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In silico methods to estimate and/or quantify skin absorption of chemicals as a function of chemistry are needed to realistically predict pharmacological, occupational, and environmental exposures. The Potts-Guy equation is a well- established approach, using multi-linear regression analysis describing skin permeability (Kp) in terms of the octanol/water partition coefficient (logP) and molecular weight (MW). In this work, we obtained regression equations for different human datasets relevant to environmental and cosmetic chemicals. Since the Potts-Guy equation was published in 1992, we explored recent datasets that include different skin layers, such as dermatomed (including dermis to a defined thickness) and full-skin. Our work was consistent with others who have observed that fits to the Potts-Guy equation are stronger for experiments focused on the epidermis. Permeability estimates for dermatomed skin and full skin resulted in low regression coefficients when compared to epidermis datasets. An updated regression equation uses a combination of fitted permeability values obtained with a published 2D compartmental model previously evaluated. The resulting regression equation was: logKp = = -2.55 +0.65*logP - 0.0085*MW, R

PBPK models are well-established frameworks used to describe absorption, distribution, metabolism, and excretion of xenobiotics. To quantify metabolism, a PBPK model for a volatile compound can be calibrated with closed chamber (i.e., vapor uptake) inhalation data. Here, we introduce global optimization as a novel component of the predictive process and use it to illustrate a procedure for metabolic parameter estimation. Male F344 rats were exposed in vapor uptake chambers to initial concentrations of 100, 500, 1000, and 3000 ppm chloroform. Chamber time-course data from these experiments, in combination with optimization using a chemical specific PBPK model, were used to estimate Michaelis-Menten metabolic constants. Matlab® simulation software was used to integrate the mass balance equations and to perform the global optimizations using MEIGO (MEtaheuristics for systems biology and bIoinformatics Global Optimization – Version 64bit, R2016A), a toolbox written for Matlab®). The cost function used the chamber time-course data and least squares to minimize the difference between data and simulation values. The final values estimated for V(max) (maximum metabolic rate) and K(m) (affinity constant) were 1.2 mg/h and a range between 0.0005 and 0.6 mg/L, respectively. Also, cost function plots were used to analyze the dose-dependent capacity to estimate V(max) and K(m) within the experimental range used. Sensitivity analysis was used to assess identifiability for both parameters and show these kinetic data may not be sufficient to identify K(m). The importance of an accurate estimation of metabolism using vapor uptake data is discussed. In summary, this work should help toxicologists interested in optimization techniques understand the overall process employed when calibrating metabolic parameters in a PBPK model with inhalation data.

Despite the plethora of studies discussing the benefits of vitamin D on physiological functioning, few mathematical models of vitamin D predict the response of the body on low-concentration supplementation of vitamin D under sunlight-restricted conditions. This study developed a physiologically based pharmacokinetic (PBPK) model utilizing published human data on the metabolic cascade of orally derived, low-concentration (placebo, 5 μg and 10 μg) supplementation of vitamin D over the course of 28 days in the absence of sunlight. Vitamin D and its metabolites are highly lipophilic and binding assays of these compounds in serum may not account for binding by lipids and additional proteins. To compensate for the additional bound amounts, this study allowed the effective adipose-plasma partition coefficient to vary dynamically with the concentration of each compound in serum utilizing the Hill equation for binding. Through incorporating the optimized parameters with the adipose partition coefficient adaptation to the PBPK model, this study was able to fit serum concentration data for circulating vitamin D at all three supplementation concentrations within confidence intervals of the data. Copyright © 2017 John Wiley & Sons, Ltd.

Lindane is a neurotoxicant used for the treatment of lice and scabies present on human skin. Due to its pharmaceutical application, an extensive pharmacokinetic database exists in humans. Mathematical diffusion models allow for calculation of lindane skin permeability coefficients using human kinetic data obtained from in vitro and in vivo experimentation as well as a default compound-specific calculation based on physicochemical characteristics used in the absence of kinetic data. A dermal model was developed to describe lindane diffusion into the skin, where the skin compartment consisted of homogeneous dermal tissue. This study utilized Fick's law of diffusion along with chemical binding to protein and lipids to determine appropriate dermal absorption parameters which were then incorporated into a physiologically based pharmacokinetic (PBPK) model to describe in vivo kinetics. The estimation of permeability coefficients using chemical binding in combination with in vivo data demonstrates the advantages of combining physiochemical properties with a PBPK model to predict dermal absorption.

Approaches for extrapolating in vitro toxicity testing results for prediction of human in vivo outcomes are needed. The purpose of this case study was to employ in vitro toxicokinetics and PBPK modeling to perform in vitro to in vivo extrapolation (IVIVE) of lindane neurotoxicity. Lindane cell and media concentrations in vitro, together with in vitro concentration-response data for lindane effects on neuronal network firing rates, were compared to in vivo data and model simulations as an exercise in extrapolation for chemical-induced neurotoxicity in rodents and humans. Time- and concentration-dependent lindane dosimetry was determined in primary cultures of rat cortical neurons in vitro using “faux” (without electrodes) microelectrode arrays (MEAs). In vivo data were derived from literature values, and physiologically based pharmacokinetic (PBPK) modeling was used to extrapolate from rat to human. The previously determined EC{sub 50} for increased firing rates in primary cultures of cortical neurons was 0.6 μg/ml. Media and cell lindane concentrations at the EC{sub 50} were 0.4 μg/ml and 7.1 μg/ml, respectively, and cellular lindane accumulation was time- and concentration-dependent. Rat blood and brain lindane levels during seizures were 1.7–1.9 μg/ml and 5–11 μg/ml, respectively. Brain lindane levels associated with seizures in rats and those predicted formore » humans (average = 7 μg/ml) by PBPK modeling were very similar to in vitro concentrations detected in cortical cells at the EC{sub 50} dose. PBPK model predictions matched literature data and timing. These findings indicate that in vitro MEA results are predictive of in vivo responses to lindane and demonstrate a successful modeling approach for IVIVE of rat and human neurotoxicity. - Highlights: • In vitro to in vivo extrapolation for lindane neurotoxicity was performed. • Dosimetry of lindane in a micro-electrode array (MEA) test system was assessed. • Cell concentrations at the MEA EC{sub 50} equaled rat brain levels associated with seizure. • PBPK-predicted human brain levels at seizure also equaled EC{sub 50} cell concentrations. • In vitro MEA results are predictive of lindane in vivo dose–response in rats/humans.« less

Despite the plethora of studies discussing the benefits of vitamin D on physiological functioning, few mathematical models of vitamin D predict the response of the body on low-concentration supplementation of vitamin D under sunlight-restricted conditions. This study developed a physiologically based pharmacokinetic (PBPK) model utilizing published human data on the metabolic cascade of orally derived, low-concentration (placebo, 5 μg and 10 μg) supplementation of vitamin D over the course of 28 days in the absence of sunlight. Vitamin D and its metabolites are highly lipophilic and binding assays of these compounds in serum may not account for binding by lipids and additional proteins. To compensate for the additional bound amounts, this study allowed the effective adipose-plasma partition coefficient to vary dynamically with the concentration of each compound in serum utilizing the Hill equation for binding. Through incorporating the optimized parameters with the adipose partition coefficient adaptation to the PBPK model, this study was able to fit serum concentration data for circulating vitamin D at all three supplementation concentrations within confidence intervals of the data. Copyright © 2017 John WileySons, Ltd.

