{"title":"根据静脉血浓度和不确定的生理药代动力学模型重建挥发性有机化合物的暴露量","authors":"L. Simon, M.K. Prakasha","doi":"10.1016/j.comtox.2024.100336","DOIUrl":null,"url":null,"abstract":"<div><div>Physiologically-based pharmacokinetic modeling was applied to determine exposures to volatile organic compounds, specifically focusing on m-xylene. Passive diffusion was used to describe permeation through the skin. The proposed model agreed with the experimental data and allowed researchers to monitor the concentration profiles in different compartments. The study also focused on the impact of parameter uncertainty on the model predictions. Local and global sensitivity analyses evaluated the influence of partition parameters, diffusion coefficients in the skin, and metabolic parameters on the blood concentration. Both methods show that the Michaelis-Menten kinetics and the lean tissue:blood partition coefficients contributed the most to the total variability. A reverse dosimetry approach used the measured biomarker level to estimate the exposure dose in four hours. The results aligned with experimental data when simulations were conducted using random parameters selected within twenty-five percent of the mean.</div></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"32 ","pages":"Article 100336"},"PeriodicalIF":3.1000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconstruction of exposure to volatile organic compounds from venous blood concentration and an uncertain physiologically-based pharmacokinetic model\",\"authors\":\"L. Simon, M.K. Prakasha\",\"doi\":\"10.1016/j.comtox.2024.100336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Physiologically-based pharmacokinetic modeling was applied to determine exposures to volatile organic compounds, specifically focusing on m-xylene. Passive diffusion was used to describe permeation through the skin. The proposed model agreed with the experimental data and allowed researchers to monitor the concentration profiles in different compartments. The study also focused on the impact of parameter uncertainty on the model predictions. Local and global sensitivity analyses evaluated the influence of partition parameters, diffusion coefficients in the skin, and metabolic parameters on the blood concentration. Both methods show that the Michaelis-Menten kinetics and the lean tissue:blood partition coefficients contributed the most to the total variability. A reverse dosimetry approach used the measured biomarker level to estimate the exposure dose in four hours. The results aligned with experimental data when simulations were conducted using random parameters selected within twenty-five percent of the mean.</div></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":\"32 \",\"pages\":\"Article 100336\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111324000380\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111324000380","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
Reconstruction of exposure to volatile organic compounds from venous blood concentration and an uncertain physiologically-based pharmacokinetic model
Physiologically-based pharmacokinetic modeling was applied to determine exposures to volatile organic compounds, specifically focusing on m-xylene. Passive diffusion was used to describe permeation through the skin. The proposed model agreed with the experimental data and allowed researchers to monitor the concentration profiles in different compartments. The study also focused on the impact of parameter uncertainty on the model predictions. Local and global sensitivity analyses evaluated the influence of partition parameters, diffusion coefficients in the skin, and metabolic parameters on the blood concentration. Both methods show that the Michaelis-Menten kinetics and the lean tissue:blood partition coefficients contributed the most to the total variability. A reverse dosimetry approach used the measured biomarker level to estimate the exposure dose in four hours. The results aligned with experimental data when simulations were conducted using random parameters selected within twenty-five percent of the mean.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs