Literature DB >> 34117770

Mechanistic Computational Model for Extrapolating In Vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats.

Sakshi Handa1, Iman Hassan2, Mary Gilbert3, Hisham El-Masri1.   

Abstract

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. Published by Oxford University Press on behalf of the Society of Toxicology 2021. This work is written by US Government employees and is in the public domain in the US.

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Keywords:  IVIVE; PBPK; thyroid

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Year:  2021        PMID: 34117770      PMCID: PMC8771814          DOI: 10.1093/toxsci/kfab074

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.109


  48 in total

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Authors:  Wei-Wei Shang; Jian Luo; Wei-Bo Cheng; Qin Huang; Wen-Dong Wang
Journal:  Sichuan Da Xue Xue Bao Yi Xue Ban       Date:  2010-05

2.  Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions.

Authors:  Trudy Rodgers; Malcolm Rowland
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Journal:  Endocrinology       Date:  1977-08       Impact factor: 4.736

4.  Estimating Margin of Exposure to Thyroid Peroxidase Inhibitors Using High-Throughput in vitro Data, High-Throughput Exposure Modeling, and Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling.

Authors:  Jeremy A Leonard; Yu-Mei Tan; Mary Gilbert; Kristin Isaacs; Hisham El-Masri
Journal:  Toxicol Sci       Date:  2016-02-10       Impact factor: 4.849

5.  Evaluation of perturbations in serum thyroid hormones during human pregnancy due to dietary iodide and perchlorate exposure using a biologically based dose-response model.

Authors:  Annie Lumen; David R Mattie; Jeffrey W Fisher
Journal:  Toxicol Sci       Date:  2013-03-27       Impact factor: 4.849

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Journal:  Endocrinology       Date:  1983-09       Impact factor: 4.736

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Review 8.  General background on the hypothalamic-pituitary-thyroid (HPT) axis.

Authors:  R Thomas Zoeller; Shirlee W Tan; Rochelle W Tyl
Journal:  Crit Rev Toxicol       Date:  2007 Jan-Feb       Impact factor: 5.635

9.  A rapid assay of human thyroid peroxidase activity.

Authors:  Hongyan Dong; Marlena Godlewska; Michael G Wade
Journal:  Toxicol In Vitro       Date:  2019-10-16       Impact factor: 3.500

10.  Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing.

Authors:  Barbara A Wetmore; John F Wambaugh; Brittany Allen; Stephen S Ferguson; Mark A Sochaski; R Woodrow Setzer; Keith A Houck; Cory L Strope; Katherine Cantwell; Richard S Judson; Edward LeCluyse; Harvey J Clewell; Russell S Thomas; Melvin E Andersen
Journal:  Toxicol Sci       Date:  2015-08-06       Impact factor: 4.849

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  1 in total

Review 1.  Intrathyroidal feedforward and feedback network regulating thyroid hormone synthesis and secretion.

Authors:  Li Jing; Qiang Zhang
Journal:  Front Endocrinol (Lausanne)       Date:  2022-09-15       Impact factor: 6.055

  1 in total

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