Background: The Ramazzini Institute (RI) has completed nearly 400 cancer bioassays on > 200 compounds. The European Food Safety Authority (EFSA) and others have suggested that study design and protocol differences between the RI and other laboratories by may contribute to controversy regarding cancer hazard findings, principally findings on lymphoma/leukemia diagnoses. Objective: We aimed to evaluate RI study design, protocol differences, and accuracy of tumor diagnoses for their impact on carcinogenic hazard characterization. Methods: We analyzed the findings from a recent Pathology Working Group (PWG) review of RI procedures and tumor diagnoses, evaluated consistency of RI and other laboratory findings for chemicals identified by the RI as positive for lymphoma/leukemia, and examined evidence for a number of other issues raised regarding RI bioassays. The RI cancer bioassay design and protocols were evaluated in the context of relevant risk assessment guidance from international authorities. Discussion: Although the PWG identified close agreement with RI diagnoses for most tumor types, it did not find close agreement for lymphoma/leukemia of the respiratory tract or for neoplasms of the inner ear and cranium. Here we discuss a) the implications of the PWG findings, particularly lymphoma diagnostic issues; b) differences between RI studies and those from other laboratories that are relevant to evaluating RI cancer bioassays; and c) future work that may help resolve some concerns. Conclusions: We concluded that a) issues related to respiratory tract infections have complicated diagnoses at that site (i.e., lymphoma/leukemia), as well as for neoplasms of the inner ear and cranium, and b) there is consistency and value in RI studies for identification of other chemical-related neoplasia. Citation: Gift JS, Caldwell JC, Jinot J, Evans MV, Cote I, Vandenberg JJ. 2013. Scientific considerations for evaluating cancer bioassays conducted by the Ramazzini Institute. Environ Health Perspect 121:1253–1263; http://dx.doi.org/10.1289/ehp.1306661

Background: In support of the Integrated Risk Information System (IRIS), the U.S. Environmental Protection Agency (EPA) completed a toxicological review of trichloroethylene (TCE) in September 2011, which was the result of an effort spanning > 20 years. Objectives: We summarized the key findings and scientific issues regarding the human health effects of TCE in the U.S. EPA’s toxicological review. Methods: In this assessment we synthesized and characterized thousands of epidemiologic, experimental animal, and mechanistic studies, and addressed several key scientific issues through modeling of TCE toxicokinetics, meta-analyses of epidemiologic studies, and analyses of mechanistic data. Discussion: Toxicokinetic modeling aided in characterizing the toxicological role of the complex metabolism and multiple metabolites of TCE. Meta-analyses of the epidemiologic data strongly supported the conclusions that TCE causes kidney cancer in humans and that TCE may also cause liver cancer and non-Hodgkin lymphoma. Mechanistic analyses support a key role for mutagenicity in TCE-induced kidney carcinogenicity. Recent evidence from studies in both humans and experimental animals point to the involvement of TCE exposure in autoimmune disease and hypersensitivity. Recent avian and in vitro mechanistic studies provided biological plausibility that TCE plays a role in developmental cardiac toxicity, the subject of substantial debate due to mixed results from epidemiologic and rodent studies. Conclusions: TCE is carcinogenic to humans by all routes of exposure and poses a potential human health hazard for noncancer toxicity to the central nervous system, kidney, liver, immune system, male reproductive system, and the developing embryo/fetus.

We have developed a comprehensive, Bayesian, PBPK model-based analysis of the population toxicokinetics of trichloroethylene (TCE) and its metabolites in mice, rats, and humans, considering a wider range of physiological, chemical, in vitro, and in vivo data than any previously published analysis of TCE. The toxicokinetics of the "population average," its population variability, and their uncertainties are characterized in an approach that strives to be maximally transparent and objective. Estimates of experimental variability and uncertainty were also included in this analysis. The experimental database was expanded to include virtually all available in vivo toxicokinetic data, which permitted, in rats and humans, the specification of separate datasets for model calibration and evaluation. The total combination of these approaches and PBPK analysis provides substantial support for the model predictions. In addition, we feel confident that the approach employed also yields an accurate characterization of the uncertainty in metabolic pathways for which available data were sparse or relatively indirect, such as GSH conjugation and respiratory tract metabolism. Key conclusions from the model predictions include the following: (1) as expected, TCE is substantially metabolized, primarily by oxidation at doses below saturation; (2) GSH conjugation and subsequent bioactivation in humans appear to be 10- to 100-fold greater than previously estimated; and (3) mice had the greatest rate of respiratory tract oxidative metabolism as compared to rats and humans. In a situation such as TCE in which there is large database of studies coupled with complex toxicokinetics, the Bayesian approach provides a systematic method of simultaneously estimating model parameters and characterizing their uncertainty and variability. However, care needs to be taken in its implementation to ensure biological consistency, transparency, and objectivity.

Trichloroethylene (TCE) is a lipophilic solvent rapidly absorbed and metabolized via oxidation and conjugation to a variety of metabolites that cause toxicity to several internal targets. Increases in liver weight (hepatomegaly) have been reported to occur quickly in rodents after TCE exposure, with liver tumor induction reported in mice after long-term exposure. An integrated dataset for gavage and inhalation TCE exposure and oral data for exposure to two of its oxidative metabolites (TCA and DCA) was used, in combination with an updated and more accurate physiologically-based pharmacokinetic (PBPK) model, to examine the question as to whether the presence of TCA in the liver is responsible for TCE-induced hepatomegaly in mice. The updated PBPK model was used to help discern the quantitative contribution of metabolites to this effect. The update of the model was based on a detailed evaluation of predictions from previously published models and additional preliminary analyses based on gas uptake inhalation data in mice. The parameters of the updated model were calibrated using Bayesian methods with an expanded pharmacokinetic database consisting of oral, inhalation, and iv studies of TCE administration as well as studies of TCE metabolites in mice. The dose-response relationships for hepatomegaly derived from the multi-study database showed that the proportionality of dose to response for TCE- and DCA-induced hepatomegaly is not observed for administered doses of TCA in the studied range. The updated PBPK model was used to make a quantitative comparison of internal dose of metabolized and administered TCA. While the internal dose of TCA predicted by modeling of TCE exposure (i.e., mg TCA/kg-d) showed a linear relationship with hepatomegaly, the slope of the relationship was much greater than that for directly administered TCA. Thus, the degree of hepatomegaly induced per unit of TCA produced through TCE oxidation is greater than that expected per unit of TCA administered directly, which is inconsistent with the hypothesis that TCA alone accounts for TCE-induced hepatomegaly. In addition, TCE-induced hepatomegaly showed a much more consistent relationship with PBPK model predictions of total oxidative metabolism than with predictions of TCE area-under-the-curve in blood, consistent with toxicity being induced by oxidative metabolites rather than the parent compound. Therefore, these results strongly suggest that oxidative metabolites in addition to TCA are necessary contributors to TCE-induced liver weight changes in mice.

Carbon tetrachloride (CCl4) is a toxic chemical that was once used in degreasers and detergents, and some remnants of the chemical may be present in the water supply. Physiologically-based pharmaco...

A physiologically based pharmacokinetic (PBPK) model for the organoarsenical dimethylarsinic acid (DMA(V)) was developed in mice. The model was calibrated using tissue time course data from multiple tissues in mice administered DMA(V) intravenously. The final model structure was based on diffusion limitation kinetics. In general, PBPK models use the assumption of blood flow-limited transport into tissues. This assumption has historically worked for small lipophilic organic solvents. However, the conditions under which flow-limited kinetics occurs and how to distinguish when flow-limited versus diffusion-limited transport is more appropriate, have been rarely evaluated. One important goal of this modeling effort was to systematically evaluate descriptions of flow-limited compared with diffusion-limited tissue distribution for DMA(V), using the relatively extensive pharmacokinetic data available in mice. The diffusion-limited model consistently provided an improved fit over flow-limited simulations when compared with tissue time course iv experimental data. After model calibration, an independent data set obtained by oral gavage of DMA(V), was used to further test model structure. Sensitivity analysis of the two PBPK model structures showed the importance of early time course data collection, and the impact of diffusion for kidney time course data description. In summary, this modeling effort suggests the importance of availability of organ specific time course data sets necessary for the discernment of PBPK modeling structure, motivated by knowledge of biology, and providing necessary feedback between experimental design and biological modelers.

