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Harvey J Clewell

Publications and source records attributed to Harvey J Clewell.

At least 19 recordsLinked to original sources
PubMed2006

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↗
PubMed2006

Pharmacokinetic modeling of saturable, renal resorption of perfluoroalkylacids in monkeys--probing the determinants of long plasma half-lives.

Perfluorooctanoate (PFOA) and perfluorooctanesulfonate (PFOS) compounds associated with surface protection product manufactures are distributed globally. The 3-5-year half-lives, reproductive and liver toxicity in animals, and lack of understanding of the factors regulating retention in the body have led to a world-wide public concern for use of these materials. Using a novel physiologically-motivated pharmacokinetic model for renal clearance, perfluoroalkylacid pharmacokinetics in monkeys was successfully described by renal resorption via high efficiency transporters for both intravenous and oral dosing. Intravenous dosing with both PFOA and PFOS in Cynomolgus monkeys produced time course curves consistent with a two-compartment distribution. Extending the PK model for intravenous dosing to examine blood and urine time course data for repeated oral dosing clearly identified the saturable renal resorption. Resorption depends on kinetic factors for transport (T(mC), transport maximum; K(T), transport affinity) and free fraction in plasma (f(plasma)). For PFOA, these parameters were estimated to be 5mg/(h kg) (T(mC)), 0.055 mg/L (K(T)), and 0.02 (f(plasma)). PFOS has longer half-life and had respective values of 13.6 mg/(h kg), 0.023 mg/L, and 0.025. PFOS appeared to have a higher transport capacity and lower affinity than PFOA. Human kinetics indicates even higher resorption efficiency.

Administration, Oral↗
PubMed2006

The use of Markov chain Monte Carlo uncertainty analysis to support a Public Health Goal for perchloroethylene.

The current Public Health Goal (PHG) for perchloroethylene (PCE) was derived using upper-bound estimates of fractional PCE metabolism in humans. These estimates were in part obtained from a published evaluation of the uncertainty and variability in human PCE metabolism conducted using a physiologically-based pharmacokinetic (PBPK) model in a Markov chain Monte Carlo (MCMC) analysis; however, the data used in that analysis were limited to post-exposure PCE blood and exhaled air concentrations from a single study. A more recent study [Volkel, W., Friedewald, M., Lederer, E., Pahler, A., Parker, J., Dekant, W., 1998. Biotransformation of perchloroethene: dose-dependent excretion of trichloroacetic acid, dichloroacetic acid, and N-acetyl-S-(trichlorovinyl)-l-cysteine in rats and humans after inhalation. Toxicol. Appl. Pharmacol. 153(1), 20-27.] provides data on blood concentrations of PCE and its major metabolite, trichloroacetic acid (TCA), and urinary excretion of TCA following exposure of human subjects to lower concentrations of PCE (10-40ppm) than in previous studies. In the present effort, a new MCMC analysis was performed that focused on data from this study along with two others [Fernandez, J., Guberan, E., Caperos, J., 1976. Experimental human exposures to tetrachloroethylene vapor and elimination in breath after inhalation. Am. Ind. Hyg. Assoc. J. 37, 143-150; Monster, A., Boersma, G., Steenweg, H., 1979. Kinetics of tetrachloroethylene in volunteers; influence of exposure concentration and work load. Int. Arch. Occup. Environ. Health 42, 303-309.] providing data on PCE blood concentrations and urinary excretion of TCA. To provide an accurate prediction of TCA kinetics, the PBPK model used here includes a description of the metabolism of PCE to TCA in both the liver and kidney. The resulting upper 95th percentile estimates of fraction of PCE metabolized by inhalation and oral routes were 2.1 and 5.2%, respectively, compared to 58 and 79% used in the derivation of the PHG.

Carcinogens, Environmental↗
PubMed2006

Bayesian population analysis of a harmonized physiologically based pharmacokinetic model of trichloroethylene and its metabolites.

Bayesian population analysis of a harmonized physiologically based pharmacokinetic (PBPK) model for trichloroethylene (TCE) and its metabolites was performed. In the Bayesian framework, prior information about the PBPK model parameters is updated using experimental kinetic data to obtain posterior parameter estimates. Experimental kinetic data measured in mice, rats, and humans were available for this analysis, and the resulting posterior model predictions were in better agreement with the kinetic data than prior model predictions. Uncertainty in the prediction of the kinetics of TCE, trichloroacetic acid (TCA), and trichloroethanol (TCOH) was reduced, while the kinetics of other key metabolites dichloroacetic acid (DCA), chloral hydrate (CHL), and dichlorovinyl mercaptan (DCVSH) remain relatively uncertain due to sparse kinetic data for use in this analysis. To help focus future research to further reduce uncertainty in model predictions, a sensitivity analysis was conducted to help identify the parameters that have the greatest impact on various internal dose metric predictions. For application to a risk assessment for TCE, the model provides accurate estimates of TCE, TCA, and TCOH kinetics. This analysis provides an important step toward estimating uncertainty of dose-response relationships in noncancer and cancer risk assessment, improving the extrapolation of toxic TCE doses from experimental animals to humans.

