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Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity

The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory...

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Autores principales: Selvestrel, Gianluca, Lavado, Giovanna J., Toropova, Alla P., Toropov, Andrey A., Gadaleta, Domenico, Marzo, Marco, Baderna, Diego, Benfenati, Emilio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9224506/
https://www.ncbi.nlm.nih.gov/pubmed/35743059
http://dx.doi.org/10.3390/ijms23126615
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author Selvestrel, Gianluca
Lavado, Giovanna J.
Toropova, Alla P.
Toropov, Andrey A.
Gadaleta, Domenico
Marzo, Marco
Baderna, Diego
Benfenati, Emilio
author_facet Selvestrel, Gianluca
Lavado, Giovanna J.
Toropova, Alla P.
Toropov, Andrey A.
Gadaleta, Domenico
Marzo, Marco
Baderna, Diego
Benfenati, Emilio
author_sort Selvestrel, Gianluca
collection PubMed
description The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory frameworks, such as the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) and the European Regulation of 1223/2009 on cosmetics. The RDT results for the safety evaluation of chemicals are undeniably important; however, the in vivo tests are time-consuming and very expensive. The in silico models can provide useful input to investigate sub-chronic RDT. Considering the complexity of these endpoints, involving variable experimental designs, this non-testing approach is challenging and attractive. Here, we built eight in silico models for the NOAEL and LOAEL predictions, focusing on systemic and organ-specific toxicity, looking into the effects on the liver, kidney and brain. Starting with the NOAEL and LOAEL data for oral sub-chronic toxicity in rats, retrieved from public databases, we developed and validated eight quantitative structure-activity relationship (QSAR) models based on the optimal descriptors calculated by the Monte Carlo method, using the CORAL software. The results obtained with these models represent a good achievement, to exploit them in a safety assessment, considering the importance of organ-related toxicity.
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spelling pubmed-92245062022-06-24 Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity Selvestrel, Gianluca Lavado, Giovanna J. Toropova, Alla P. Toropov, Andrey A. Gadaleta, Domenico Marzo, Marco Baderna, Diego Benfenati, Emilio Int J Mol Sci Article The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory frameworks, such as the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) and the European Regulation of 1223/2009 on cosmetics. The RDT results for the safety evaluation of chemicals are undeniably important; however, the in vivo tests are time-consuming and very expensive. The in silico models can provide useful input to investigate sub-chronic RDT. Considering the complexity of these endpoints, involving variable experimental designs, this non-testing approach is challenging and attractive. Here, we built eight in silico models for the NOAEL and LOAEL predictions, focusing on systemic and organ-specific toxicity, looking into the effects on the liver, kidney and brain. Starting with the NOAEL and LOAEL data for oral sub-chronic toxicity in rats, retrieved from public databases, we developed and validated eight quantitative structure-activity relationship (QSAR) models based on the optimal descriptors calculated by the Monte Carlo method, using the CORAL software. The results obtained with these models represent a good achievement, to exploit them in a safety assessment, considering the importance of organ-related toxicity. MDPI 2022-06-14 /pmc/articles/PMC9224506/ /pubmed/35743059 http://dx.doi.org/10.3390/ijms23126615 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Selvestrel, Gianluca
Lavado, Giovanna J.
Toropova, Alla P.
Toropov, Andrey A.
Gadaleta, Domenico
Marzo, Marco
Baderna, Diego
Benfenati, Emilio
Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity
title Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity
title_full Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity
title_fullStr Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity
title_full_unstemmed Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity
title_short Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity
title_sort monte carlo models for sub-chronic repeated-dose toxicity: systemic and organ-specific toxicity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9224506/
https://www.ncbi.nlm.nih.gov/pubmed/35743059
http://dx.doi.org/10.3390/ijms23126615
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