Much progress has been made in understanding the complex pharmacokinetics of trichloroethylene (TCE) . Qualitatively, it is clear that TCE is metabolized to multiple metabolites either locally or into systemic circulation. Many of these metabolites are thought to have toxicologic importance. In addition, efforts to develop physiologically based pharmacokinetic (PBPK) models have led to a better quantitative assessment of the dosimetry of TCE and several of its metabolites. As part of a mini-monograph on key issues in the health risk assessment of TCE, this article is a review of a number of the current scientific issues in TCE pharmacokinetics and recent PBPK modeling efforts with a focus on literature published since 2000. Particular attention is paid to factors affecting PBPK modeling for application to risk assessment. Recent TCE PBPK modeling efforts, coupled with methodologic advances in characterizing uncertainty and variability, suggest that rigorous application of PBPK modeling to TCE risk assessment appears feasible at least for TCE and its major oxidative metabolites trichloroacetic acid and trichloroethanol. However, a number of basic structural hypotheses such as enterohepatic recirculation, plasma binding, and flow- or diffusion-limited treatment of tissue distribution require additional evaluation and analysis. Moreover, there are a number of metabolites of potential toxicologic interest, such as chloral, dichloroacetic acid, and those derived from glutathione conjugation, for which reliable pharmacokinetic data is sparse because of analytical difficulties or low concentrations in systemic circulation. It will be a challenge to develop reliable dosimetry for such cases.

The relationship between the concentration of trichloroethylene (TCE) in the brain and changes in brain function, indicated by the amplitude of steady-state pattern-elicited visual evoked potentials (VEP), was evaluated in Long-Evans rats. VEPs were recorded from visual cortex following stimulation of the eyes and, thus, reflect the function of the afferent visual pathway and, in broad terms, may be indicative of overall brain function. The concentration of TCE in the brain at the time of VEP testing (i.e., momentary brain concentration) was hypothesized to predict the amplitude of the VEP across a range of inhalation concentrations, both during and after exposure. Awake restrained rats were exposed to clean air or TCE in the following combinations of concentration and duration: 500 ppm (4 h), 1000 ppm (4 h), 2000 (2 h), 3000 ppm (1.3 h), 4000 ppm (1 h), and 5000 ppm (0.8 h). VEPs were recorded several times during the exposure session, and afterward for experimental sessions of less than 4 h total duration (i.e., concentrations from 2000 to 5000 ppm). The sample collection time for each VEP was about 1 min. Brain concentrations of TCE were predicted using a physiologically based pharmacokinetic (PBPK) model. VEP waveforms were submitted to spectral analysis, and the amplitude of the largest response component, occurring at twice the temporal stimulation rate (F2), was measured. Exposure to all air concentrations of TCE in the study reduced F2 amplitude. The reduction of F2 amplitude was proportional to momentary brain TCE concentration during and after exposure. A logistical function fit to the combined data from all exposure conditions described a statistically significant relationship with 95% confidence limits between brain TCE concentration and F2 amplitude. The results support the hypothesis that momentary brain concentration of TCE is an appropriate dose metric to describe the effects of acute TCE inhalation exposure on rat VEPs. The combination of the PBPK model predicting brain TCE concentration from the exposure conditions with the logistical function predicting F2 amplitude from the brain TCE concentration constitute a quantitative exposure-dose-response model describing an acute change in neurological function following exposure to an important hazardous air pollutant.

The potential human health risk(s) from chemical exposure must frequently be assessed under conditions for which adequate human or animal data are not available. The default method for exposure-duration adjustment, based on Haber's rule, C (external exposure concentration) or C(n) (the ten Berge modification) x t (exposure duration) = K (a constant toxic effect), has been criticized for prediction errors. A promising alternative approach to duration adjustment is based on equivalence of internal dose, that is, target-tissue dose levels, across different exposure durations. A proposed methodology for dose-duration adjustments for acute exposure guideline levels (AEGLs) based on physiologically based pharmacokinetic (PBPK) estimates of dose is illustrated with trichloroethylene (TCE). Steps in this methodology include: (1) selection and evaluation, or development and evaluation, of an appropriate PBPK model; (2) determination of an appropriate measure of internal dose; (3) estimation with the PBPK model of the tissue dose (the target tissue dose) resulting from the external exposure conditions (concentration, duration) of the critical effect; (4) estimation of the external exposure concentrations required to achieve tissue doses equivalent to the target tissue dose at exposure durations of interest; and (5) evaluation of sources of variability and uncertainty. For TCE, this PBPK modeling approach has allowed determination of dose metrics predictive of the acute neurotoxic effects of TCE and dose-duration adjustments based on estimates of internal dose.

1,1-Dichloropropene (1,1-DCPe) is a contaminant of some source waters used to make drinking water. Because of this and the fact that no toxicological data were available for this compound, which is structurally similar to the rodent carcinogen 1,3-dichloropropene (1,3-DCPe), 1,1-DCPe was placed on the Contaminant Candidate List of the US Environmental Protection Agency. Consequently, we have performed a hazard characterization of 1,1-DCPe by evaluating its mutagenicity in the Salmonella assay and its DNA damaging (comet assay) and apoptotic (caspase assay) activities in human lymphoblastoid cells. In Salmonella, 1,1-DCPe was not mutagenic in strains TA98, TA100, TA1535, or TA104 +/-S9 mix. However, it was clearly mutagenic in strain RSJ100, which expresses the rat GSTT1-1 gene. 1,1-DCPe did not induce DNA damage in GSTT1-1-deficient human lymphoblastoid cells, and it induced apoptosis in these cells only at 5 mM. Consistent with its mutagenesis in RSJ100, 1,1-DCPe reacted with glutathione (GSH) in vitro, suggesting an addition-elimination mechanism to account for the detected GSH conjugate. 1,1-DCPe was approximately 5000 times more mutagenic than its ethene congener 1,1-dichloroethylene (1,1-DCE or vinylidene chloride). Neither 1,1-DCE nor 1,3-DCPe showed enhanced mutagenicity in strain RSJ100, indicating a lack of activation of these congeners by GSTT1-1. Thus, 1,1-DCPe is a base-substitution mutagen requiring activation by GSTT1-1, possibly involving the production of a reactive episulfonium ion. This bioactivation mechanism of 1,1-DCPe is different from that of its congeners 1,1-DCE and 1,3-DCPe. The presence of 1,1-DCPe in source waters could pose an ecological or human health risk. Occurrence data for 1,1-DCPe in finished drinking water are needed to estimate human exposure to, and possible health risks from, this mutagenic compound.

