has unusual pharmacokinetics because of its high lipid solubility. The standard approach to describing the pharmacokinetics is by a multi-compartmental model. This paper presents the first detailed human physiologically based pharmacokinetic (PBPK) model for propofol. METHODS: PKQuest, a freely distributed software routine http://www.pkquest.com, was used for all the calculations. The "standard human" PBPK parameters developed in previous applications is used. It is assumed that the blood and tissue binding is determined by simple partition into the tissue lipid, which is characterized by two previously determined set of parameters: 1) the value of the propofol oil/water partition coefficient; 2) the lipid fraction in the blood and tissues. The model was fit to the individual experimental data of Schnider et. al., Anesthesiology, 1998; 88:1170 in which an initial bolus dose was followed 60 minutes later by a one hour constant infusion. RESULTS: The PBPK model provides a good description of the experimental data over a large range of input dosage, subject age and fat fraction. Only one adjustable parameter (the liver clearance) is required to describe the constant infusion phase for each individual subject. In order to fit the bolus injection phase, for 10 or the 24 subjects it was necessary to assume that a fraction of the bolus dose was sequestered and then slowly released from the lungs (characterized by two additional parameters). The average weighted residual error (WRE) of the PBPK model fit to the both the bolus and infusion phases was 15%; similar to the WRE for just the constant infusion phase obtained by Schnider et. al. using a 6-parameter NONMEM compartmental model. CONCLUSION: A PBPK model using standard human parameters and a simple description of tissue binding provides a good description of human propofol kinetics. The major advantage of a PBPK model is that it can be used to predict the changes in kinetics produced by variations in physiological parameters. As one example, the model simulation of the changes in pharmacokinetics for morbidly obese subjects is discussed.

Journal Article↗

Physiologically based pharmacokinetic models for trichloroethylene and its oxidative metabolites.

Trichloroethylene (TCE) pharmacokinetics have been studied in experimental animals and humans for over 30 years. Compartmental and physiologically based pharmacokinetic (PBPK) models have been developed for the uptake, distribution, and metabolism of TCE and the production, distribution, metabolism, and elimination of P450-mediated metabolites of TCE. TCE is readily taken up into systemic circulation by oral and inhalation routes of exposure and is rapidly metabolized by the hepatic P450 system and to a much lesser degree, by direct conjugation with glutathione. Recent PBPK models for TCE and its metabolites have focused on the major metabolic pathway for metabolism of TCE (P450-mediated metabolic pathway). This article briefly reviews selected published compartmental and PBPK models for TCE. Trichloroacetic acid (TCA) is considered a principle metabolite responsible for TCE-induced liver cancer in mice. Liver cancer in mice was considered a critical effect by the U.S. Environmental Protection Agency for deriving the current maximum contaminant level for TCE in water. In the literature both whole blood and plasma measurements of TCA are reported in mice and humans. To reduce confusion about disparately measured and model-predicted levels of TCA in plasma and whole blood, model-predicted outcomes are compared for first-generation (plasma) and second-generation (whole blood) PBPK models published by Fisher and colleagues. Qualitatively, animals and humans metabolize TCE in a similar fashion, producing the same metabolites. Quantitatively, PBPK models for TCE and its metabolites are important tools for providing dosimetry comparisons between experimental animals and humans. TCE PBPK models can be used today to aid in crafting scientifically sound public health decisions for TCE.

Animals↗

Physiological modeling and extrapolation of pharmacokinetic interactions from binary to more complex chemical mixtures.

The available data on binary interactions are yet to be considered within the context of mixture risk assessment because of our inability to predict the effect of a third or a fourth chemical in the mixture on the interacting binary pairs. Physiologically based pharmacokinetic (PBPK) models represent a potentially useful framework for predicting the consequences of interactions in mixtures of increasing complexity. This article highlights the conceptual basis and validity of PBPK models for extrapolating the occurrence and magnitude of interactions from binary to more complex chemical mixtures. The methodology involves the development of PBPK models for all mixture components and interconnecting them at the level of the tissue where the interaction is occurring. Once all component models are interconnected at the binary level, the PBPK framework simulates the kinetics of all mixture components, accounting for the interactions occurring at various levels in more complex mixtures. This aspect was validated by comparing the simulations of a binary interaction-based PBPK model with experimental data on the inhalation kinetics of m-xylene, toluene, ethyl benzene, dichloromethane, and benzene in mixtures of varying composition and complexity. The ability to predict the kinetics of chemicals in complex mixtures by accounting for binary interactions alone within a PBPK model is a significant step toward the development of interaction-based risk assessment for chemical mixtures.

