Computational toxicology: a tool for all industries

Statistical, expert system, and machine learning methods among others have been used to develop in silico tools for the prediction of toxicological hazard from chemical structure. The models are being applied to the mammalian and environmental toxicological assessment of chemicals across a range of...

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Bibliographic Details
Published in:Wiley interdisciplinary reviews. Computational molecular science 2012-05, Vol.2 (3), p.424-434
Main Author: Marchant, Carol A.
Format: Article
Language:English
Subjects:
Chemical industry
Chemicals
Computer applications
Cosmetics
Environmental assessment
Environmental law
Environmental legislation
Expert systems
Food
Food industry
Industry
Learning algorithms
Legislation
Machine learning
Molecular weight
Nanoparticles
Organic chemicals
Organic chemistry
Proteins
Software
Toxicity
Toxicology
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Summary:Statistical, expert system, and machine learning methods among others have been used to develop in silico tools for the prediction of toxicological hazard from chemical structure. The models are being applied to the mammalian and environmental toxicological assessment of chemicals across a range of industries including cosmetics, foods, industrial chemicals, and pharmaceuticals. Their use within a regulatory environment has also been encouraged by recent legislation. Generally, the models address the potential toxicity of low to medium molecular weight organic chemicals but models for other chemical types such as proteins and nanoparticles have also received some attention. © 2011 John Wiley & Sons, Ltd. This article is categorized under: Computer and Information Science > Chemoinformatics
ISSN:1759-0876
1759-0884
DOI:10.1002/wcms.100