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Article: Development of physiologically based toxicokinetic models for 3-monochloropropane-1,2-diol and glycidol

TitleDevelopment of physiologically based toxicokinetic models for 3-monochloropropane-1,2-diol and glycidol
Authors
Keywords3-monochloropropane-1,2-diol
Biomarker
Glycidol
Physiologically based toxicokinetic model
Risk assessment
Issue Date2023
Citation
Food and Chemical Toxicology, 2023, v. 172, article no. 113555 How to Cite?
Abstract3-Monochloropropane-1,2-diol (3-MCPD), glycidol, together with their fatty acid esters are commonly presented in various food and have shown carcinogenicity in various laboratory animals. Public health risk assessment of 3-MPCD and glycidol exposure relies on quantitative tools that represent their in vivo toxicokinetics. In order to better understand the absorption, distribution, metabolism, and excretion profiles of 3-MCPD and glycidol in male rats, a physiologically based pharmacokinetic (PBTK) model was developed. The model's predictive power was evaluated by comparing in silico simulations to in vivo time course data obtained from experimental studies. Results indicate that our PBTK model successfully captured the toxicokinetics of both free chemicals in key organs, and their metabolites in accessible biological fluids. With the validated PBTK model, we then gave an animal-free example on how to extrapolate the toxicological knowledge acquired from a single gavage to a realistic dietary intake scenario. Three biomarkers, free compound in serum, urinary metabolite DHPMA, and glycidol-hemoglobin adduct (diHOPrVal) were selected for in silico simulation following constant dietary intakes, and their internal levels were correlated with proposed external daily exposure via reverse dosimetry approaches. Taken together, our model provides a computational approach for extrapolating animal toxicokinetic experiments to biomonitoring measurement and risk assessment.
Persistent Identifierhttp://hdl.handle.net/10722/342257
ISSN
2023 Impact Factor: 3.9
2023 SCImago Journal Rankings: 0.780
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorJia, Wei-
dc.contributor.authorJiang, Jiahao-
dc.contributor.authorKe, Xing-
dc.contributor.authorZhang, Lange-
dc.contributor.authorLi, Yaoran-
dc.contributor.authorWan, Xuzhi-
dc.contributor.authorJiao, Jingjing-
dc.contributor.authorZhang, Yu-
dc.date.accessioned2024-04-17T07:02:30Z-
dc.date.available2024-04-17T07:02:30Z-
dc.date.issued2023-
dc.identifier.citationFood and Chemical Toxicology, 2023, v. 172, article no. 113555-
dc.identifier.issn0278-6915-
dc.identifier.urihttp://hdl.handle.net/10722/342257-
dc.description.abstract3-Monochloropropane-1,2-diol (3-MCPD), glycidol, together with their fatty acid esters are commonly presented in various food and have shown carcinogenicity in various laboratory animals. Public health risk assessment of 3-MPCD and glycidol exposure relies on quantitative tools that represent their in vivo toxicokinetics. In order to better understand the absorption, distribution, metabolism, and excretion profiles of 3-MCPD and glycidol in male rats, a physiologically based pharmacokinetic (PBTK) model was developed. The model's predictive power was evaluated by comparing in silico simulations to in vivo time course data obtained from experimental studies. Results indicate that our PBTK model successfully captured the toxicokinetics of both free chemicals in key organs, and their metabolites in accessible biological fluids. With the validated PBTK model, we then gave an animal-free example on how to extrapolate the toxicological knowledge acquired from a single gavage to a realistic dietary intake scenario. Three biomarkers, free compound in serum, urinary metabolite DHPMA, and glycidol-hemoglobin adduct (diHOPrVal) were selected for in silico simulation following constant dietary intakes, and their internal levels were correlated with proposed external daily exposure via reverse dosimetry approaches. Taken together, our model provides a computational approach for extrapolating animal toxicokinetic experiments to biomonitoring measurement and risk assessment.-
dc.languageeng-
dc.relation.ispartofFood and Chemical Toxicology-
dc.subject3-monochloropropane-1,2-diol-
dc.subjectBiomarker-
dc.subjectGlycidol-
dc.subjectPhysiologically based toxicokinetic model-
dc.subjectRisk assessment-
dc.titleDevelopment of physiologically based toxicokinetic models for 3-monochloropropane-1,2-diol and glycidol-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.fct.2022.113555-
dc.identifier.pmid36493944-
dc.identifier.scopuseid_2-s2.0-85144254634-
dc.identifier.volume172-
dc.identifier.spagearticle no. 113555-
dc.identifier.epagearticle no. 113555-
dc.identifier.eissn1873-6351-
dc.identifier.isiWOS:000910033300001-

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