Animals↗
PubMed2006

Application of pharmacokinetic data to the risk assessment of inhaled manganese.

There is increased interest within the scientific community concerning the neurotoxicity of manganese owing in part to the use of methylcyclopentadienyl manganese tricarbonyl (MMT) as a gasoline fuel additive and an enhanced awareness that this essential metal may play a role in hepatic encephalopathy and other neurologic diseases. Neurotoxicity generally arises over a prolonged period of time and results when manganese intake exceeds its elimination leading to increases in brain manganese concentration. Neurotoxicity can occur following high dose oral, inhalation, or parenteral exposure or when hepatobiliary clearance of this metal is impaired. Studies completed during the past several years have substantially improved our understanding of the health risks posed by inhaled manganese by determining exposure conditions that lead to increased concentrations of manganese within the central nervous system and other target organs. Many of these studies focused on phosphates, sulfates, and oxides of manganese since these are formed and emitted following MMT combustion by an automobile. These studies have evaluated the role of direct nose-to-brain transport of inhaled manganese and have examined differences in manganese toxicokinetics in potentially sensitive subpopulations (e.g., fetuses, neonates, individuals with compromised hepatic function or sub-optimal manganese intake, and the aged). This manuscript reviews the U.S. Environmental Protection Agency's current risk assessment for inhaled manganese, summarizes these contemporary pharmacokinetic studies, and considers how these data could inform future risk assessments of this metal following inhalation.

Animals↗
PubMed2006

Revised assessment of cancer risk to dichloromethane: part I Bayesian PBPK and dose-response modeling in mice.

The current USEPA cancer risk assessment for dichloromethane (DCM) is based on deterministic physiologically based pharmacokinetic (PBPK) modeling involving comparative metabolism of DCM by the GST pathway in the lung and liver of humans and mice. Recent advances in PBPK modeling include probabilistic methods and, in particular, Bayesian inference to quantitatively address variability and uncertainty separately. Although Bayesian analysis of human PBPK models has been published, no such efforts have been reported specifically addressing the mouse, apart from results included in the OSHA final rule on DCM. Certain aspects of the OSHA model, however, are not consistent with current approaches or with the USEPA's current DCM cancer risk assessment. Therefore, Bayesian analysis of the mouse PBPK model and dose-response modeling was undertaken to support development of an improved cancer risk assessment for DCM. A hierarchical population model was developed and prior parameter distributions were selected to reflect parameter values that were considered the most appropriate and best available. Bayesian modeling was conducted using MCSim, a publicly available software program for Markov Chain Monte Carlo analysis. Mean posterior values from the calibrated model were used to develop internal dose metrics, i.e., mg DCM metabolized by the GST pathway/L tissue/day in the lung and liver using exposure concentrations and results from the NTP mouse bioassay, consistent with the approach used by the USEPA for its current DCM cancer risk assessment. Internal dose metrics were 3- to 4-fold higher than those that support the current USEPA IRIS assessment. A decrease of similar magnitude was also noted in dose-response modeling results. These results show that the Bayesian PBPK model in the mouse provides an improved basis for a cancer risk assessment of DCM.

Animals↗
PubMed2006

Revised assessment of cancer risk to dichloromethane II. Application of probabilistic methods to cancer risk determinations.

An updated PBPK model of methylene chloride (DCM, dichloromethane) carcinogenicity in mice was recently published using Bayesian statistical methods (Marino et al., 2006). In this work, this model was applied to humans, as recommended by Sweeney et al.(2004). Physiological parameters for input into the MCMC analysis were selected from multiple sources reflecting, in each case, the source that was considered to represent the most current scientific evidence for each parameter. Metabolic data for individual subjects from five human studies were combined into a single data set and population values derived using MCSim. These population values were used for calibration of the human model. The PBPK model using the calibrated metabolic parameters was used to perform a cancer risk assessment for DCM, using the same tumor incidence and exposure concentration data relied upon in the current IRIS entry. Unit risks, i.e., the risk of cancer from exposure to 1 microg/m3 over a lifetime, for DCM were estimated using the calibrated human model. The results indicate skewed distributions for liver and lung tumor risks, alone or in combination, with a mean unit risk (per microg/m3) of 1.05 x 10(-9), considering both liver and lung tumors. Adding the distribution of genetic polymorphisms for metabolism to the ultimate carcinogen, the unit risks range from 0 (which is expected given that approximately 20% of the US population is estimated to be nonconjugators) up to a unit risk of 2.70 x 10(-9) at the 95th percentile. The median, or 50th percentile, is 9.33 x 10(-10), which is approximately a factor of 500 lower than the current EPA unit risk of 4.7 x 10(-7) using a previous PBPK model. These values represent the best estimates to date for DCM cancer risk because all available human data sets were used, and a probabilistic methodology was followed.

