Extrahepatic metabolism by CYP2E1 in PBPK modeling of lipophilic volatile organic chemicals: impacts on metabolic parameter estimation and prediction of dose metrics

A Model Template Approach for Rapid Evaluation and Application of Physiologically Based Pharmacokinetic Models: Extension to Volatile Organic Compounds

Chemical risk assessors use physiologically based pharmacokinetic (PBPK) models to perform dosimetric calculations, including extrapolations between exposure scenarios, species, and populations of interest. Assessors should complete a thorough quality assurance (QA) review to ensure biological accuracy and correct implementation prior to using these models. This process can be time-consuming, and we developed a PBPK model template that allows for faster, more efficient QA review. The model template consists of a single model "superstructure" with equations and logic commonly found in PBPK models, allowing users to implement a wide variety of chemical-specific PBPK models. QA review can be completed more quickly than for conventional PBPK model implementations because the general model equations have already been reviewed and only parameters describing chemical-specific model and exposure scenarios need review for any given model implementation. We have expanded a previous version of the PBPK model template by adding features commonly included in PBPK models for volatile organic compounds (VOCs). We included multiple options for representing concentrations in blood, describing metabolism, and modeling gas exchange processes to allow for inhalation exposures. We created PBPK model template implementations of published models for seven VOCs: dichloromethane, methanol, chloroform, styrene, vinyl chloride, trichloroethylene, and carbon tetrachloride. Simulations performed using our template implementations matched published simulation results to a high degree of accuracy (maximum observed percent error: 1%). Thus, the model template approach can now be applied to a broader class of chemical-specific PBPK models while continuing to bolster efficiency of QA processes that should be conducted prior to using models for risk assessment applications.

Prioritization of mixtures of neurotoxic chemicals for biomonitoring using high-throughput toxicokinetics and mixture toxicity modeling

Modern society continues to pollute the environment with larger quantities of chemicals that have also become more structurally and functionally diverse. Risk assessment of chemicals can hardly keep up with the sheer numbers that lead to complex mixtures of increasing chemical diversity including new chemicals, substitution products on top of still abundant legacy compounds. Fortunately, over the last years computational tools have helped us to identify and prioritize chemicals of concern. These include toxicokinetic models to predict exposure to chemicals as well as new approach methodologies such as in-vitro bioassays to address toxicodynamic effects. Combined, they allow for a prediction of mixtures and their respective effects and help overcome the lack of data we face for many chemicals. In this study we propose a high-throughput approach using experimental and predicted exposure, toxicokinetic and toxicodynamic data to simulate mixtures, to which a virtual population is exposed to and predict their mixture effects. The general workflow is adaptable for any type of toxicity, but we demonstrated its applicability with a case study on neurotoxicity. If no experimental data for neurotoxicity were available, we used baseline toxicity predictions as a surrogate. Baseline toxicity is the minimal toxicity any chemical has and might underestimate the true contribution to the mixture effect but many neurotoxicants are not by orders of magnitude more potent than baseline toxicity. Therefore, including baseline-toxic effects in mixture simulations yields a more realistic picture than excluding them in mixture simulations. This workflow did not only correctly identify and prioritize known chemicals of concern like benzothiazoles, organochlorine pesticides and plasticizers but we were also able to identify new potential neurotoxicants that we recommend to include in future biomonitoring studies and if found in humans, to also include in neurotoxicity screening.

Hepatic, Extrahepatic and Extracellular Vesicle Cytochrome P450 2E1 in Alcohol and Acetaminophen-Mediated Adverse Interactions and Potential Treatment Options

Alcohol and several therapeutic drugs, including acetaminophen, are metabolized by cytochrome P450 2E1 (CYP2E1) into toxic compounds. At low levels, these compounds are not detrimental, but higher sustained levels of these compounds can lead to life-long problems such as cytotoxicity, organ damage, and cancer. Furthermore, CYP2E1 can facilitate or enhance the effects of alcohol-drug and drug-drug interactions. In this review, we discuss the role of CYP2E1 in the metabolism of alcohol and drugs (with emphasis on acetaminophen), mediating injury/toxicities, and drug-drug/alcohol-drug interactions. Next, we discuss various compounds and various nutraceuticals that can reduce or prevent alcohol/drug-induced toxicity. Additionally, we highlight experimental outcomes of alcohol/drug-induced toxicity and potential treatment strategies. Finally, we cover the role and implications of extracellular vesicles (EVs) containing CYP2E1 in hepatic and extrahepatic cells and provide perspectives on the clinical relevance of EVs containing CYP2E1 in intracellular and intercellular communications leading to drug-drug and alcohol-drug interactions. Furthermore, we provide our perspectives on CYP2E1 as a druggable target using nutraceuticals and the use of EVs for targeted drug delivery in extrahepatic and hepatic cells, especially to treat cellular toxicity.

