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K-State Today

March 29, 2021

Researchers publish series of physiologically-based pharmacokinetic model manuscripts for perfluorooctane sulfonate

Submitted by Cheyenne Swoope

The 2021 research team had their manuscript published in Environmental Health Perspectives. They are (top row, left to right) Qiran Chen, Zhoumeng Lin, Wei-Chun Chou (bottom row, left to right) Long Yuan and Md Mahbubul Huq Riad.

A team of researchers at Kansas State University focuses on applying computational modeling technologies to address food safety, toxicology and risk assessment issues. Members develop and apply innovative physiologically based pharmacokinetic, or PBPK, models to assess exposure to drugs, environmental chemicals or nanomaterials in the target tissue in laboratory animals, food-producing animals, companion animals or humans.

Over three years, the team led by Zhoumeng Lin, associate professor of pharmacology and toxicology and the principal investigator, has published three papers related to perfluorooctane sulfonate or PFOS. Considered a pollutant, PFOS is a member of the family of per- and polyfluoroalkyl substances, or PFAS, which are human-made, persistent environmental contaminants and a global public health concern. The published manuscripts focus on creating models for utilization in human health risk assessments.

In 2019, the team published a study titled “Bayesian Evaluation of a Physiologically Based Pharmacokinetic (PBPK) Model for Perfluorooctane Sulfonate (PFOS) to Characterize the Interspecies Uncertainty between Mice, Rats, Monkeys, and Humans: Development and Performance Verification,” in the journal, Environment International. Available species-specific toxicokinetic data from other studies were used for model calibration and optimization, and independent datasets were used for model evaluation.

“This manuscript describes a physiologically based pharmacokinetic model for PFOS in mice, rats, monkeys and humans,” said Lin. “This model can be used to extrapolate toxicokinetic and toxicity data from animals to humans to support risk assessment and derivation of a new reference dose of PFOS, ultimately helping make public health decisions on this environmental contaminant.”

Lin’s team performed Bayesian statistical analysis using Markov chain Monte Carlo simulation to optimize the model and to characterize the uncertainty and interspecies variability of chemical-specific parameters. The integrated and comparative analysis provides an important step toward improving interspecies extrapolation and quantitative risk assessment of PFOS. This open-source model provides a foundation for developing models for other perfluoroalkyl substances. It was donned the Best Paper Award by the Society of Toxicology Biological Modeling Specialty Section.

In 2020, the group followed up with a study titled “Probabilistic human health risk assessment of perfluorooctane sulfonate (PFOS) by integrating in vitro, in vivo toxicity, and human epidemiological studies using a Bayesian-based dose-response assessment coupled with physiologically based pharmacokinetic (PBPK) modeling approach,” published in Environment International. A Bayesian dose-response model was developed to analyze 34 studies, including human epidemiological, animal in vivo, and ToxCast in vitro toxicity datasets.

“The article describes a new probabilistic human health risk assessment method for PFOS that can be used to conduct dose-response analysis of different types of toxicity data,” said Wei-Chun Chou, research fellow in Institute of Computational Comparative Medicine in the department of anatomy and physiology of the College of Veterinary Medicine and lead author of the series of manuscripts. “This includes high-throughput in vitro data, in vivo animal toxicity data, and human epidemiological data and the dose-response analysis results can be linked to a PBPK model for subsequent risk assessment.”

The dose-response results were incorporated into a multi-species PBPK model to reduce the toxicokinetic/toxicodynamic uncertainties. In addition, a population-based probabilistic risk assessment of PFOS was performed for Asian, Australian, European, and North American populations, respectively, based on reported environmental exposure levels. The results provide insights into a complete risk characterization of PFOS and may help regulatory agencies in the reevaluation of PFOS risk.

The 2021 study titled, “Development of a Gestational and Lactational Physiologically Based Pharmacokinetic (PBPK) Model for Perfluorooctane Sulfonate (PFOS) in Rats and Humans and its Implications in the Derivation of Health-Based Toxicity Values” was recently accepted for publication in Environmental Health Perspectives. The focus of the study is developing a gestational and lactational PBPK model in rats and humans for PFOS to aid risk assessment in sensitive human subpopulations.

This study utilized existing PBPK models for PFOS, addressing a data gap of renal reabsorption and excretion in kidneys during gestation and lactation. The model was calibrated with previously published rat toxicokinetic and human biomonitoring data, and Monte Carlo simulation was used to address the inter-individual variability. Model simulations were generally well correlated with observed PFOS concentrations in maternal, fetal and neonatal plasma and liver in rats and humans.

“The latest manuscript describes a PBPK model for PFOS in sensitive subpopulations, including pregnant women, fetuses, lactating women and neonates,” said Lin. “This study provides a quantitative tool to aid risk re-evaluation of PFOS, especially in sensitive human subpopulations.”

The results support the importance of renal reabsorption and excretion during pregnancy and lactation in PFOS dosimetry and suggest that the derivation of health-based toxicity values based on developmental toxicity studies should consider gestational/lactational dosimetry estimated from a life stage-appropriate PBPK model.

The DOI address of the 2019 manuscript is https://doi.org/10.1016/j.envint.2019.03.058; the 2020 manuscript https://doi.org/10.1016/j.envint.2020.105581; and the 2021 manuscript https://doi.org/10.1289/EHP7671.

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