Animals↗

Rat to human extrapolation of HCFC-123 kinetics deduced from halothane kinetics: a corollary approach to physiologically based pharmacokinetic modeling.

The goal of this study was to develop a human physiologically based pharmacokinetic (PBPK) model for the chemical HCFC-123 (2,2-dichloro-1,1,1-trifluoroethane) and its major metabolite, trifluoroacetic acid (TFA). No human kinetic data for HCFC-123 are available, thus a corollary approach was developed. HCFC-123 is a structural analog of the common anesthetic agent halothane (2-bromo-2-chloro-1,1,1-trifluoroethane) and follows a common pathway of oxidative biotransformation, resulting in the formation of the same metabolite, TFA. In this study, halothane models for rats and humans were developed and validated. Then the corollary approach was used to develop a human HCFC-123 model from a rat HCFC-123 model. This strategy was implemented by using a previously validated PBPK model for HCFC-123/TFA in the Fisher 344 rat as a template model for halothane in rats. Model predictions were then compared to, and were in good agreement with, measured values for the concentration of halothane in rat blood and fat tissue. A human PBPK model for halothane was developed. The identical mode structure (with the exception of the description for the fat compartment) that was used to describe halothane and TFA in the rat was used for describing halothane and TFA in the human. Human physiological parameters for tissue volumes and flows were taken from the literature, and human tissue partition coefficients for halothane were measured in the laboratory. Based on reported similarity in metabolism of halothane by humans and rats, metabolic constants for halothane in the rat were used in the human model, and specific parameters describing the kinetics of TFA were estimated by optimization. The model was validated against human exposure data for halothane from six published studies (expired breath concentrations of halothane and serum/urine data for TFA). A similar approach was then used to derive a human HCFC-123 model for humans from the HCFC-123 rat model. The corollary approach described here illustrates the innovative use of template model structures to aid in the development and validation of models for structural analogs with similar metabolism and activity in biologic systems. Furthermore, given that the PBPK model adequately describes the kinetics of halothane in rats and humans and of HCFC-123 in rats, use of the human PBPK model is proposed for deriving dose-response estimates of human health risks in the absence of human kinetic data.

Animals↗

DNA-protein cross-links (DPX) and cell proliferation in B6C3F1 mice but not Syrian golden hamsters exposed to dichloromethane: pharmacokinetics and risk assessment with DPX as dosimeter.

Dichloromethane (DCM) (methylene chloride; CH2Cl2) is metabolized via a glutathione S-transferase-mediated pathway to formaldehyde (HCHO), a mutagenic compound that could play a role in the carcinogenic effects of DCM observed in the liver and lungs of B6C3F1 mice at 2000 and 4000 ppm. Mice but not hamsters formed DNA-protein cross-links (DPX) in the liver at DCM concentrations ranging from approximately 500 to 4000 ppm. The formation of DPX was a nonlinear function of the airborne concentration of DCM. In addition, mice exposed to DCM (6 hr/day, 3 days) at concentrations ranging from approximately 1500 to 4000 ppm showed an increased rate of DNA synthesis in the lung indicating cell proliferation, but increased cell turnover was not detected in mouse lung at exposure concentrations of 150 or 500 ppm. Hamsters showed no evidence of cell proliferation in the lung at any concentration, and cell proliferation was not apparent in the livers of either mice or hamsters. An extended physiologically based pharmacokinetic (PBPK) model for DPX formation in mouse liver was developed, based on a published PBPK model for DCM (Andersen, M.E., Clewell, H.J., III, Gargas, M.L., Smith, F.A., and Reitz, R.H. (1987). Toxicol. Appl. Pharmacol. 87, 185-205). The extended PBPK model was fitted to the DPX data using the PBPK model-estimated area under the curve for DCM in mouse liver as the independent variable. Parameter estimates for HCHO disposition in the livers of mice exposed to dichloromethane were similar to previously published estimates for HCHO disposition in the nasal mucosa of rats exposed to formaldehyde. Using the extended PBPK model, estimates were made of the yields of DPX presumably formed in mouse liver at the DCM concentrations used in a bioassay (Mennear, J.H., McConnell, E.E., Huff, J.E., Renne, R.A., and Giddens, E. (1988). Ann. NY Acad. Sci. 534, 343-351). The tumor incidence data in mice were fitted to the DPX yields and to the airborne concentration of DCM as alternative measures of exposure using the linearized multistage (LMS) model. The two dose measures yielded similar maximum likelihood estimates for the cancer risk at concentrations from 10 to 100 ppm, but the upper 95% confidence limit on the risk was reduced by two orders of magnitude when DPX rather than the airborne concentration was used as the measure of exposure. The results demonstrate that an internal dosimeter such as DPX can markedly improve the precision of low-dose risk estimates, while having only a minor effect on the maximum likelihood estimates calculated with the LMS model.