Incorporation of in vitro metabolism data and physiologically based pharmacokinetic modeling in a risk assessment for chloroprene

Objective: To develop a physiologically based pharmacokinetic (PBPK) model for chloroprene in the mouse, rat and human, relying only on in vitro data to estimate tissue metabolism rates and partitioning, and to apply the model to calculate an inhalation unit risk (IUR) for chloroprene.Materials and methods: Female B6C3F1 mice were the most sensitive species/gender for lung tumors in the 2-year bioassay conducted with chloroprene. The PBPK model included tissue metabolism rate constants for chloroprene estimated from results of in vitro gas uptake studies using liver and lung microsomes. To assess the validity of the PBPK model, a 6-hr, nose-only chloroprene inhalation study was conducted with female B6C3F1 mice in which both chloroprene blood concentrations and ventilation rates were measured. The PBPK model was then used to predict dose measures - amounts of chloroprene metabolized in lungs per unit time - in mice and humans.Results: The mouse PBPK model accurately predicted in vivo pharmacokinetic data from the 6-hr, nose-only chloroprene inhalation study. The PBPK model was used to conduct a cancer risk assessment based on metabolism of chloroprene to reactive epoxides in the lung, the target tissue in mice. The IUR was over100-fold lower than the IUR from the EPA Integrated Risk Information System (IRIS), which was based on inhaled chloroprene concentration. The different result from the PBPK model risk assessment arises from use of the more relevant tissue dose metric, amount metabolized, rather than inhaled concentrationDiscussion and conclusions: The revised chloroprene PBPK model is based on the best available science, including new test animal in vivo validation, updated literature review and a Markov-Chain Monte Carlo analysis to assess parameter uncertainty. Relying on both mouse and human metabolism data also provides an important advancement in the use of quantitative in vitro to in vivo extrapolation (QIVIVE). Inclusion of the best available science is especially important when deriving a toxicity value based on species extrapolation for the potential carcinogenicity of a reactive metabolite.

A comprehensive review of cytochrome P450 2E1 for xenobiotic metabolism

Cytochrome P450 2E1 (CYP2E1) plays a vital role in drug-induced hepatotoxicity and cancers (e.g. lung and bladder cancer), since it is responsible for metabolizing a number of medications and environmental toxins to reactive intermediate metabolites. CYP2E1 was recently found to be the highest expressed CYP enzyme in human livers using a proteomics approach, and CYP2E1-related toxicity is strongly associated with its protein level that shows significant inter-individual variability related to ethnicity, age, and sex. Furthermore, the expression of CYP2E1 demonstrates regulation by extensive genetic polymorphism, endogenous hormones, cytokines, xenobiotics, and varying pathological states. Over the past decade, the knowledge of pharmacology, toxicology, and biology about CYP2E1 has grown remarkably, but the research progress has yet to be summarized. This study presents a timely systematic review on CYP2E1's xenobiotic metabolism, genetic polymorphism, and inhibitors, with the focus on their clinical relevance for the efficacy and toxicity of various CYP2E1 substrates. Moreover, several knowledge gaps have been identified towards fully understanding the potential interactions among different CYP2E1 substrates in clinical settings. Through in-depth analyses of these knowns and unknowns, we expect this review will aid in future drug development and improve management of CYP2E1 related clinical toxicity.

Post-operative elimination of sevoflurane anesthetic and hexafluoroisopropanol metabolite in exhaled breath: pharmacokinetic models for assessing liver function

Sevoflurane (SEV), a commonly used anesthetic agent for invasive surgery, is directly eliminated via exhaled breath and indirectly by metabolic conversion to inorganic fluoride and hexafluoroisopropanol (HFIP), which is also eliminated in the breath. We studied the post-operative elimination of SEV and HFIP of six patients that had undergone a variety of surgeries lasting between 2.5 to 8.5 h using exhaled breath analysis. A classical three compartments pharmacokinetic model developed for the study of environmental contaminants was fitted to the breath data. We found that SEV kinetic behavior following surgery (for up to six days) is consistent across all subjects whereas the production and elimination of HFIP varies to some extent. We developed subject specific parameters for HFIP metabolism and interpreted the differences in the context of timing and dose of anesthesia, type of surgery, and specific host factors. We propose methods for assessing individual patient liver function using SEV as a probe molecule for assessing efficiency of liver metabolism to HFIP. This work is valuable not only for the clinical study of metabolism recovery, but potentially also for the study of the interaction of other manufactured and environmental compounds with human systems biology in controlled exposure and observational studies.