A physiologically based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine the mechanism of metabolic interactions occurring during simultaneous exposures to the organic solvents chloroform and trichloroethylene (TCE). Visualization-based sensitivity and identifiability analyses of the model were performed to determine the conditions under which four inhibitory parameters describing inhibitor binding could be estimated. The sensitivity methods were used to reduce the 4-parameter estimation problem into two distinct 2-parameter problems. The inhibitory parameters were then estimated from multiple closed-chamber gas-uptake experiments using graphical methods. The estimated values of the four inhibitory parameters predicted that chloroform and TCE interact in a competitive manner. Based on the model analysis, we present recommendations for the design of experiments for determination of inhibition mechanism in binary chemical mixtures. We assert that a thorough analysis of the parameter-dependent sensitivity and identifiability characteristics can be used to plan efficient experimental protocols for the quantitative analysis of inhalation pharmacokinetics.

beta-Chloroprene (2-chloro-1,3-butadiene; CD), which is used in the synthesis of polychloroprene, caused significant incidences of several tumor types in B6C3F1 mice and Fischer rats, but not in Wistar rats or Syrian hamsters. This project investigates the relevance of the bioassay lung tumor findings to human health risk by developing a physiologically based toxicokinetic (PBTK) model and exploring a tissue specific exposure-dose-response relationship. Key steps included identification of the plausible genotoxic mode of action, experimental quantification of tissue-to-air partition coefficients, scaling of in vitro parameters of CD metabolism for input into the PBTK model, comparing the model with in vivo experimental gas uptake data, selecting an appropriate tissue dosimetric, and predicting a corresponding human exposure concentration. The total daily milligram amount of CD metabolized per gram of lung was compared with the animal bioassay response data, specifically combined bronchiolar adenoma/carcinoma. The faster rate of metabolism in mouse lung agreed with the markedly greater incidence of lung tumors compared with the other rodent species. A lung tissue dose was predicted for the combined rodent lung tumor bioassay data at a 10% benchmark response. A human version of the PBTK model predicted that the lung tissue dose in humans would be equivalent to continuous lifetime daily exposure of 23 ppm CD. PBTK model sensitivity analysis indicated greater dependence of model predictions of dosimetry on physiological than biochemical parameters. The combined analysis of lung tumor response across species using the PBTK-derived internal dose provides an improved alternative to default pharmacokinetic interspecies adjustments for application to human health risk assessment.

Risk assessments often must consider exposures that vary over time or for which the exposure duration of concern differs from the available data, and a variety of extrapolation procedures have been devised accordingly. The present experiments explore the relationship(s) between exposure concentration (C) and time (t) to investigate procedures for assessing the risks of short-term solvent exposures. The first hypothesis tested was that the product of C x t would produce a constant health effect (Haber's rule). The second hypothesis tested was that exposure conditions produce effects in proportion to the tissue concentrations created. Awake, adult, male Long-Evans (LE) rats were exposed to trichloroethylene (TCE) vapor in a head-only exposure chamber while pattern onset/offset visual evoked potentials (VEPs) were recorded. Exposure conditions were designed to provide C x t products of 0 ppm/h (0 ppm for 4 h) or 4000 ppm/h created through four exposure scenarios: 1000 ppm for 4 h; 2000 ppm for 2 h; 3000 ppm for 1.3 h; or 4000 ppm for 1h (n = 9-10/concentration). The amplitude of the VEP frequency double component (F2) was decreased significantly by exposure; this decrease was related to C but not to t or to the C x t product, indicating that Haber's rule did not hold. The mean amplitude (+/- SEM in muV) of the F2 component in the control and treatment groups measured 4.4 +/- 0.5 (0 ppm/4 h), 3.1 +/- 0.5 (1000 ppm/4 h), 3.1 +/- 0.4 (2000 ppm/2 h), 2.3 +/- 0.3 (3000 ppm/1.3 h), and 1.9 +/- 0.4 (4000 ppm/1 h). A physiologically based pharmacokinetic (PBPK) model was used to estimate the concentrations of TCE in the brain achieved during each exposure condition. The F2 amplitude of the VEP decreased monotonically as a function of the estimated peak brain concentration but was not related to the area under the curve (AUC) of the brain TCE concentration. In comparison to estimates from the PBPK model, extrapolations based on Haber's rule yielded approximately a 6-fold error in estimated exposure duration when extrapolating across only a 4-fold change in exposure concentration. These results indicate that the use of a linear form of Haber's rule will not predict accurately the risks of acute exposure to TCE, nor will an estimate of AUC of brain TCE. However, an estimate of the brain TCE concentration at the time of VEP testing predicted the effects of TCE across exposure concentrations and durations.

Haber's rule as commonly interpreted in inhalation toxicology, can be stated as exposure concentration times duration equals a constant biological effect, or C × t = k . In other words, identical products of concentration and duration lead to the same effect. The goals of this paper are to develop a biological and pharmacokinetic modeling approach for chloroform, and to evaluate Haber's rule for different ages by taking into account the physiological changes due to growth and aging in rats. Three-dimensional dose–response surfaces for liver toxicity were generated for each age group of interest: adolescent, adult, and senescent rats. The three-dimensional surfaces were then characterized with a generalized description of Haber's rule for each age group. The simulations suggest that adolescent rats need higher exposure levels in order to achieve similar levels of liver damage compared to adults or senescent rats, if the comparison is made using the same exposure length. In summary, a pharmacokinetic modeling approach with a biological framework including the chemical's mode of action, was used to relate concentration, exposure duration and effect. Major advantages of this approach include: the potential ability to extrapolate to humans, the inclusion of aging in the simulations, and the ability to summarize the results using a generalized form of Haber's rule.

Arsenic (iAs) is a known human carcinogen and widespread contaminant in drinking water. To provide a quantitative framework for experimental design and hypothesis testing, we developed a pharmacokinetic model describing the uptake and methylation of arsenite (AsIII) in primary rat hepatocytes. Measured metabolites were inorganic As (iAs), mono-methylated As (MMA), and di-methylated As (DMA) concentration in cells and media. Transport and methylation parameters were estimated from time course data for iAs, MMA, and DMA at three initial media As(III) concentrations (0.1, 0.4, 1.0 μM). Inhibition of the formation DMA from MMA by As(III) was necessary to adequately describe the data. The data were consistent with multiple types of inhibition, although uncompetitive inhibition provided a slightly better fit. Model simulations indicate that cellular MMA (cMMA) is a key arsenical to measure; measurement of cMMA in the 4–6 hr time range using an initial concentration of 1.4 μM AsIII would provide the best experimental conditions to distinguish uncompetitive from other types of inhibition. Due to the large number of model parameters estimated from the data, we used sensitivity analysis to determine the influential parameters. Use of sensitivity surfaces facilitated the comparison of parameters over time and across doses. Predicted model responses were most sensitive to influx and efflux parameters, suggesting that transport processes are critical in determining cellular arsenical concentrations. These high sensitivities imply that independent experiments to estimate these parameters with greater certainty may be crucial for refinement of this model and to extend this model to describe methylation and transport in human hepatocytes.

In this paper we present three physiologically based pharmacokinetic (PBPK) models for the systemic transport of trichloroethylene (TCE), with a focus on the adipose, or fat tissue. TCE is a widespread environmental contaminant, and has been shown to produce toxic effects in both animals and humans. A key characteristic of TCE is its tendency to accumulate in fat tissue, which has a major impact on the overall systemic disposition of TCE. Here we use PBPK models to predict the dynamics of TCE in the various tissues and organs, including the adipose tissue. The first model utilizes the standard 'perfusion-limited' compartmental model for the fat tissue, while the second model uses a 'diffusion-limited' model to describe the transport through the adipose tissue. Both of these ODE models are based on 'well-mixed' and rapid equilibrium assumptions, and do not take into account the specific and largely heterogeneous physiology of adipose tissue. The third model we discuss is a PBPK hybrid model with an axial-dispersion type model for the adipose tissue. This PDE-based model is designed to capture key physiological heterogeneities of fat tissue, including widely varying fat cell sizes, lipid distribution, and blood flow properties. Model simulations demonstrate that this model may be well-suited to predict the experimental behavior of TCE in adipose tissue using parameter estimation techniques.

The accurate quantification of metabolism is essential for performing dosimetry of volatile organic compounds because metabolism is typically required for toxicity. One approach available to measure metabolism is gas uptake analysis, which combines experimental data with physiologically based pharmacokinetic (PBPK) modeling in order to obtain metabolic parameters. One of the primary concerns when using modeling to infer parameter values arises from the uncertainty involved in this process. In this article, we illustrate the use of sensitivity analysis, a numerical technique, typically used to identify optimal exposure times aimed at improving future experiments. This particular analysis was performed using a previously published PBPK model for chloroform, which was chosen as a model volatile compound. In order to illustrate the interpretation of sensitivity coefficients, three different time-course plots are generated for liver concentration by varying the metabolism parameter Vmax plus or minus 10%. We t...

