Literature DB >> 20465524

Computational science in drug metabolism and toxicology.

Luis G Valerio1.   

Abstract

Computational scientific tools involving construction and testing of models, screening and data mining for drug and chemical induced toxicities and metabolism have significantly grown in experimental use to help guide product development and assist by enhancing certain areas of regulatory decision making. This themed issue of the journal entitled Computational Science in Drug Metabolism & Toxicology contains state-of-the-art review articles and perspectives covering a diversity of in silico approaches. Computational science tools have a strong potential for expediting our further understanding of drug metabolism and toxicity and are continually being developed and validated. The reader will gain an understanding of the current state of in silico tools and modeling approaches aimed at reducing these liabilities. In addition, how these tools are tested and developed for use in drug safety to support drug development efforts and a review of how they are used to predict genotoxic liabilities are covered in this issue. Computational science tools when properly validated and used judiciously can lend themselves as enablers to support drug safety assessment in investigative and applied settings.

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Year:  2010        PMID: 20465524     DOI: 10.1517/17425255.2010.486789

Source DB:  PubMed          Journal:  Expert Opin Drug Metab Toxicol        ISSN: 1742-5255            Impact factor:   4.481


  2 in total

Review 1.  In silico toxicology models and databases as FDA Critical Path Initiative toolkits.

Authors:  Luis G Valerio
Journal:  Hum Genomics       Date:  2011-03       Impact factor: 4.639

2.  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 in total

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