Carcinogens↗
PubMed2006

Use of a physiologically based pharmacokinetic model to identify exposures consistent with human biomonitoring data for chloroform.

Biomonitoring data provide evidence of human exposure to environmental chemicals by quantifying the chemical or its metabolite in a biological matrix. To better understand the correlation between biomonitoring data and environmental exposure, physiologically based pharmacokinetic (PBPK) modeling can be of use. The objective of this study was to use a combined PBPK model with an exposure model for showering to estimate the intake concentrations of chloroform based on measured blood and exhaled breath concentrations of chloroform. First, the predictive ability of the combined model was evaluated with three published studies describing exhaled breath and blood concentrations in people exposed to chloroform under controlled showering events. Following that, a plausible exposure regimen was defined combining inhalation, ingestion, and dermal exposures associated with residential use of water containing typical concentrations of chloroform to simulate blood and exhaled breath concentrations of chloroform. Simulation results showed that inhalation and dermal exposure could contribute substantially to total chloroform exposure. Next, sensitivity analysis and Monte Carlo analysis were performed to investigate the sources of variability in model output. The variability in exposure conditions (e.g., shower duration) was shown to contribute more than the variability in pharmacokinetics (e.g., body weight) to the predicted variability in blood and exhaled breath concentrations of chloroform. Lastly, the model was used in a reverse dosimetry approach to estimate distributions of exposure consistent with concentrations of chloroform measured in human blood and exhaled breath.

Chloroform↗
PubMed2005

Exposure assessment and risk characterization for perfluorooctanoate in selected consumer articles.

An exposure assessment and risk characterization was conducted to better understand the potential human health significance of trace levels of perfluorooctanoate (PFO) detected in certain consumer articles. PFO is the anion of perfluorooctanoic acid (PFOA). Concentrations of PFO in the consumer articles were determined from extraction tests and product formulation information. Potential exposures during consumer use of the articles were quantified based on an assessment of behavior patterns and regulatory guidance. Health benchmarks were developed and then compared to the exposure estimates to yield margins of exposure (MOEs). A simple one-compartment model was also developed to estimate contributions of potential consumer exposures to PFO concentrations in serum. While there are considerable uncertainties in this assessment, it indicates that exposures to PFO during consumer use of the articles evaluated in this study are not expected to cause adverse human health effects in infants, children, adolescents, adult residents, or professionals nor result in quantifiable levels of PFO in human serum.

Adolescent↗
PubMed2005

Comparison of tissue dosimetry in the mouse following chronic exposure to arsenic compounds.

Several chronic bioassays have been conducted in multiple strains of mice in which various concentrations of arsenate or arsenite were administered in the drinking water without a tumorigenic effect. However, one study (Ng et al., 1999) reported a significant increase in tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. A physiologically based pharmacokinetic model for arsenic in the mouse has previously been developed (Gentry et al., 2004) to investigate potential differences in tissue dosimetry of arsenic species across various strains of mice. Initial results indicated no significant differences in blood, liver, or urine dosimetry in B6C3F1 and C57Bl/6 mice for acute or subchronic exposure. The current work was conducted to compare model-predicted estimates of tissue dosimetry to additional kinetic information from the (C57Bl/6 xCBA)F1 and TgAc mouse. The results from the current modeling indicate that the pharmacokinetic parameters derived based on information in the B6C3F1 mouse adequately describe the measured concentrations in the blood/plasma, liver, and urine of both the (C57Bl/6 x CBA)F1 and TgAc mouse, providing further support that the differences in response observed in the chronic bioassays are not related to strain-specific differences in pharmacokinetics. One significant finding was that no increases in skin or lung concentrations of arsenic species in the (C57Bl/6 x CBA)F1 strain were observed following administration of low concentrations (0.2 or 2 mg/U of arsenate in the drinking water, even though differences in response in the skin were reported. These data suggest that pharmacodynamic changes may be observed following exposure to arsenic compounds without an observable change in tissue dosimetry. These results provided further indirect support for the existence of inducible arsenic efflux in these tissues.

