SAR and QSAR modeling of a large collection of LD 50 rat acute oral toxicity data
The median lethal dose for rodent oral acute toxicity (LD50) is a standard piece of information required to categorize chemicals in terms of the potential hazard posed to human health after acute exposure. The exclusive use of in vivo testing is limited by the time and costs required for performing...
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Published in | Journal of cheminformatics Vol. 11; no. 1; p. 58 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
30.08.2019
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Subjects | |
Online Access | Get full text |
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Abstract | The median lethal dose for rodent oral acute toxicity (LD50) is a standard piece of information required to categorize chemicals in terms of the potential hazard posed to human health after acute exposure. The exclusive use of in vivo testing is limited by the time and costs required for performing experiments and by the need to sacrifice a number of animals. (Quantitative) structure-activity relationships [(Q)SAR] proved a valid alternative to reduce and assist in vivo assays for assessing acute toxicological hazard. In the framework of a new international collaborative project, the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods and the U.S. Environmental Protection Agency's National Center for Computational Toxicology compiled a large database of rat acute oral LD50 data, with the aim of supporting the development of new computational models for predicting five regulatory relevant acute toxicity endpoints. In this article, a series of regression and classification computational models were developed by employing different statistical and knowledge-based methodologies. External validation was performed to demonstrate the real-life predictability of models. Integrated modeling was then applied to improve performance of single models. Statistical results confirmed the relevance of developed models in regulatory frameworks, and confirmed the effectiveness of integrated modeling. The best integrated strategies reached RMSEs lower than 0.50 and the best classification models reached balanced accuracies over 0.70 for multi-class and over 0.80 for binary endpoints. Computed predictions will be hosted on the EPA's Chemistry Dashboard and made freely available to the scientific community. |
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AbstractList | The median lethal dose for rodent oral acute toxicity (LD50) is a standard piece of information required to categorize chemicals in terms of the potential hazard posed to human health after acute exposure. The exclusive use of in vivo testing is limited by the time and costs required for performing experiments and by the need to sacrifice a number of animals. (Quantitative) structure-activity relationships [(Q)SAR] proved a valid alternative to reduce and assist in vivo assays for assessing acute toxicological hazard. In the framework of a new international collaborative project, the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods and the U.S. Environmental Protection Agency's National Center for Computational Toxicology compiled a large database of rat acute oral LD50 data, with the aim of supporting the development of new computational models for predicting five regulatory relevant acute toxicity endpoints. In this article, a series of regression and classification computational models were developed by employing different statistical and knowledge-based methodologies. External validation was performed to demonstrate the real-life predictability of models. Integrated modeling was then applied to improve performance of single models. Statistical results confirmed the relevance of developed models in regulatory frameworks, and confirmed the effectiveness of integrated modeling. The best integrated strategies reached RMSEs lower than 0.50 and the best classification models reached balanced accuracies over 0.70 for multi-class and over 0.80 for binary endpoints. Computed predictions will be hosted on the EPA's Chemistry Dashboard and made freely available to the scientific community. |
Author | Lavado, Giovanna J Gadaleta, Domenico Benfenati, Emilio Mansouri, Kamel Vuković, Kristijan Roncaglioni, Alessandra Karmaus, Agnes L Kleinstreuer, Nicole C Toma, Cosimo |
Author_xml | – sequence: 1 givenname: Domenico orcidid: 0000-0002-3154-5930 surname: Gadaleta fullname: Gadaleta, Domenico email: domenico.gadaleta@marionegri.it organization: Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy. domenico.gadaleta@marionegri.it – sequence: 2 givenname: Kristijan surname: Vuković fullname: Vuković, Kristijan organization: Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy – sequence: 3 givenname: Cosimo surname: Toma fullname: Toma, Cosimo organization: Institute for Risk Assessment Sciences, Utrecht University, PO Box 80177, 3508 TD, Utrecht, The Netherlands – sequence: 4 givenname: Giovanna J surname: Lavado fullname: Lavado, Giovanna J organization: Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy – sequence: 5 givenname: Agnes L surname: Karmaus fullname: Karmaus, Agnes L organization: Integrated Laboratory Systems, Research Triangle Park, NC, 27560, USA – sequence: 6 givenname: Kamel surname: Mansouri fullname: Mansouri, Kamel organization: Integrated Laboratory Systems, Research Triangle Park, NC, 27560, USA – sequence: 7 givenname: Nicole C surname: Kleinstreuer fullname: Kleinstreuer, Nicole C organization: NTP Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27560, USA – sequence: 8 givenname: Emilio surname: Benfenati fullname: Benfenati, Emilio organization: Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy – sequence: 9 givenname: Alessandra surname: Roncaglioni fullname: Roncaglioni, Alessandra organization: Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy |
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Keywords | LD50 Computational toxicology Acute rat oral toxicity Integrated modeling (Q)SAR |
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Title | SAR and QSAR modeling of a large collection of LD 50 rat acute oral toxicity data |
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