In silico toxicology: computational methods for the prediction of chemical toxicity
Type
ArticleAuthors
Raies, Arwa B.
Bajic, Vladimir B.

KAUST Department
Computational Bioscience Research Center (CBRC)Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
Date
2016-01-06Online Publication Date
2016-01-06Print Publication Date
2016-03Permanent link to this record
http://hdl.handle.net/10754/593340
Metadata
Show full item recordAbstract
Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.Citation
In silico toxicology: computational methods for the prediction of chemical toxicity 2016:n/a Wiley Interdisciplinary Reviews: Computational Molecular SciencePublisher
WileyPubMed ID
27066112Additional Links
http://doi.wiley.com/10.1002/wcms.1240ae974a485f413a2113503eed53cd6c53
10.1002/wcms.1240
Scopus Count
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