Literature DB >> 29934896

Computational Toxicology and Drug Discovery.

Catrin Hasselgren1,2, Glenn J Myatt3.   

Abstract

The use of computational toxicology methods within drug discovery began in the early 2000s with applications such as predicting bacterial mutagenicity and hERG inhibition. The field has been continuously expanding ever since and the tasks at hand have become more complex. These approaches are now strategically integrated into the risk assessment process, as a complement to in vitro and in vivo methods. Today, computational toxicology can be used in every phase of drug discovery and development, from profiling large libraries early on, to predicting off-target effects in the mid-discovery phase, to assessing potential mutagenic impurities in development and degradants as part of life-cycle management. This chapter provides an overview of the field and describes the application of computational toxicology throughout the entire discovery and development process.

Entities:  

Keywords:  Computational toxicology; Drug discovery; Hit identification; Lead identification; Lead optimization

Mesh:

Year:  2018        PMID: 29934896     DOI: 10.1007/978-1-4939-7899-1_11

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  The rapid development of computational toxicology.

Authors:  Hermann M Bolt; Jan G Hengstler
Journal:  Arch Toxicol       Date:  2020-05-07       Impact factor: 5.153

2.  STopTox: An in Silico Alternative to Animal Testing for Acute Systemic and Topical Toxicity.

Authors:  Joyce V B Borba; Vinicius M Alves; Rodolpho C Braga; Daniel R Korn; Kirsten Overdahl; Arthur C Silva; Steven U S Hall; Erik Overdahl; Nicole Kleinstreuer; Judy Strickland; David Allen; Carolina Horta Andrade; Eugene N Muratov; Alexander Tropsha
Journal:  Environ Health Perspect       Date:  2022-02-22       Impact factor: 11.035

  2 in total

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