Strategies are needed for assessing the risks of exposures to airborne toxicants that vary over concentrations and durations. The goal of this project was to describe the relationship between the concentration and duration of exposure to inhaled trichloroethylene (TCE), a representative volatile organic chemical, tissue dose as predicted by a physiologically based pharmacokinetic model, and neurotoxicity. Three measures of neurotoxicity were studied: hearing loss, signal detection behavior, and visual function. The null hypothesis was that exposure scenarios having an equivalent product of concentration and duration would produce equal toxic effects, according to the classic linear form of Haber's Rule ((italic)C(/italic) times t = k), where C represents the concentration, t, the time (duration) of exposure, and k, a constant toxic effect. All experiments used adult male, Long-Evans rats. Acute and repeated exposure to TCE increased hearing thresholds, and acute exposure to TCE impaired signal detection behavior and visual function. Examination of all three measures of neurotoxicity showed that if Haber's Rule were used to predict outcomes across exposure durations, the risk would be overestimated when extrapolating from shorter to longer duration exposures, and underestimated when extrapolating from longer to shorter duration exposures. For the acute effects of TCE on behavior and visual function, the estimated concentration of TCE in blood at the time of testing correlated well with outcomes, whereas cumulative exposure, measured as the area under the blood TCE concentration curve, did not. We conclude that models incorporating dosimetry can account for differing exposure scenarios and will therefore improve risk assessments over models considering only parameters of external exposure.

Historically, a number of different software packages running on a variety of hardware platforms have been used for model simulation. SimuSolv found wide use because of its broad capabilities, including optimization, statistical analysis, and formalized sensitivity analysis as well as the capacity to incorporate user-supplied subroutines. However, in the early 1990s, SimuSolv development ceased and a final version was released in 1993. Thus SimuSolv will not be developed for newer platforms and operating systems. In this article, we compare and contrast the use of SimuSolv and Matlab (The MathWorks, Natick, MA) for physiologically based pharmacokinetic (PBPK) model implementation with respect to parameter estimation (optimization) and sensitivity analysis using a PBPK model for trichloroethylene (TCE). In both packages, it is possible to code PBPK models, run simulations, estimate parameters, and do sensitivity analysis.The key difference is the additional programming required in Matlab. Since Matlab does...

The purpose of this study was to determine the effects of maturation and aging on cardiac output, the distribution of cardiac output, tissue blood flow (determined by using the radioactive-microsphere technique), and body composition in conscious juvenile (2-mo-old), adult (6-mo-old), and aged (24-mo-old) male Fischer-344 rats. Cardiac output was lower in juvenile rats (51 ± 4 ml/min) than in adult (106 ± 5 ml/min) or aged (119 ± 10 ml/min) rats, but cardiac index was not different among groups. The proportion of cardiac output going to most tissues did not change with increasing age. However, the fraction of cardiac output to brain and spinal cord tissue and to skeletal muscle was greater in juvenile rats than that in the two adult groups. In addition, aged rats had a greater percent cardiac output to adipose tissue and a lower percent cardiac output to cutaneous and reproductive tissues than that in juvenile and adult rats. Differences in age also had little effect on mass-specific perfusion rates in most tissues. However, juvenile rats had lower flows to the pancreas, gastrointestinal tract, thyroid and parathyroid glands, and kidneys than did adult rats, and aged rats had lower flows to the white portion of rectus femoris muscle, spleen, thyroid and parathyroid glands, and prostate gland than did adult rats. Body mass of juvenile rats was composed of a lower percent adipose mass and a greater fraction of brain and spinal cord, heart, kidney, liver, and skeletal muscle than that of the adult and aged animals. Relative to the young adult rats, the body mass of aged animals had a greater percent adipose tissue mass and a lower percent skeletal muscle and skin mass. These data demonstrate that maturation and aging have a significant effect on the distribution of cardiac output but relatively little influence on mass-specific tissue perfusion rates in conscious rats. The old-age-related alterations in cardiac output distribution to adipose and cutaneous tissues appear to be associated with the increases in percent body fat and the decreases in the fraction of skin mass, respectively, whereas the decrease in the portion of cardiac output directed to reproductive tissue of aged rats appears to be related to a decrease in mass-specific blood flow to the prostate gland.

Gargas et al. (1986) demonstrated that the physiologically based simulation approach could be used to obtain information about rodent in vivo metabolic kinetics from gas uptake data. This statistical approach has been widely used to estimate apparent in vivo metabolic constants for use in physiologically based pharmacokinetics (PBPK) models. Despite extensive use of this methodology and the potential importance of the resulting fitted estimates of metabolic constants to the estimation of health risk, a formal evaluation of the statistical properties of this estimation procedure as applied to gas uptake data has not been performed. This article describes results from a computer simulation study to investigate three important statistical properties of this estimation procedure: bias (whether fitted estimates on average predict the true population mean), efficiency (whether fitted estimates tend to concentrate over a narrow range), and consistency (whether fitted estimates concentrate in a narrower and narro...

Gas uptake studies analyzed by physiologically based pharmacokinetic (PBPK) models have been used to estimate metabolic parameters for many volatiles. The metabolic constants for a saturable pathway (Vmax′ mg/h and Km′, mg/L) and for a first-order process (Kf′ h−1) are typically inferred from the decline in chemical concentration observed in closed chamber exposures. Sensitivity analysis was used to quantify the identifiability of these metabolic parameters with PBPK models for three compounds: chloroform (Vmax = 2.25 mg/h), dichloromethane (Vmax = 1.33 mg/h), and carbon tetrachloride (Vmax=0.11 mg/h). Further sensitivity analysis related the increased ability to estimate Vmax for chloroform and dichloromethane with their higher metabolic rates, indicating the value of Vmax to be an important determinant in its identifiability. The optimal experimental concentration needed for estimating Vmax was lower for carbon tetrachloride (12-18 ppm) than for either chloroform (740-770 ppm) or dichloromethane...

This paper describes an automated gas uptake system for pharmacokinetic research with volatile organic compounds, designed to operate within the parameters maintained during conventional whole-body inhalation exposures according to the Good Laboratory Practices (GLP) guidelines. Benefits are twofold: (1) to ensure that animals are tested under the same widely accepted guidelines, and (2) to minimize the number of animals required to perform a study, by allowing direct comparison of results from gas uptake studies with results from other inhalation toxicology studies and use of animals from gas uptake experiments for postexposure toxicological testing. Other features implemented in the chamber design improve the ease of use and productivity of the system. These include provisions to adapt the apparatus for use in different pharmacokinetic experimental protocols, automation of data acquisition and oxygen control during exposures, and automated calculation of exposure summary statistics and graphics using a ...

Bromochloromethane (BCM) is a volatile compound and a by-product of disinfection of water by chlorination. Physiologically based pharmacokinetic (PBPK) models are used in risk assessment applications. An updated PBPK model for BCM is generated and applied to hypotheses testing calibrated using vapor uptake data. The two different metabolic hypotheses examined are (1) a two-pathway model using both CYP2E1 and glutathione transferase enzymes and (2) a two-binding site model where metabolism can occur on one enzyme, CYP2E1. Our computer simulations show that both hypotheses describe the experimental data in a similar manner. The two pathway results were comparable to previously reported values (Vmax=3.8 mg/hour,Km=0.35 mg/liter, andkGST=4.7 /hour). The two binding site results wereVmax⁡1=3.7 mg/hour,Km⁡1=0.3 mg/hour, CL2= 0.047 liter/hour. In addition, we explore the sensitivity of different parameters for each model using our obtained optimized values.

