Biomedical subjects

P Robinan Gentry

Publications and source records attributed to P Robinan Gentry.

12 recordsLinked to original sources

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

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↗

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 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↗

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

Interspecies dose extrapolation for inhaled dimethyl sulfate: a PBPK model-based analysis using nasal cavity N7-methylguanine adducts.

Dimethyl sulfate (DMS) is a volatile sulfuric acid ester used principally as a methylating agent in a wide variety of industrial applications. DMS reacts with organic macromolecules by a SN2 mechanism. The weight of experimental evidence suggests that DMS possesses genotoxic and carcinogenic potential. Inhalation studies have shown that repeated exposure to DMS leads to tumors in the nasal cavity and lower respiratory tract in both rats and mice. Here we present a quantitative assessment for cross-species dose extrapolation for inhaled DMS using a physiologically based pharmacokinetic (PBPK) model. The model is designed to simulate N7-methylguanine (N7 mG) DNA adduct levels in the nasal mucosa following DMS exposure in rats and humans. This model was parameterized and predictions were tested by comparison against experimentally measured N7 mG DNA adduct levels in rat nasal mucosa following inhalation exposure to DMS. The model-based interspecies dose comparison, using N7 mG adduct levels in the nasal respiratory tissue as the appropriate dose metrics, predicts a dose rate seven times higher in rats compared to humans.

Administration, Inhalation↗

PubMed2003

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

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

Acetone↗

PubMed2003

Evaluation of the potential impact of pharmacokinetic differences on tissue dosimetry in offspring during pregnancy and lactation.

In recent years efforts have increased to develop a framework for assessing differences, both pharmacokinetic and pharmacodynamic, between children and adults for purposes of assessing risk of adverse effects following chemical exposure. The specific goal of this study was to demonstrate an approach for using PBPK modeling to compare maternal and fetal/neonatal blood and tissue dose metrics during pregnancy and lactation. Six chemical classes were targeted to provide a variety of physicochemical properties (volatility, lipophilicity, water solubility), and surrogate chemicals were selected to represent each class (isopropanol, vinyl chloride, methylene chloride, perchloroethylene, nicotine, and TCDD), based on the availability of pharmacokinetic information. These chemicals were also selected to provide different pharmacokinetic characteristics, including metabolic production of stable or reactive intermediates in the liver and competing pathways for metabolism. Changes in dosimetry during pregnancy predicted by the modeling were mainly attributable to the development of enzymatic pathways in the fetus or to changes in tissue composition in the mother and fetus during pregnancy. In general, blood concentrations were lower in the neonate during the lactation period than in the fetus during gestation. This postnatal decrease varied from only a slight change (for TCDD) to approximately four orders of magnitude (for vinyl chloride). As compared to maternal exposure, fetal/neonatal exposures ranged from approximately twice as great (for TCDD) to several orders of magnitude lower (for isopropanol). The results of this study are in general agreement with the analyses of data on pharmaceutical chemicals, which have suggested that the largest difference in pharmacokinetics observed between children and adults is for the perinatal period. The most important factor appears to be the potential for decreased clearance of toxic chemicals in the perinatal period due to immature metabolic enzyme systems, although this same factor can also reduce the risk from reactive metabolites during the same period.

Animals↗

PubMed2003

Evaluation of the potential impact of age- and gender-specific lung morphology and ventilation rate on the dosimetry of vapors.

In recent years, there have been growing concerns that due to differences, both pharmacokinetic and pharmacodynamic, between children and adults, children could be at greater risk of adverse effects following chemical exposure. The specific goal of this study was to demonstrate an approach for using physiologically based pharmacokinetic (PBPK) modeling to compare inhalation dosimetry in the adult and the child of both males and females. Three categories of gases were considered: rapidly and irreversibly reactive in the respiratory tract (ozone), relatively water-soluble and nonreactive (isopropanol), and relatively water-insoluble and nonreactive (styrene, vinyl chloride, and perchloroethylene). The nonreactive chemicals were also selected because they are metabolized in the respiratory tract. The age-related changes observed for the estimated dose metrics were a function of the physiochemical properties of the inhaled vapor and their interactions in the body. Blood concentrations estimated for all vapors, either poorly metabolized (e.g., PERC), moderately metabolized (e.g., ST), or highly metabolized vapors (e.g., IPA and VC), varied less than a factor of two between infants and adults. These changes, moreover, were confined to the first year after birth, a relatively short window compared to the total lifespan of the individual. In contrast, circulating metabolite concentrations estimated in the blood, as well as amounts metabolized in the liver and lung, appeared to be a strong function of age, due to their dependence on the maturity of the pertinent metabolic enzyme systems.

2-Propanol↗

PubMed2002

An approach for the quantitative consideration of genetic polymorphism data in chemical risk assessment: examples with warfarin and parathion.

In recent years, a great deal of research has been conducted to identify genetic polymorphisms. One focus has been to characterize variability in metabolic enzyme systems that could impact internal doses of pharmaceuticals or environmental pollutants. Methods are needed for using this metabolic information to estimate the resulting variability in tissue doses associated with chemical exposure. We demonstrate here the use of physiologically based pharmacokinetic (PBPK) modeling in combination with Monte Carlo analysis to incorporate information on polymorphisms into the analysis of toxicokinetic variability. Warfarin and parathion were used as case studies to demonstrate this approach. Our results suggest that polymorphisms in the PON1 gene, that give rise to allelic variants of paraoxonase, which is involved in the metabolism of paraoxon (a metabolite of parathion), make only a minor contribution to the overall variability in paraoxon tissue dose, while polymorphisms in the CYP2C9 gene, which gives rise to allelic variants of the major metabolic enzyme for warfarin, account for a significant portion of the overall variability in (S)-warfarin tissue dose. These analyses were used to estimate chemical-specific adjustment factors (CSAFs) for the human variability in toxicokinetics for both parathion and warfarin. Implications of alternatives in the calculation of CSAFs are explored. Key decision points for applying the PBPK-Monte Carlo approach to evaluate toxicokinetic variability for other chemicals are also discussed.

Animals↗