Physiologically Based Pharmacokinetic Modeling of Inhaled Trichloroethylene and Its Oxidative Metabolites in B6C3F1Mice

Ms, Greenberg; Ga, Burton; Jw, Fisher

doi:10.1006/taap.1998.8594

Cited by 31 publications

(30 citation statements)

References 42 publications

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“…The most recent advancements in PBPK modeling of TCE and its metabolites occurred in mice and humans (14)(15)(16). In the mouse, pharmacokinetic studies were undertaken in the laboratory to support development and validation of second-generation PBPK models for P450-mediated metabolism of TCE to chloral hydrate (CH), DCA, TCA, TCOH, and trichloroethanol glucuronide (TCOH-b) (14,15).…”

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confidence: 99%

“…In the mouse, pharmacokinetic studies were undertaken in the laboratory to support development and validation of second-generation PBPK models for P450-mediated metabolism of TCE to chloral hydrate (CH), DCA, TCA, TCOH, and trichloroethanol glucuronide (TCOH-b) (14,15). A human PBPK model was developed using new pharmacokinetic data collected from eight females and nine males that were exposed to TCE vapors (50 or 100 ppm) for 4 hr in a chamber (16).…”

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confidence: 99%

“…The kidney's role in the submodel structure was urinary excretion of metabolites and assessing metabolite dosimetry. The differential equations used to describe the submodel compartments are found in Abbas and Fisher (14) and Greenberg et al (15). The linkage of the metabolite submodels ( Figure 2C) was based on a proposed pathway for metabolism of TCE taken from Davidson and Beliles (23).…”

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Physiologically based pharmacokinetic models for trichloroethylene and its oxidative metabolites.

Fisher

2000

Environ Health Perspect

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

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Physiologically based pharmacokinetic models for trichloroethylene and its oxidative metabolites.

Fisher

2000

Environ Health Perspect

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“…Several PBPK models have been developed for TCE (e.g., see [11][12][13][14][15]). A majority of these models make use of the standard "perfusion-limited" compartmental model for each of the modeled tissues and organs (see Section 4 for a description of the perfusion-limited model).…”

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Probabilistic methods for addressing uncertainty and variability in biological models: application to a toxicokinetic model

Banks

Potter

2004

Mathematical Biosciences

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Population variability and uncertainty are important features of biological systems that must be considered when developing mathematical models for these systems. In this paper we present probability-based parameter estimation methods that account for such variability and uncertainty. Theoretical results that establish well-posedness and stability for these methods are discussed. A probabilistic parameter estimation technique is then applied to a toxicokinetic model for trichloroethylene using several types of simulated data. Comparison with results obtained using a standard, deterministic parameter estimation method suggests that the probabilistic methods are better able to capture population variability and uncertainty in model parameters.

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“…When exposure-effect relationships were generated to determine exposure concentrations producing constant neurotoxicological effects as a result of changing exposure durations, the effective concentrations fell on a line having a shallower slope than that given by Haber's Rule (Figures 1, 3A). (27), enterohepatic recirculation of TCE metabolites (28), B6C3F1 mice (29), and humans (30). PBPK models play a prominent role in the U.S. EPA current reassessment of TCE (6,31 (32), and the neurotoxicity data were collected in Long-Evans rats.…”

Section: Effects Oftce Inhalation On V'isual-evoked Potentialsmentioning

confidence: 99%

Neurotoxic and pharmacokinetic responses to trichloroethylene as a function of exposure scenario.

Boyes

Bushnell

Crofton

et al. 2000

Environ Health Perspect

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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 (C x 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.

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Physiologically Based Pharmacokinetic Modeling of Inhaled Trichloroethylene and Its Oxidative Metabolites in B6C3F1Mice

Cited by 31 publications

References 42 publications

Physiologically based pharmacokinetic models for trichloroethylene and its oxidative metabolites.

Physiologically based pharmacokinetic models for trichloroethylene and its oxidative metabolites.

Probabilistic methods for addressing uncertainty and variability in biological models: application to a toxicokinetic model

Neurotoxic and pharmacokinetic responses to trichloroethylene as a function of exposure scenario.

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