Physiologically based Pharmacokinetic (PBPK) models are used for predictions of internal or target dose from environmental and pharmacologic chemical exposures. Their use in human risk assessment is dependent on the nature of databases (animal or human) used to develop and test them, and includes extrapolations across species, experimental paradigms, and determination of variability of response within human populations. Integration of state-of-the science PBPK modeling with emerging computational toxicology models is critical for extrapolation betweenin vitroexposures,in vivophysiologic exposure, whole organism responses, and long-term health outcomes. This special issue contains papers that can provide the basis for future modeling efforts and provide bridges to emerging toxicology paradigms. In this overview paper, we present an overview of the field and introduction for these papers that includes discussions of model development, best practices, risk-assessment applications of PBPK models, and limitations and bridges of modeling approaches for future applications. Specifically, issues addressed include: (a) increased understanding of human variability of pharmacokinetics and pharmacodynamics in the population, (b) exploration of mode of action hypotheses (MOA), (c) application of biological modeling in the risk assessment of individual chemicals and chemical mixtures, and (d) identification and discussion of uncertainties in the modeling process.

Physiologically based pharmacokinetic (PBPK) models developed from gas uptake experiments have been used to estimate metabolic parameters for volatile organic compounds. Due to the potential application of PBPK models to estimate metabolic bioactivation constants in humans, it is important to understand the complex nature of these models and the resulting estimates. Adult male F344 rats (165-205 g) were individually exposed to carbon tetrachloride (CC14) in gas uptake systems. Three rats at each concentration were exposed for 6 hr to initial concentrations of 25, 100, 250, and 1000 ppm CCl4. Partition coefficient determinations were performed by the vial equilibration technique and used as model inputs. Computer optimizations with the means of each initial chamber concentration at each time point resulted in an estimate of Vmax of 0.11 mg/hr (Vmaxc = 0.37 mg/hr/kg) and Km of 1.3 mg/liter. To determine the effect of individual animal variation in Vmax optimizations were also performed with the mean ± SD, resulting in Vmax estimates of 0.09 and 0.12 mg/hr, respectively. Similar analysis resulted in Km estimates of 0.98 and 1.58 mg/liter. The results of the sensitivity analysis were concentration dependent for CCl4. These results show Vmax and Km to be most accurately detected at lower initial chamber concentrations. Results of the sensitivity analysis at the lowest concentration established the following model input hierarchy: blood to air partition > fat partition and fat volume fraction > slowly perfused partition, ventilation rate, cardiac output, fat blood flow percentage > liver blood flow percentage and slowly perfused blood flow percentage. Further sensitivity analysis determined Vmax and Km to be highly correlated when using gas uptake technology and point to the need to an independent estimate for either constant. In summary, the application of sensitivity analysis to PBPK modeling resulted in an increased understanding of factors governing the estimation of metabolic parameters.

Dichloromethane (DCM, methylene chloride) is a lipophilic volatile compound readily absorbed and then metabolized to several metabolites that may lead to chronic toxicity in different target organs. Physiologically based pharmacokinetic (PBPK) models are useful tools for calculation of internal and target organ doses of parent compound and metabolites. PBPK models, coupled with in vivo inhalation gas-uptake data, can be useful to estimate total metabolism. Previously, such an approach was used to make predictions regarding the metabolism and to make subsequent inferences of DCM's mode of action for toxicity. However, current evidence warrants re-examination of this approach. The goal of this work was to examine two different hypotheses for DCM metabolism in mice. One hypothesis describes two metabolic pathways: one involving cytochrome P450 2E1 (CYP2E1) and a second glutathione (GSH). The second metabolic hypothesis describes only one pathway mediated by CYP2E1 that includes multiple binding sites. The results of our analysis show that the in vivo gas-uptake data fit both hypotheses well and the traditional analysis of the chamber concentration data is not sufficient to distinguish between them. Gas-uptake data were re-analyzed by construction of a velocity plot as a function of increasing DCM initial concentration. The velocity (slope) analysis revealed that there are two substantially different phases in velocity, one rate for lower exposures and a different rate for higher exposures. The concept of a “metabolic switch,” namely that due to conformational changes in the enzyme after one site is occupied – a different metabolic rate is seen – is also consistent with the experimental data. Our analyses raise questions concerning the importance of GSH metabolism for DCM. Recent research results also question the importance of this pathway in the toxicity of DCM. GSH-related DNA adducts were not formed after in vivo DCM exposure in mice and DCM-induced DNA damage has been detected in human lung cultures without GSH metabolism. In summary, a revised/updated metabolic hypothesis for DCM has been examined using in vivo inhalation data in mice combined with PBPK modeling that is consistent with up-to-date models of the active site for CYP2E1 and suggests that this pathway is the major metabolizing pathway for DCM metabolism.

2,2,4-Trimethylpentane (TMP) is a volatile colorless liquid used primarily to increase the octane rating of combustible fuels. TMP is released in the environment through the manufacture, use, and disposal of products associated with the gasoline and petroleum industry. Short-term inhalation exposure to TMP (4 h;1000 ppm) caused sensory and motor irritations in rats and mice. Like many volatile hydrocarbons, acute exposure to TMP may also be expected to alter neurological functions. To estimate in vivo metabolic kinetics of TMP and to predict its target tissue dosimetry during inhalation exposures, a physiologically based pharmacokinetic (PBPK) model was developed for the chemical in Long-Evans male rats using closed-chamber gas-uptake experiments. Gas-uptake experiments were conducted in which rats (80-90 days old) were exposed to targeted initial TMP concentrations of 50, 100, 500, and 1000 ppm. The model consisted of compartments for the closed uptake chamber, lung, fat, kidney, liver, brain, and rapidly and slowly perfused tissues. Physiological parameters were obtained from literature. Partition coefficients for the model were experimentally determined for air/blood, fat, liver, kidney, muscle, and brain using vial equilibration methods. Common to other hydrocarbons, metabolism of TMP via oxidative reactions is assumed to mainly occur in the liver. The PBPK model simulations of the closed chamber data were used to estimate in vivo metabolic parameters for TMP in male Long-Evans rats.

Trichloroethylene (TCE) is an industrial chemical and an environmental contaminant. TCE and its metabolites may be carcinogenic and affect human health. Physiologically based pharmacokinetic (PBPK) models that differ in compartmentalization are developed for TCE metabolism in humans, and the focus of this investigation is to evaluate alternative models. The two models formulated differ in the compartmentalization of metabolites; more specifically, one model has compartments for all chemicals and the other model has only a generalized body compartment for each the metabolites and contains multiple compartments for the parent, TCE. The models are compared through sensitivity analyses in order to selectively discriminate with regards to model structure. Sensitivities to a parameter of cardiac output (Qcc) are calculated, and the more compartmentalized model predictions for excretion show lower sensitivity to changes in this parameter. Values of Qcc used in the sensitivity analyses are specifically chosen to be applicable to adults of ages into the low 60s. Since information about cardiac output across a population is not often incorporated into a PBPK model, the more compartmentalized ("full") model is probably a more appropriate mathematical description of TCE metabolism, but further study may be necessary to decide which model is a more reasonable option if distributional information about Qcc is used. The study is intended to illustrate how sensitivity analysis can be used in order to make appropriate decisions about model development when considering physiological parameters than vary across the population.

In their 2004 article, Clewell and Andersen provide their perspective on the application of mode-of-action (MOA) and pharmacokinetic considerations in contemporary cancer risk assessment using trichloroethylene (TCE) as a case example. TCE is a complex chemical toxicologically, with multiple metabolites, multiple sites of observed toxicity, and multiple potential MOAs. As scientists who are responsible for revising the U.S. Environmental Protection Agency's draft risk assessment of TCE, we welcome input of the quality to which the Agency is held accountable. However, in our view, Clewell and Andersen do not present a sufficiently current, complete, accurate, and transparent review of the pertinent scientific literature. In particular, their article would need to incorporate substantial recently published scientific information, better support its conclusions about MOA and choice of linear or nonlinear dose-response extrapolation, and increase its transparency as to quantitative analyses in order to make a significant contribution to the scientific discussion of TCE health risks.