Administration, Inhalation↗

Computer simulation of the lactational transfer of tetrachloroethylene in rats using a physiologically based model.

A physiologically based pharmacokinetic (PBPK) model describing transfer of inhaled tetrachloroethylene (PCE) into breast milk with the consequent exposure of the nursing pups was developed and validated in lactating rats. The PBPK model was based on partition coefficients (PCs), which were determined by the equilibration of tissues with known concentrations of PCE vapor. The blood/air and milk/blood PCs for the dam were 33.5 and 12.0, the liver/blood and fat/blood PCs for the dam were 1.9 and 42.4, and the slowly perfused tissues/blood and rapidly perfused tissues/blood PCs for the dam were 0.9 and 1.7, respectively. The blood/air PC for the pup was 24.3, and the solid tissues/blood PC for the pup was 4.5. Metabolic constants were determined by a gas uptake method. The pseudo-maximal velocity of PCE metabolism in the dam was low, 0.03 mg/kg/hr, and the apparent Michaelis-Menten constant was 0.3 mg/liter. The lactating Sprague-Dawley females were exposed to PCE vapor for 2 hr with concentrations ranging from 20 to 1000 ppm PCE. The dams were returned to the pups after exposure and the pups received PCE via breast milk while they nursed. PCE concentrations in the air, blood, milk, and tissues were determined by gas chromatography and compared to PBPK model predictions. Nursing resulted in a peak pup blood PCE concentration of 0.9 mg/liter and a peak pup solid tissue PCE concentration of 8 mg/kg. The PBPK lactation model adequately described the distribution of inhaled PCE in maternal blood and milk, as well as in the nursed pup's gastrointestinal tract, blood, and solid tissues. It is concluded that the predictions based on PBPK modeling for disposition of PCE in lactating rats and their pups were in good agreement with the experimental data.

Administration, Inhalation↗

A physiologically based pharmacokinetic model for trichloroethylene and its metabolites, chloral hydrate, trichloroacetate, dichloroacetate, trichloroethanol, and trichloroethanol glucuronide in B6C3F1 mice.

A six-compartment physiologically based pharmacokinetic (PBPK) model for the B6C3F1 mouse was developed for trichloroethylene (TCE) and was linked with five metabolite submodels consisting of four compartments each. The PBPK model for TCE and the metabolite submodels described oral uptake and metabolism of TCE to chloral hydrate (CH). CH was further metabolized to trichloroethanol (TCOH) and trichloroacetic acid (TCA). TCA was excreted in urine and, to a lesser degree, metabolized to dichloroacetic acid (DCA). DCA was further metabolized. The majority of TCOH was glucuronidated (TCOG) and excreted in the urine and feces. TCOH was also excreted in urine or converted back to CH. Partition coefficient (PC) values for TCE were determined by vial equilibrium, and PC values for nonvolatile metabolites were determined by centrifugation. The largest PC values for TCE were the fat/blood (36.4) and the blood/air (15.9) values. Tissue/blood PC values for the water-soluble metabolites were low, with all PC values under 2.0. Mice were given bolus oral doses of 300, 600, 1200, and 2000 mg/kg TCE dissolved in corn oil. At various time points, mice were sacrificed, and blood, liver, lung, fat, and urine were collected and assayed for TCE and metabolites. The 1200 mg/kg dose group was used to calibrate the PBPK model for TCE and its metabolites. Urinary excretion rate constant values were 0. 06/hr/kg for CH, 1.14/hr/kg for TCOH, 32.8/hr/kg for TCOG, and 1. 55/hr/kg for TCA. A fecal excretion rate constant value for TCOG was 4.61/hr/kg. For oral bolus dosing of TCE with 300, 600, and 2000 mg/kg, model predictions of TCE and several metabolites were in general agreement with observations. This PBPK model for TCE and metabolites is the most comprehensive PBPK model constructed for P450-mediated metabolism of TCE in the B6C3F1 mouse.

