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In silicotoxicology: computational methods for the prediction of chemical toxicity
- Source :
- Wiley Interdisciplinary Reviews: Computational Molecular Science. 6:147-172
- Publication Year :
- 2016
- Publisher :
- Wiley, 2016.
-
Abstract
- 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. WIREs Comput Mol Sci 2016, 6:147-172. doi: 10.1002/wcms.1240 For further resources related to this article, please visit the WIREs website.
- Subjects :
- 0301 basic medicine
Chemical toxicity
Computer science
In silico
010501 environmental sciences
computer.software_genre
01 natural sciences
Biochemistry
Expert system
Computer Science Applications
Toxicology
03 medical and health sciences
Computational Mathematics
030104 developmental biology
Modelling methods
Toxicity
Materials Chemistry
Physical and Theoretical Chemistry
computer
Predictive modelling
0105 earth and related environmental sciences
Subjects
Details
- ISSN :
- 17590876
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- Wiley Interdisciplinary Reviews: Computational Molecular Science
- Accession number :
- edsair.doi...........6d0914c4f3b3740e5ca11fac8933b677