Acute Exposure Guideline Level (AEGL) recommendations are developed for 10-minute, 30-minute, 1-hour, 4-hours, and 8-hours exposure durations and are designated for three levels of severity: AEGL-1 represents concentrations above which acute exposures may cause noticeable discomfort including irritation; AEGL-2 represents concentrations above which acute exposure may cause irreversible health effects or impaired ability to escape; and AEGL-3 represents concentrations above which exposure may cause life-threatening health effects or death. The default procedure for setting AEGL values across durations when applicable data are unavailable involves estimation based on Haber's rule, which has an underlying assumption that cumulative exposure is the determinant of toxicity. For acute exposure to trichloroethylene (TCE), however, experimental data indicate that momentary tissue concentration, and not the cumulative amount of exposure, is important. We employed an alternative approach to duration adjustments in which a physiologically-based pharmacokinetic (PBPK) model was used to predict the arterial blood concentrations [TCE a ] associated with adverse outcomes appropriate for AEGL-1, -2, or -3-level effects. The PBPK model was then used to estimate the atmospheric concentration that produces equivalent [TCE a ] at each of the AEGL-specific exposure durations. This approach yielded [TCE a ] values of 4.89 mg/l for AEGL-1, 18.7 mg/l for AEGL-2, and 310 mg/l for AEGL-3. Duration adjustments based on equivalent target tissue doses should provide similar degrees of toxicity protection at different exposure durations.

Chloroform (CHCl3) is a near-ubiquitous environmental contaminant, a by-product of the disinfection of drinking water sources and a commercially important compound. Standards for safe exposure have been established based on information defining its toxicity, which is mediated by metabolites. The metabolism of CHCl3 is via cytochrome P-450 2E1 (CYP2E1)-mediated oxidation to phosgene, which is known to obey a saturable mechanism. CYP2E1 is a highly conserved form, expressed in all mammalian systems studied, and is responsible for the metabolism of a great many low-molecular-weight (halogenated) compounds. However, the Michaelis-Menten rate constants for CHCl3 oxidation have not been derived in vitro, and the specific activity of CYP2E1 toward CHCl3 has not been reported. In this investigation with microsomal protein (MSP), apparent Vmax values of 27.6 and 28.3 nmol/h/mg MSP and apparent K(m) values of 1 and 0.15 microM in rats and human organ donors, respectively, were demonstrated. The specific activity of CYP2E1 toward CHCl3 in rats and humans was 5.29 and 5.24 pmol/min/pmol CYP2E1, respectively. Toluene metabolism to benzyl alcohol (BA), another CYP2E1-dependent reaction, was also highly dependent on CYP2E1 content in humans, and was more efficient than was CHCl3 metabolism. The specific activity of human CYP2E1 toward toluene metabolism in human MSP was 23 pmol/min/pmol CYP2E1. These results demonstrate that differences in CYP2E1 content of MSP among individuals and between species are largely responsible for observed differences in toluene and CHCl3 metabolism in vitro.

beta-Chloroprene (2-chloro-1,3-butadiene; CD), which is used in the synthesis of polychloroprene, caused significant incidences of several tumor types in B6C3F1 mice and Fischer rats, but not in Wistar rats or Syrian hamsters. This project investigates the relevance of the bioassay lung tumor findings to human health risk by developing a physiologically based toxicokinetic (PBTK) model and exploring a tissue specific exposure-dose-response relationship. Key steps included identification of the plausible genotoxic mode of action, experimental quantification of tissue-to-air partition coefficients, scaling of in vitro parameters of CD metabolism for input into the PBTK model, comparing the model with in vivo experimental gas uptake data, selecting an appropriate tissue dosimetric, and predicting a corresponding human exposure concentration. The total daily milligram amount of CD metabolized per gram of lung was compared with the animal bioassay response data, specifically combined bronchiolar adenoma/carcinoma. The faster rate of metabolism in mouse lung agreed with the markedly greater incidence of lung tumors compared with the other rodent species. A lung tissue dose was predicted for the combined rodent lung tumor bioassay data at a 10% benchmark response. A human version of the PBTK model predicted that the lung tissue dose in humans would be equivalent to continuous lifetime daily exposure of 23 ppm CD. PBTK model sensitivity analysis indicated greater dependence of model predictions of dosimetry on physiological than biochemical parameters. The combined analysis of lung tumor response across species using the PBTK-derived internal dose provides an improved alternative to default pharmacokinetic interspecies adjustments for application to human health risk assessment.

Cytochrome P450-dependent oxidation and glutathione (GSH)-dependent conjugation are the primary routes of metabolism of haloalkanes. Using rat liver microsomes and cytosol, we investigated the metabolism of two halopropanes found on the U.S. Environmental Protection Agency Contaminant Candidate List, 1,3-dichloropropane (1,3-DCP) and 2,2-dichloropropane (2,2-DCP). An automated headspace technique using gas chromatography was developed to determine rates of metabolism. Additional dihaloalkanes (1,2-dichloroethane, 1,2-dichloropropane, 1,4-dichlorobutane, 1,2-dibromoethane, 1,2-dibromopropane, 1,4-dibromobutane) were evaluated to assess structure-activity relationships. In general, brominated dihaloalkanes were eliminated from rat cytosol faster than chlorinated dihaloalkanes, reflecting the expected halide order of reactivity (Br > Cl). Furthermore, the rate of GSH conjugation was proportional to alpha,omega-haloalkane chain length. The clearance of 1,3-DCP via the GSH conjugation pathway (1.6 x 10(-4) l/h/mg cytosol protein) was minor relative to the P450 pathway (2.8 x 10(-2) l/h/mg microsomal protein). In contrast, we did not observe metabolism of 2,2-DCP via the GSH-dependent conjugation pathway and observed only a minor level of clearance via the P450 pathway (7 x 10(-4) l/h/mg microsomal protein). Neither compound was mutagenic in various strains of Salmonella, including those containing GSTT1-1, indicating that GSTT1-1 does not metabolize 1,3-DCP or 2,2-DCP to mutagens. Analysis of the reaction products of 1,3-DCP and GSH in cytosol by liquid chromatography/mass spectrometry revealed significant production of S-(3-chloropropyl) glutathione conjugate, indicating that the conjugate half-mustard does not rearrange to form a sulfonium ion, as typically occurs with vicinal dihaloalkanes.

Arsenic (iAs) is a known human carcinogen and widespread contaminant in drinking water. To provide a quantitative framework for experimental design and hypothesis testing, we developed a pharmacokinetic model describing the uptake and methylation of arsenite (AsIII) in primary rat hepatocytes. Measured metabolites were inorganic As (iAs), mono-methylated As (MMA), and di-methylated As (DMA) concentration in cells and media. Transport and methylation parameters were estimated from time course data for iAs, MMA, and DMA at three initial media As(III) concentrations (0.1, 0.4, 1.0 microM). Inhibition of the formation DMA from MMA by As(III) was necessary to adequately describe the data. The data were consistent with multiple types of inhibition, although uncompetitive inhibition provided a slightly better fit. Model simulations indicate that cellular MMA (cMMA) is a key arsenical to measure; measurement of cMMA in the 4-6 hr time range using an initial concentration of 1.4 microM AsIII would provide the best experimental conditions to distinguish uncompetitive from other types of inhibition. Due to the large number of model parameters estimated from the data, we used sensitivity analysis to determine the influential parameters. Use of sensitivity surfaces facilitated the comparison of parameters over time and across doses. Predicted model responses were most sensitive to influx and efflux parameters, suggesting that transport processes are critical in determining cellular arsenical concentrations. These high sensitivities imply that independent experiments to estimate these parameters with greater certainty may be crucialfor refinement of this model and to extend this model to describe methylation and transport in human hepatocytes.