Administration, Oral↗

Determination of parameters responsible for pharmacokinetic behavior of TCDD in female Sprague-Dawley rats.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is the most toxic member of a class of planar and halogenated chemicals. Improvements in exposure assessment of TCDD require scientific information on the distribution of TCDD in target tissues and cellular responses induced by TCDD. Since 1980, several physiologically based pharmacokinetic (PBPK) models for TCDD and related compounds have been reported. Some of these models incorporated the induction of a hepatic binding protein in response to interactions of TCDD, the Ah receptor, and DNA binding sites and described the TCDD disposition in a biological system for certain data sets. Due to the limitations of the available experimental data, different values for the same physical parameters of these models were obtained from the different studies. The inconsistencies of the parameter values limit the application of PBPK models to risk assessment. Therefore, further refinement of previous models is necessary. This paper develops an improved PBPK model to describe TCDD disposition in eight target tissues. The interaction of TCDD with the Ah receptor and with hepatic inducible CYP1A2 were also incorporated into the model. This model accurately described the time course distribution of TCDD following a single oral dose of 10 microg/kg, as well as the TCDD concentration on Day 3 after six different doses, 0.01, 0.1, 0.3, 1, 10, and 30 microg TCDD/kg, in target tissues. This study extends previous TCDD models by illustrating the validity and the limitation of the model and providing further confirmation of the potential PBPK model for us in optimal experimental design and extrapolation across doses and routes of exposure. In addition, this study demonstrated some critical issues in PBPK modeling.

Administration, Oral↗

Application of physiology-based pharmacokinetic and pharmacodynamic modeling to individualized target-controlled propofol infusions.

This study compared the ability of the physiology-based pharmacokinetic (PBPK) model with that of compartmental models used in propofol infusion devices to predict the pharmacokinetics and pharmacodynamics of propofol in various patient groups (children, pregnant women, young men, normal weight adults, and obese adults). With a PBPK model, loss of consciousness (LOC) and recovery of consciousness (ROC) corresponded to a narrow range of brain tissue concentrations (2.2-4.0 mg/L). With the compartmental models, predicted effect concentrations were also within a narrow range at LOC, but were outside the range at ROC. In individuals of normal weight, coefficients of variation (CV) of the predicted brain or effect concentrations at LOC were in a similar range-between 18% and 32%. In obese individuals, however, interindividual CV values for brain or effect concentrations were 41% (PBPK) and 93% (compartmental). This comparison suggests the increased flexibility of PBPK models over compartmental models, the latter of which rely heavily on the patient group from which the model was derived. The incorporation of PBPK models may provide target-controlled infusions with enhanced ability to predict response in a wide variety of patients.

Adult↗

Use of physiologically based pharmacokinetic modeling to investigate individual versus population risk.

Because of the heterogeneity of the human population, it is generally expected that there will be a broad range of observed susceptibilities to the biological effects of exposure to chemicals or drugs. Often it is possible to distinguish specific classes of individuals, such as infants or the elderly, who appear to be more susceptible to a specific effect. Non-cancer risk assessment often address this variability by dividing the experimentally determined acceptable exposure level by an uncertainty factor of 10 to protect sensitive individuals; cancer risk assessments typically do not address this issue in any quantitative fashion. Physiologically based pharmacokinetic (PBPK) modeling provides the capability to quantitatively describe the potential impact of pharmacokinetic factors on the variability of individual risk. In particular, PBPK models can be used to determine the impact of differences in key metabolism enzymes, whether due to multiple genotypic expression, such as cytochrome P450 polymorphisms, or just due to normal variation in enzyme activities within the general population. Other potential modulators of sensitivity which can be addressed quantitatively with a PBPK model include physical condition, level of activity, disease states, age, hormonal status, and interactions with other chemicals and drugs. In each case, the PBPK model provides a quantitative structure for determining the effect of these various factors on the relationship between the external (environmental) exposure and the internal (biologically effective) target tissue exposure. When coupled with Monte Carlo analysis, the PBPK model provides a method to assess the quantitative impact of these sources of variability on individual risk (as opposed to average population risk) by comparing model-predicted risks over the distribution of individual parameter values.