Administration, Oral↗
PubMed2005

Evaluation of oral and intravenous route pharmacokinetics, plasma protein binding, and uterine tissue dose metrics of bisphenol A: a physiologically based pharmacokinetic approach.

Bisphenol A (BPA) is a weakly estrogenic monomer used in the production of polycarbonate plastic and epoxy resins, both of which are used in food contact and other applications. A physiologically based pharmacokinetic (PBPK) model of BPA pharmacokinetics in rats and humans was developed to provide a physiological context in which the processes controlling BPA pharmacokinetics (e.g., plasma protein binding, enterohepatic recirculation of the glucuronide [BPAG]) could be incorporated. A uterine tissue compartment was included to allow the correlation of simulated estrogen receptor (ER) binding of BPA with increases in uterine wet weight (UWW) in rats. Intravenous- and oral-route blood kinetics of BPA in rats and oral-route plasma and urinary elimination kinetics in humans were well described by the model. Simulations of rat oral-route BPAG pharmacokinetics were less exact, most likely the result of oversimplification of the GI tract compartment. Comparison of metabolic clearance rates derived from fitting rat i.v. and oral-route data implied that intestinal glucuronidation of BPA is significant. In rats, but not humans, terminal elimination rates were strongly influenced by enterohepatic recirculation. In the absence of BPA binding to plasma proteins, simulations showed high ER occupancy at doses without uterine effects. Restricting free BPA to the measured unbound amount demonstrated the importance of including plasma binding in BPA kinetic models: the modeled relationship between ER occupancy and UWW increases was consistent with expectations for a receptor-mediated response with low ER occupancy at doses with no response and increasing occupancy with larger increases in UWW.

Administration, Oral↗
PubMed2005

Evaluation of physiologically based pharmacokinetic models in risk assessment: an example with perchloroethylene.

One of the more problematic aspects of the application of physiologically based pharmacokinetic (PBPK) models in risk assessment is the question of whether the model has been adequately validated to provide confidence in the dose metrics calculated with it. A number of PBPK models have been developed for perchloroethylene (PCE), differing primarily in the parameters estimated for metabolism. All of the models provide reasonably accurate simulations of selected kinetic data for PCE in mice and humans and could thus be considered to be "validated" to some extent. However, quantitative estimates of PCE cancer risk are critically dependent on the prediction of the rate of metabolism at low environmental exposures. Recent data on the urinary excretion of trichloroacetic acid (TCA), the major metabolite of PCE, for human subjects exposed to lower concentrations than those used in previous studies, make it possible to compare the high- to low-dose extrapolation capability of the various published human models. The model of Gearhart et al., which is the only model to include a description of TCA kinetics, provided the closest predictions of the urinary excretion observed in these low-concentration exposures. Other models overestimated metabolite excretion in this study by 5- to 15-fold. A systematic discrepancy between model predictions and experimental data for the time course of the urinary excretion of TCA suggested a contribution from TCA formed by metabolism of PCE in the kidney and excreted directly into the urine. A modification of the model of Gearhart et al. to include metabolism of PCE to TCA in the kidney at 10% of the capacity of the liver, with direct excretion of the TCA formed in the kidney into the urine, markedly improved agreement with the experimental time-course data, without altering predictions of liver metabolism. This case study with PCE demonstrates the danger of relying on parent chemical kinetic data to validate a model that will be used for the prediction of metabolism.

Animals↗
PubMed2005

Quantitative estimates of risk for noncancer endpoints.

While quantitative estimates of risk have been a standard practice in cancer risk assessment for many years, no similar practice is evident in noncancer risk assessment. We use two recent examples involving methylmercury and arsenic to illustrate the negative impact of this discrepancy on risk communication and cost-benefit analysis. We argue for a more balanced treatment of cancer and noncancer risks and suggest an approach for reaching this goal.

Arsenic↗
PubMed2004

Development of a physiologically based pharmacokinetic model for volatile fractions of gasoline using chemical lumping analysis.

