Literature DB >> 19835978

Computational toxicology--a tool for early safety evaluation.

Cédric Merlot1.   

Abstract

Although inappropriate pharmacokinetic properties were a major cause of attrition in the 1990s, safety issues are recognized as today's single largest cause of drug candidate failure. It is expected that the right balance of in vivo, in vitro and computational toxicology predictions applied as early as possible in the discovery process will help to reduce the number of safety issues. This review focuses on recent developments in computational toxicology. Direct modeling of toxic endpoints has been deceiving and hampered the wide acceptance of computer predictions. The current trend is to make simpler predictions, closer to the mechanism of action, and to follow them up with in vitro or in vivo assays as appropriate. Copyright 2009 Elsevier Ltd. All rights reserved.

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Year:  2009        PMID: 19835978     DOI: 10.1016/j.drudis.2009.09.010

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  21 in total

1.  A multiparametric organ toxicity predictor for drug discovery.

Authors:  Chirag N Patel; Sivakumar Prasanth Kumar; Rakesh M Rawal; Daxesh P Patel; Frank J Gonzalez; Himanshu A Pandya
Journal:  Toxicol Mech Methods       Date:  2019-10-29       Impact factor: 2.987

Review 2.  In vitro platforms for evaluating liver toxicity.

Authors:  Shyam Sundhar Bale; Lawrence Vernetti; Nina Senutovitch; Rohit Jindal; Manjunath Hegde; Albert Gough; William J McCarty; Ahmet Bakan; Abhinav Bhushan; Tong Ying Shun; Inna Golberg; Richard DeBiasio; Berk Osman Usta; D Lansing Taylor; Martin L Yarmush
Journal:  Exp Biol Med (Maywood)       Date:  2014-04-24

3.  Shaping the future of safer innovative drugs in Europe.

Authors:  Jordi Mestres; Sharon D Bryant; Ismael Zamora; Johann Gasteiger
Journal:  Nat Biotechnol       Date:  2011-09-08       Impact factor: 54.908

4.  Computer-aided molecular design of 1H-imidazole-2,4-diamine derivatives as potential inhibitors of Plasmodium falciparum DHFR enzyme.

Authors:  Legesse Adane; Prasad V Bharatam
Journal:  J Mol Model       Date:  2010-06-05       Impact factor: 1.810

5.  Prediction of hERG Liability - Using SVM Classification, Bootstrapping and Jackknifing.

Authors:  Hongmao Sun; Ruili Huang; Menghang Xia; Sampada Shahane; Noel Southall; Yuhong Wang
Journal:  Mol Inform       Date:  2016-12-21       Impact factor: 3.353

Review 6.  Paradigm shift in toxicity testing and modeling.

Authors:  Hongmao Sun; Menghang Xia; Christopher P Austin; Ruili Huang
Journal:  AAPS J       Date:  2012-04-20       Impact factor: 4.009

7.  Mapping drug physico-chemical features to pathway activity reveals molecular networks linked to toxicity outcome.

Authors:  Philipp Antczak; Fernando Ortega; J Kevin Chipman; Francesco Falciani
Journal:  PLoS One       Date:  2010-08-27       Impact factor: 3.240

8.  ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling.

Authors:  Tailong Lei; Youyong Li; Yunlong Song; Dan Li; Huiyong Sun; Tingjun Hou
Journal:  J Cheminform       Date:  2016-02-01       Impact factor: 5.514

Review 9.  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

10.  In silico toxicology - non-testing methods.

Authors:  Hannu Raunio
Journal:  Front Pharmacol       Date:  2011-06-30       Impact factor: 5.810

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