Bohan Hu, Hans J.H.J. van den Berg, Ivonne M.C.M. Rietjens, Nico W. van den Brink
{"title":"预测大鼠口服吡虫啉和多菌灵后体内和体外剂量水平的 PBK 模型","authors":"Bohan Hu, Hans J.H.J. van den Berg, Ivonne M.C.M. Rietjens, Nico W. van den Brink","doi":"10.1016/j.comtox.2024.100321","DOIUrl":null,"url":null,"abstract":"<div><p>Monitoring oral exposure to pesticides in wildlife is crucial for assessing environmental risks and preventing adverse effects on non-target species. Traditionally, this requires invasive tissue sampling, raising ethical, regulatory, and economic concerns. To address this gap, our study aims to develop a method for assessing external oral dose levels in rats using physiologically-based kinetic (PBK) modeling based on blood concentration levels of two pesticides, imidacloprid and carbendazim, and one of their primary metabolites. We utilized <em>in vitro</em> metabolic kinetic data from hepatic microsomal and S9 incubations to inform our models. These models were then evaluated by comparing their predictions with existing <em>in vivo</em> experimental data from the literature. Our results demonstrate that the models provide accurate predictions, presenting a novel <em>in vitro</em> and <em>in silico</em> approach for environmental exposure and risk assessment of pesticides. This methodology has the potential for application in wildlife species, advancing the frontier of knowledge in non-invasive pesticide exposure assessment.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468111324000239/pdfft?md5=da6bee24a4252857f106dd35f4ca3b45&pid=1-s2.0-S2468111324000239-main.pdf","citationCount":"0","resultStr":"{\"title\":\"PBK models to predict internal and external dose levels following oral exposure of rats to imidacloprid and carbendazim\",\"authors\":\"Bohan Hu, Hans J.H.J. van den Berg, Ivonne M.C.M. Rietjens, Nico W. van den Brink\",\"doi\":\"10.1016/j.comtox.2024.100321\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Monitoring oral exposure to pesticides in wildlife is crucial for assessing environmental risks and preventing adverse effects on non-target species. Traditionally, this requires invasive tissue sampling, raising ethical, regulatory, and economic concerns. To address this gap, our study aims to develop a method for assessing external oral dose levels in rats using physiologically-based kinetic (PBK) modeling based on blood concentration levels of two pesticides, imidacloprid and carbendazim, and one of their primary metabolites. We utilized <em>in vitro</em> metabolic kinetic data from hepatic microsomal and S9 incubations to inform our models. These models were then evaluated by comparing their predictions with existing <em>in vivo</em> experimental data from the literature. Our results demonstrate that the models provide accurate predictions, presenting a novel <em>in vitro</em> and <em>in silico</em> approach for environmental exposure and risk assessment of pesticides. This methodology has the potential for application in wildlife species, advancing the frontier of knowledge in non-invasive pesticide exposure assessment.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2468111324000239/pdfft?md5=da6bee24a4252857f106dd35f4ca3b45&pid=1-s2.0-S2468111324000239-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111324000239\",\"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/S2468111324000239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
PBK models to predict internal and external dose levels following oral exposure of rats to imidacloprid and carbendazim
Monitoring oral exposure to pesticides in wildlife is crucial for assessing environmental risks and preventing adverse effects on non-target species. Traditionally, this requires invasive tissue sampling, raising ethical, regulatory, and economic concerns. To address this gap, our study aims to develop a method for assessing external oral dose levels in rats using physiologically-based kinetic (PBK) modeling based on blood concentration levels of two pesticides, imidacloprid and carbendazim, and one of their primary metabolites. We utilized in vitro metabolic kinetic data from hepatic microsomal and S9 incubations to inform our models. These models were then evaluated by comparing their predictions with existing in vivo experimental data from the literature. Our results demonstrate that the models provide accurate predictions, presenting a novel in vitro and in silico approach for environmental exposure and risk assessment of pesticides. This methodology has the potential for application in wildlife species, advancing the frontier of knowledge in non-invasive pesticide exposure assessment.
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