Citation:

El-Masri, H., T. Hong, C. Henning, W. Mendez, E. Hudgens, D. Thomas, AND JaniceS Lee. Evaluation of a Physiologically based Pharmacokinetic (PBPK) Model for Inorganic Arsenic Exposure Using Data from Two Diverse Human Populations. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, 126(7):1-18, (2018). https://doi.org/10.1289/EHP3096

Impact/Purpose:

Physiologically-based pharmacokinetic (PBPK) models can be used to interpret the results of biomonitoring data to better inform estimates of external exposures and daily intake, through back-estimation of levels of exposure and dose consistent with measured biomarker concentrations. Specifically, PBPK models can be used to normalize data reported in multiple human studies to a common metric of exposure or dose for the purposes of a meta-analysis. In the current analysis, a published human PBPK model for iAs oral intake by El-Masri and Kenyon (2008) was evaluated using data from two populations. Simulations were conducted using the PBPK model to estimate total iAs levels in urine in comparison with data obtained from two large population studies in Bangladesh and the United States. In both comparisons, intake of iAs was examined using data on consumption of iAs-contaminated water alone or in combination with data on consumption of arsenic in food. Results of the evaluation of the PBPK model illustrate the model’s utility for exposure reconstruction, and hence its value for application to human health risk assessment for inorganic arsenic exposure.

Description:

Background: Multiple epidemiological studies exist for some of the well-studied health endpoints associated with inorganic arsenic (iAs) exposure; however, results are usually expressed in terms of different exposure/dose metrics. Physiologically based pharmacokinetic (PBPK) models may be used to obtain a common exposure metric for application in dose–response meta-analysis. Objective: A previously published PBPK model for inorganic arsenic (iAs) was evaluated using data sets for arsenic-exposed populations from Bangladesh and the United States. Methods: The first data set was provided by the Health Effects of Arsenic Longitudinal Study cohort in Bangladesh. The second data set was provided by a study conducted in Churchill County, Nevada, USA. The PBPK model consisted of submodels describing the absorption, distribution, metabolism and excretion (ADME) of iAs and its metabolites monomethylarsenic (MMA) and dimethylarsenic (DMA) acids. The model was used to estimate total arsenic levels in urine in response to oral ingestion of iAs. To compare predictions of the PBPK model against observations, urinary arsenic concentration and creatinine-adjusted urinary arsenic concentration were simulated. As part of the evaluation, both water and dietary intakes of arsenic were estimated and used to generate the associated urine concentrations of the chemical in exposed populations. Results: When arsenic intake from water alone was considered, the results of the PBPK model underpredicted urinary arsenic concentrations for individuals with low levels of arsenic in drinking water and slightly overpredicted urinary arsenic concentrations in individuals with higher levels of arsenic in drinking water. When population-specific estimates of dietary intakes of iAs were included in exposures, the predictive value of the PBPK model was markedly improved, particularly at lower levels of arsenic intake. Conclusions: Evaluations of this PBPK model illustrate its adequacy and usefulness for oral exposure reconstructions in human health risk assessment, particularly in individuals who are exposed to relatively low levels of arsenic in water or food. https://doi.org/10.1289/EHP3096

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