Animals↗

Evaluation of uncertainty in input parameters to pharmacokinetic models and the resulting uncertainty in output.

Physiologically-based pharmacokinetic (PBPK) models may be used to predict the concentrations of parent chemical or metabolites in tissues, resulting from specified chemical exposures. An important application of PBPK modeling is in assessment of carcinogenic risks to humans, based on animal data. The parameters of a PBPK model may include metabolic parameters, blood/air and tissue/blood partition coefficients, and physiological parameters, such as organ weights and blood flow rates. Uncertainty in estimates of these parameters results in uncertainty regarding tissue concentrations and resulting risks. Data are reviewed relevant to the quantification of these uncertainties, for a PBPK model-based risk assessment for tetrachloroethylene. Probability distributions are developed to express uncertainty in model parameters, and uncertainties are propagated by a sequence of operations that simulates processes recognized as contributing to estimates of human risk. Distributions of PBPK model output and human risk estimates are used to characterize uncertainty resulting from uncertainty in model parameters.

Animals↗

The application of physiologically based pharmacokinetic modeling in human health risk assessment of hazardous substances.

Physiologically based pharmacokinetic (PBPK) modeling is an important tool for improving the accuracy of human health risk assessments for hazardous substances in the environment. The proper use of PBPK modeling can reduce uncertainties that currently exist in risk assessment procedures by providing more scientifically credible extrapolations across species and routes of exposure, and from high experimental doses to potential environmental exposures. Current applications of PBPK models range from relatively straightforward uses for the extrapolation of chemical kinetics across species, route, and duration of exposure to much more demanding chemical risk assessment applications requiring a description of complex pharmacodynamic phenomena such as mitogenicity and hyperplasia secondary to cytotoxicity. PBPK modeling helps to identify the factors that are most important in determining the health risks associated with exposure to a chemical, and provides a means for estimating the impact of those factors both on the average risk to a population and on the specific risk to an individual. The chief challenge in the application of PBPK modeling in human health risk assessment lies in the need to generate chemical-specific data to support the development and validation of the models. Extensive use of rapidly developing in vitro and structure-activity relationship techniques is needed to provide the data required for the large number of hazardous chemicals currently contaminating the environment.

Animals↗

Application of physiologically based pharmacokinetic modelling to combination toxicology.

Non-additive toxicity has been demonstrated in laboratory animals for a large number of temporally separated or concurrent multiple chemical exposures. These exposures are typically at concentrations higher than those found in the environment, leading to the question of the applicability of the results to the human situation. Physiologically based pharmacokinetic (PBPK) modelling has been applied successfully to single chemicals; its utility for extrapolation across species and dose has been demonstrated. Use of PBPK modelling in the study of chemical mixtures is increasing although still limited. The use of PBPK modelling by various investigators in the field of combination toxicology is reviewed. PBPK modelling has been used to examine: the role of increased metabolism in non-additive toxicity resulting from temporally separated exposures; the influence of the time interval separating two chemical exposures; and the role of inhibition of metabolism in concurrent exposure to two chemicals. In summary, development of a PBPK or PBPK/pharmacodynamic model for a combined exposure provides a basis for extrapolation across species, route and dose, and a useful tool for risk assessment.

Animals↗

Reverse dosimetry: interpreting trihalomethanes biomonitoring data using physiologically based pharmacokinetic modeling.