A physiologically based pharmacokinetic (PBPK) model for trichloroethylene (TCE) in the male Long-Evans (LE) rat was needed to aid in evaluation of neurotoxicity data collected in this rodent stock. The purpose of this study was to develop such a model with the greatest possible specificity for the LE rat. The PBPK model consisted of 5 compartments: brain, fat, slowly perfused tissue, rapidly perfused viscera, and liver. Partition coefficients (blood, fat, muscle, brain, liver) were determined for LE rats. The volumes of the brain, liver, and fat compartments were estimated for each rat, with tissue-specific regression equations developed from measurements made in LE rats. Vapor uptake data from LE rats were used for estimation of Vmaxc. As blood flow values for LE rats were not available, values from Sprague-Dawley (SD) and Fischer-344 (F344) rats were used in separate simulations. The resulting values of Vmaxc were used to simulate tissue (blood, liver, brain, fat) TCE concentrations, which were measured during (5, 20, 60 min) and after (60 min of TCE followed by 60 min of air) flow-through inhalation exposures of LE rats to 200, 2000, or 4000 ppm TCE. Simulation of the experimental data was improved by use of F-344 blood-flow values and the corresponding Vmaxc (8.68 mg/h/kg) compared to use of SD flows and the associated Vmaxc (7.34 mg/h/kg). Sensitivity analysis was used to determine those input parameters with the greatest influence on TCE tissue concentrations. Alveolar ventilation consistently (across exposure concentration, exposure duration, and target tissue) had the greatest impact on TCE tissue concentration. The PBPK model described here is being used to explore the relationship between measures of internal dose of TCE and neurotoxic outcome.

A kinetic model describing the hepatic methylation of arsenite ([As[III]) was developed on the basis of limited data from in vitro mechanistic studies. The model structure is as follows: sequential enzymic methylation of arsenite to its monomethylated (MMA) and dimethylated (DMA) products by first-order and Michaelis-Menten kinetics, respectively; uncompetitive inhibition of the formation of DMA by As(III); and first-order reversible binding of As(III), MMA and DMA to cytosolic proteins. Numerical sensitivity analysis was used to evaluate systematically the impact of changes in input parameters on model responses. Sensitivity analysis was used to investigate the possibility of designing experiments for robust testing of the uncompetitive inhibition hypothesis, and for further refining the model. Based on the sensitivity analysis, the MMA concentration is the most important response on which to focus. The parameters Vmax and ki can be reliably estimated by using the same concentration time-course data at intermediate initial arsenite concentrations of 1–5μM at 30 ± 5 minutes. Km must be estimated independently of Vmax, since the two parameters are highly correlated at all times, and the optimal experimental conditions would include lower initial concentrations of arsenite (0.1–0.5μM) and earlier time-points (about 8–18 minutes). The use of initial arsenite concentrations much above 5μM would not yield additional useful information, because the sensitivity coefficients for MMA, protein-bound MMA, DMA and protein-bound DMA tend to become extremely small or exhibit erratic trends. Overall trends in the sensitivity analysis indicated the desirability of performing measurements at times shorter than 60 minutes. This work demonstrates that physiological modelling and sensitivity analysis can be efficient tools for experimental planning and hypothesis testing when applied in the earliest phases of kinetic model development, thus allowing more-efficient and more-directed experimentation, and minimising the use of laboratory animals.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) has dose-dependent tissue distribution because of induction of CYP1A2, a TCDD-binding protein, in the liver. Induction requires transcriptional activation of the CYP1A2 gene product by TCDD and the Ah receptor. An empirical model for dose-dependent distribution (Carrier et al., 1995, Toxicol. Appl. Pharmacol. 131, 253-266) included two simple descriptors: one for the maximum liver sequestration (Fmax) and the other for body burden leading to half maximum sequestration (Kd). Physiologically based pharmacokinetic (PBPK) models include specific parameters for protein receptors, protein binding, tissue solubility, and protein induction. We have applied a PBPK model to define two macroscopic constants related to these dose-response curves, i.e., the inflection point, and the maximum values of these curves. The dose-response curves generated from the PBPK model were for the proportion sequestered in liver and the liver to fat concentration ratio. Our analysis assessed the specific biological factors in the PBPK model that governed the values of these two macroscopic constants. For the fraction in liver, the Hill coefficient (a shape exponent describing the relationship between the Ah receptor-TCDD complex with the DNA receptor) resulted in the largest shift in inflection when using PBPK model parameters specific for TCDD. For the liver to fat ratio, the inflection point was most affected by the number of available Ah receptors. Conventional normalized sensitivity coefficients for the liver-to-fat ratio at the maximum were highest for the fat-to-blood partition coefficient, CYP1A2 binding affinity, and maximum extent of induction of CYP1A2. A similar pattern was observed for the liver fraction, except that the sensitivity coefficients were much smaller. The behavior of different TCDD congeners was evaluated by altering the value of key parameters. Our results demonstrate that the inflection point is more related to characteristics of DNA binding/induction steps of the Ah receptor-DNA complex than by the CYP1A2 affinity of TCDD or concentrations of CYP1A2. Surprisingly, the maximum is more sensitive to changes in CYP1A2 concentrations and affinity for TCDD. In addition, the analysis showed that the liver-to-fat ratio is a more useful experimental measure than is proportion in liver because the ratio responds with similar sensitivity over a much wider range of input parameters.

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.

A single 6-hr exposure to inhaled methanol (MeOH) has been shown to enhance carbon tetrachloride (CCl4) hepatotoxicity. The objective of the present study was to use gas uptake data and the development of a physiologically based pharmacokinetic model (PBPK) to determine in vivo changes in CCl4 metabolism resulting from MeOH pretreatment. Adult male F344 rats (167-197 g) were exposed to 10,000 ppm MeOH (constant concentration) via inhalation for 6 hr. Individual rats were exposed using gas uptake techniques to CCl4 alone or to CCl4 either 24 or 48 hr after initiation of MeOH pretreatment. The following initial concentrations were used for CCl4: 0, 25, 100, 250, and 1000 ppm with exposures lasting 6 hr. Vmax (metabolic rate) was estimated from gas uptake data and Km (Michaelis constant) was assumed constant after methanol pretreatment. For CCl4 alone, Vmax was 0.11 mg/hr (Vmaxc = 0.37 mg/hr/kg) and Km was 1.3 mg/liter. Vmax was 0.48 mg/hr (Vmaxc = 1.6 mg/hr/kg) for the 24-hr MeOH + CCl4 group and Vmax was 0.18 mg/hr (Vmaxc = 0.6 mg/hr/kg) for the 48-hr MeOH + CCl4 group. For CCl4 alone, serum markers of hepatotoxicity alanine aminotransferase (ALT) and sorbitol dehydrogenase (SDH) were increased significantly only at 1000 ppm CCl4. Both serum markers of hepatotoxicity in the 24-hr MeOH + CCl4 group increased as a function of CCl4 concentration when compared with 0 ppm CCl4 controls. The maximum increase occurred at 1000 ppm CCl4, where ALT and SDH increased by 392- and 286-fold, respectively. At 100, 250, and 1000 ppm CCl4, ALT and SDH values for the 24-hr MeOH + CCl4 groups were significantly increased relative to control (0 ppm CCl4), CCl4 alone, and 48-hr MeOH + CCl4. ALT and SDH levels in the 48-hr MeOH + CCl4 groups were not statistically different from the respective CCl4 alone groups.