Marina V. Evans

Characterizing uncertainty and population variability in the toxicokinetics of trichloroethylene and metabolites in mice, rats, and humans using an updated database, physiologically based pharmacokinetic (PBPK) model, and Bayesian approach

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.

Issues in the pharmacokinetics of trichloroethylene and its metabolites.

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.

Cutting Edge PBPK Models and Analyses: Providing the Basis for Future Modeling Efforts and Bridges to Emerging Toxicology Paradigms.

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 between in vitro exposures, in vivo physiologic 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.

Development of an updated PBPK model for trichloroethylene and metabolites in mice, and its application to discern the role of oxidative metabolism in TCE-induced hepatomegaly

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.

Duration Adjustment of Acute Exposure Guideline Level Values for Trichloroethylene Using a Physiologically‐Based Pharmacokinetic Model

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 Habers 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.

Evaluation of two different metabolic hypotheses for dichloromethane toxicity using physiologically based pharmacokinetic modeling for in vivo inhalation gas uptake data exposure in female B6C3F1 mice

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 DCMs 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.

Pharmacokinetic Modeling of Arsenite Uptake and Metabolism in Hepatocytes—Mechanistic Insights and Implications for Further Experiments

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.

Improving in vitro to in vivo extrapolation by incorporating toxicokinetic measurements: A case study of lindane-induced neurotoxicity

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 EC50 for increased firing rates in primary cultures of cortical neurons was 0.6μg/ml. Media and cell lindane concentrations at the EC50 were 0.4μg/ml and 7.1μg/ml, respectively, and cellular lindane accumulation was time- and concentration-dependent. Rat blood and brain lindane levels during seizures were 1.7-1.9μg/ml and 5-11μg/ml, respectively. Brain lindane levels associated with seizures in rats and those predicted for humans (average=7μg/ml) by PBPK modeling were very similar to in vitro concentrations detected in cortical cells at the EC50 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.

Visualization-based analysis for a mixed-inhibition binary PBPK model: Determination of inhibition mechanism

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.

Scientific Considerations for Evaluating Cancer Bioassays Conducted by the Ramazzini Institute

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;u2002http://dx.doi.org/10.1289/ehp.1306661