Biomonitoring data provide evidence of exposure of environmental chemicals but are not, by themselves, direct measures of exposure. To use biomonitoring data in understanding exposure, physiologically based pharmacokinetic (PBPK) modeling can be used in a reverse dosimetry approach to assess a distribution of exposures possibly associated with specific blood or urine levels of compounds. Reverse dosimetry integrates PBPK modeling with exposure pattern characterization, Monte Carlo analysis, and statistical tools to estimate a distribution of exposures that are consistent with biomonitoring data in a population. The present study used an existing PBPK model for chloroform as a generic framework to develop PBPK models for other trihalomethanes (THMs). Using Monte Carlo sampling techniques, probabilistic information about pharmacokinetics and exposure patterns was included to estimate distributions of THMs concentrations in blood in relation to various exposure patterns in a diverse population. In addition, the possibility of inhibition of hepatic metabolism among THMs was evaluated under the scenarios of household exposure. These studies demonstrated how PBPK modeling can be used as a tool to estimate a population distribution of exposures that could have resulted in particular biomonitoring results. When toxicity level is known, this tool can also be used to estimate proportion of population above levels associated with health risk.

Animals↗

Physiologically based pharmacokinetics of bisphenol A.

A physiologically based pharmacokinetic (PBPK) model consisting of vein, artery, lung, liver, spleen, kidneys, heart, testes, muscle, brain, adipose tissue, stomach, and small intestine was developed to predict the tissue distribution and blood pharmacokinetics of bisphenol A in rats and humans. To demonstrate the validity of the developed PBPK model, bisphenol A was administered to rats by multiple iv injections to steady state. The PBPK model predicted the steady-state levels of bisphenol A in blood and various tissues observed in rats after multiple iv injections. The PBPK model was further applied to predict blood and various tissue levels of bisphenol A in a 70 kg-human after single iv injection (5-mg dose) and multiple oral administrations to steady state (100-mg doses every 24 h). The simulated steady-state human blood levels (0.9-1.6 ng/ml) were comparable to basal blood levels of bisphenol A reported in literature (1.49 ng/ml). Furthermore, pharmacokinectic parameters of CL (116.6 L/h), Vss (141.8 L), and t1/2 (76.8 min) predicted for humans were comparable to those previously predicted by simple allometric scaling. This PBPK model may provide insights into the tissue distribution characteristics as a result of human exposure to bisphenol A.

Animals↗

Application of a physiologically based pharmacokinetic model for reference dose and reference concentration estimation for acetone.

Recent health risk assessments to propose a Reference Dose (RfD) for acetone (Forsyth, 2001; U.S. EPA, 2001) have been based on the results of an oral subchronic study conducted in rats and mice (Dietz et al., 1991; NTP, 1991). These assessments have utilized the traditional concept of establishing the RfD by determining the lowest experimentally determined No-Observed-Adverse-Effect Level (NOAEL) and applying various Uncertainty Factors (UFs) (U.S. EPA, 1988). This article describes a risk assessment for acetone based on the systemic toxicity observed in subchronic and developmental toxicity studies to estimate an RfD and an inhalation reference concentration (RfC) for acetone. Specifically, this approach examined the subchronic study by Dietz et al. (1991), as well as an inhalation developmental toxicity study on acetone (Mast et al., 1988) and several toxicology studies of isopropanol (IPA). This was accomplished by applying a physiologically based pharmacokinetic (PBPK) model developed previously for IPA and its metabolite acetone (Clewell et al., 2001). The incorporation of the PBPK model into the derivation of an RfD and RfC for acetone allowed for a tissue-based approach rather than an external exposure-based approach, making it possible to derive an oral RfD from an inhalation study. In addition, the use of the PBPK model to analyze data from chronic and reproductive/developmental studies conducted with IPA enabled an assessment of the potential for acetone to produce any of the effects observed in the IPA studies. This analysis provided sufficient information to reduce the need for UFs in the adjustment of the NOAEL from the oral subchronic study for the determination of an RfD. Using the PBPK model in the acetone risk assessment supports a composite UF of 60 for the subchronic study, compared to composite factors of 300 to 3000 in the other recent risk assessments. This difference resulted in an RfD of 16 mg/kg/d, compared to the values of 0.3 to 3 that have previously been estimated (Forsyth, 2001; U.S. EPA, 2001). Considering the results from the inhalation developmental study (Mast et al., 1988) resulted in an RfD of 8.7 mg/kg/d. Using this study also fills a data gap for acetone that exists if only the oral database for acetone is considered for RfD derivation. An RfC of 29 ppm was also estimated for acetone using the Mast et al. (1988) study results in combination with the PBPK model. The potential impact of endogenous acetone on a risk assessment for acetone is also discussed.

Acetone↗