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October 18, 2025European Journal of Medical and Health Research2 citationsOpen Access

Computational Toxicokinetics of Endocrine-Disrupting Chemicals in Humans Using Physiologically Based Pharmacokinetic (PBPK) Models

IOIsaac OdoiKwame Nkrumah University of Science and Technology IOIrhiogbe Wilfred OmwenkeEdo State University Uzairue UEUbong Bernard EssienUniversity of Port Harcourt

Key Points

PBPK models effectively model absorption, distribution, metabolism, and elimination of endocrine-disrupting chemicals.
Results indicate significant differences in half-lives and retention rates of chemicals like bisphenol A and polychlorinated biphenyls.
The analysis highlights an increase in regulatory engagements by authorities like EFSA and USEPA for chemical safety.
Future research aims to enhance biomonitoring, mixture modelling, and inclusion of at-risk populations in toxicity assessments.

Abstract

Endocrine-disrupting chemicals (EDCs) are widespread environmental pollutants that disrupt hormonal control and lead to reproductive, developmental, and metabolic issues. They have complicated dynamics that require heavy computational capabilities not available from conventional pharmacokinetic and animal studies. This paper critically presents the role of Physiologically-Based Pharmacokinetic (PBPK) models in EDC toxicokinetics by summarising the most recent literature (2020-2025) on toxic compounds, including bisphenol A, phthalates, polychlorinated biphenyls, dioxin, and per- and polyfluoroalkyl compounds. The results indicate that the PBPK models are relatively useful in modelling absorption, distribution, metabolism, and elimination processes, indicating small half-lives with compounds that are rapidly metabolised (for instance, Bisphenol A (BPA)), long-term retention in lipophilic they polluted (such as Polychlorinated Biphenyls (PCBs), but not Per- and Polyfluoroalkyl Substances (PFAS)), and high variability between life-decodes and populations. The models have almost doubled the interpretation of biomonitoring data, aiding in the damage of risk to specific life stages, and understanding of this and more applications by regulatory authorities like the European Food Safety Authority (EFSA) and the United States Environmental Protection Agency (USEPA) are on the rise. PBPK modelling, therefore, possesses mechanistic, predictive strengths in comparison with traditional models. Future research must increase biomonitoring and In Vitro–In Vivo Extrapolation (IVIVE) data, enhance mixture modelling, include at-risk populations, and cultivate harmonised global platforms to adopt a regulating framework in an attempt to maximise effects.

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