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Mechanistic Computational Model for Extrapolating In vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats.
Citation:
Handa, S., I. Hassan, Mary E. Gilbert, AND H. El-Masri. Mechanistic Computational Model for Extrapolating In vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 183(1):36-48, (2021). https://doi.org/10.1093/toxsci/kfab074
Impact/Purpose:
While in vitro high throughput (HTP) assays can be used to screen thyroid disrupting chemicals (TDC), they can be used to inform the health risk assessments for the chemicals. This assessment is based on thyroid hormones (THs) in vivo serum levels. Furthermore, the in vitro HTP assays cannot be linked to varying environmental exposure levels. An integrative computational model including chemical specific physiologically based pharmacokinetic (PBPK) and TH kinetics models is developed to provide a mechanistic quantitative approach to translate thyroidal in vitro HTP assays to in vivo measures of circulating THs serum levels. When combined with quantitative methods and literature data to obtain chemical specific kinetic parameters for PBPK modeling, this integrative modeling approach can be generalized across many chemicals and exposure scenarios for TDCs.
Description:
High-throughput in vitro assays are developed to screen chemicals for their potential to inhibit thyroid hormones (THs) synthesis. Some of these experiments, such as the thyroid peroxidase (TPO) inhibition assay, are based on thyroid microsomal extracts. However, the regulation of thyroid disruption chemicals is based on THs in vivo serum levels. This necessitates the estimation of thyroid disruption chemicals in vivo tissue levels in the thyroid where THs synthesis inhibition by TPO takes place. The in vivo tissue levels of chemicals are controlled by pharmacokinetic determinants such as absorption, distribution, metabolism, and excretion, and can be described quantitatively in physiologically based pharmacokinetic (PBPK) models. An integrative computational model including chemical-specific PBPK and TH kinetics models provides a mechanistic quantitative approach to translate thyroidal high-throughput in vitro assays to in vivo measures of circulating THs serum levels. This computational framework is developed to quantitatively establish the linkage between applied dose, chemical thyroid tissue levels, thyroid TPO inhibition potential, and in vivo TH serum levels. Once this link is established quantitatively, the overall model is used to calibrate the TH kinetics parameters using experimental data for THs levels in thyroid tissue and serum for the 2 drugs, propylthiouracil and methimazole. The calibrated quantitative framework is then evaluated against literature data for the environmental chemical ethylenethiourea. The linkage of PBPK and TH kinetics models illustrates a computational framework that can be extrapolated to humans to screen chemicals based on their exposure levels and potential to disrupt serum THs levels in vivo.
URLs/Downloads:
DOI: Mechanistic Computational Model for Extrapolating In vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats.
https://pubmed.ncbi.nlm.nih.gov/34117770/