Physiologically based pharmacokinetic (PBPK) models have often been used to describe the absorption, distribution, metabolism, and excretion of chemicals in animals but have been limited to single chemicals and simple mixtures due to the numerous parameters required in the models. To overcome the barrier to modeling more complex mixtures, we used a chemical lumping approach, used in the past in chemical engineering but not in pharmacokinetic modeling, in a rat PBPK model for gasoline hydrocarbons. Our previous gasoline model consisted of five individual components (benzene, toluene, ethylbenzene, xylene, and hexane) and a lumped chemical that included all remaining components of whole gasoline. Despite being comprised of hundreds of components, the lumped component could be described using a single set of chemical parameters that depended on the blend of gasoline. In the present study, we extend this approach to evaporative fractions of gasoline. The PBPK model described the pharmacokinetics of all of the volatility-weighted fractions of gasoline when differences in partitioning and metabolism between fractions were taken into account. Adjusting the ventilation rate parameter to account for respiratory depression at high exposures also allowed a much improved description of the data. At high exposure levels, gasoline components competitively inhibit each other's metabolism, and the model successfully accounted for binary interactions of this type, including between the lumped component and the five other chemicals. The model serves as a first example of how the engineering concept of chemical lumping can be used in pharmacokinetics.

Adsorption↗
PubMed2004

Evaluation of the potential impact of age- and gender-specific pharmacokinetic differences on tissue dosimetry.

The physiological and biochemical processes that determine the tissue concentration time courses (pharmacokinetics) of xenobiotics vary, in some cases significantly, with age and gender. While it is known that age- and gender-specific differences have the potential to affect tissue concentrations and, hence, individual risk, the relative importance of the contributing processes and the quantitative impact of these differences for various life stages are not well characterized. The objective of this study was to identify age- and gender-specific differences in physiological and biochemical processes that affect tissue dosimetry and integrate them into a predictive physiologically based pharmacokinetic (PBPK) life-stage model. The life-stage model was exercised for several environmental chemicals with a variety of physicochemical, biochemical, and mode-of-action properties. In general, predictions of average pharmacokinetic dose metrics for a chemical across life stages were within a factor of two, although larger transient variations were predicted, particularly during the neonatal period. The most important age-dependent pharmacokinetic factor appears to be the potential for decreased clearance of a toxic chemical in the perinatal period due to the immaturity of many metabolic enzyme systems, although this same factor may also reduce the production of a reactive metabolite. Given the potential for age-dependent pharmacodynamic factors during early life, there may be chemicals and health outcomes for which decreased clearance over a relatively brief period could have a substantial impact on risk.

2-Propanol↗
PubMed2004

Physiologically based pharmacokinetic modeling of arsenic in the mouse.

A remarkable feature of the carcinogenicity of inorganic arsenic is that while human exposures to high concentrations of inorganic arsenic in drinking water are associated with increases in skin, lung, and bladder cancer, inorganic arsenic has not typically caused tumors in standard laboratory animal test protocols. Inorganic arsenic administered for periods of up to 2 yr to various strains of laboratory mice, including the Swiss CD-1, Swiss CR:NIH(S), C57Bl/6p53(+/-), and C57Bl/6p53(+/+), has not resulted in significant increases in tumor incidence. However, Ng et al. (1999) have reported a 40% tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. In order to investigate the potential role of tissue dosimetry in differential susceptibility to arsenic carcinogenicity, a physiologically based pharmacokinetic (PBPK) model for inorganic arsenic in the rat, hamster, monkey, and human (Mann et al., 1996a, 1996b) was extended to describe the kinetics in the mouse. The PBPK model was parameterized in the mouse using published data from acute exposures of B6C3F1 mice to arsenate, arsenite, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) and validated using data from acute exposures of C57Black mice. Predictions of the acute model were then compared with data from chronic exposures. There was no evidence of changes in the apparent volume of distribution or in the tissue-plasma concentration ratios between acute and chronic exposure that might support the possibility of inducible arsenite efflux. The PBPK model was also used to project tissue dosimetry in the C57Bl/6J study, in comparison with tissue levels in studies having shorter duration but higher arsenic treatment concentrations. The model evaluation indicates that pharmacokinetic factors do not provide an explanation for the difference in outcomes across the various mouse bioassays. Other possible explanations may relate to strain-specific differences, or to the different durations of dosing in each of the mouse studies, given the evidence that inorganic arsenic is likely to be active in the later stages of the carcinogenic process.

Acute Disease↗
PubMed2004

The perils and promise of modern risk assessment: the example of trichloroethylene.

This article summarizes some of the major scientific shortcomings identified by reviewers of the draft "Trichloroethylene Health Risk Assessment: Synthesis and Characterization" (TCE HRA) in the context of current US Environmental Protection Agency risk assessment guidance and the Data Quality Act guidelines. Our purpose is not to further criticize the draft HRA but to highlight specific areas for improvement and suggest specific ameliorative actions that we believe would improve the scientific credibility (quality) of the final document. This exercise is expected to be applicable beyond the specific case of TCE, because the draft HRA surely exemplifies many of the new challenges being posed to risk assessment in general by the ever-increasing sophistication of modern science.

Animals↗