Application of an updated physiologically based pharmacokinetic model for chloroform to evaluate CYP2E1-mediated renal toxicity in rats and mice

Physiologically based pharmacokinetic (PBPK) models are tools for interpreting toxicological data and extrapolating observations across species and route of exposure. Chloroform (CHCl(3)) is a chemical for which there are PBPK models available in different species and multiple sites of toxicity. Because chloroform induces toxic effects in the liver and kidneys via production of reactive metabolites, proper characterization of metabolism in these tissues is essential for risk assessment. Although hepatic metabolism of chloroform is adequately described by these models, there is higher uncertainty for renal metabolism due to a lack of species-specific data and direct measurements of renal metabolism. Furthermore, models typically fail to account for regional differences in metabolic capacity within the kidney. Mischaracterization of renal metabolism may have a negligible effect on systemic chloroform levels, but it is anticipated to have a significant impact on the estimated site-specific production of reactive metabolites. In this article, rate parameters for chloroform metabolism in the kidney are revised for rats, mice, and humans. New in vitro data were collected in mice and humans for this purpose and are presented here. The revised PBPK model is used to interpret data of chloroform-induced kidney toxicity in rats and mice exposed via inhalation and drinking water. Benchmark dose (BMD) modeling is used to characterize the dose-response relationship of kidney toxicity markers as a function of PBPK-derived internal kidney dose. Applying the PBPK model, it was also possible to characterize the dose response for a recent data set of rats exposed via multiple routes simultaneously. Consistent BMD modeling results were observed regardless of species or route of exposure.

Chemical-specific screening criteria for interpretation of biomonitoring data for volatile organic compounds (VOCs)--application of steady-state PBPK model solutions

The National Health and Nutrition Examination Survey (NHANES) generates population-representative biomonitoring data for many chemicals including volatile organic compounds (VOCs) in blood. However, no health or risk-based screening values are available to evaluate these data from a health safety perspective or to use in prioritizing among chemicals for possible risk management actions. We gathered existing risk assessment-based chronic exposure reference values such as reference doses (RfDs), reference concentrations (RfCs), tolerable daily intakes (TDIs), cancer slope factors, etc. and key pharmacokinetic model parameters for 47 VOCs. Using steady-state solutions to a generic physiologically-based pharmacokinetic (PBPK) model structure, we estimated chemical-specific steady-state venous blood concentrations across chemicals associated with unit oral and inhalation exposure rates and with chronic exposure at the identified exposure reference values. The geometric means of the slopes relating modeled steady-state blood concentrations to steady-state exposure to a unit oral dose or unit inhalation concentration among 38 compounds with available pharmacokinetic parameters were 12.0 microg/L per mg/kg-d (geometric standard deviation [GSD] of 3.2) and 3.2 microg/L per mg/m(3) (GSD=1.7), respectively. Chemical-specific blood concentration screening values based on non-cancer reference values for both oral and inhalation exposure range from 0.0005 to 100 microg/L; blood concentrations associated with cancer risk-specific doses at the 1E-05 risk level ranged from 5E-06 to 6E-02 microg/L. The distribution of modeled steady-state blood concentrations associated with unit exposure levels across VOCs may provide a basis for estimating blood concentration screening values for VOCs that lack chemical-specific pharmacokinetic data. The screening blood concentrations presented here provide a tool for risk assessment-based evaluation of population biomonitoring data for VOCs and are most appropriately applied to central tendency estimates for such datasets.

Identification of antigenic proteins associated with trichloroethylene-induced autoimmune disease by serological proteome analysis

Although many studies indicated that trichloroethylene (TCE) could induce autoimmune diseases and some protein adducts were detected, the proteins were not identified and mechanisms remain unknown. To screen and identify autoantigens which might be involved in TCE-induced autoimmune diseases, three groups of sera were collected from healthy donors (I), patients suffering from TCE-induced exfoliative dermatitis (ED) (II), and the healed ones (III). Serological proteome analysis (SERPA) was performed with total proteins of TCE-treated L-02 liver cells as antigen sources and immunoglobins of the above sera as probes. Highly immunogenic spots (2-fold or above increase compared with group I) in group II and III were submitted to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and tandem mass spectrometry sequencing. Western blot analysis was followed using commercial antibodies and individual serum. Six proteins were identified. Among them, Enoyl Coenzyme A hydratase peroxisoma 1 and lactate dehydrogenase B only showed stronger immunogenicity for group II sera, while Purine nucleoside phosphorylase, ribosomal protein P0 and proteasome activator subunit1 isoform1 also showed stronger immunogenicity for group III sera. Noteworthy, NM23 reacted only with group II sera. Western blot analysis of NM23 expression indicated that all of the individual serum of group II showed immune activity, which confirmed the validity of SERPA result. These findings revealed that there exist autoantibodies in group II and III sera. Besides, autoantibodies of the two stages of disease course were different. These autoantigens might serve as biomarkers to elucidate mechanisms underlying TCE toxicity and are helpful for diagnosis, therapy and prognosis of TCE-induced autoimmune diseases.