Literature DB >> 17054413

Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database.

Brigitte Ganter1, Ronald D Snyder, Donald N Halbert, May D Lee.   

Abstract

A range of genomics technologies are increasingly becoming integrated with existing scientific disciplines to broaden and strengthen existing capabilities and open new avenues of research in drug discovery and development. Examples of these new research fields are proteomics, pharmacogenomics, metabolomics and toxicogenomics. Here we review the application of toxicogenomics to improve the evaluation of drug safety, mechanism of action and toxicity in the drug discovery and development process.

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Year:  2006        PMID： 17054413     DOI： 10.2217/14622416.7.7.1025

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN： 1462-2416            Impact factor:   2.533


  39 in total

Review 1.  Mechanisms of drug toxicity and relevance to pharmaceutical development.

Authors:  F Peter Guengerich
Journal:  Drug Metab Pharmacokinet       Date:  2010-10-22       Impact factor: 3.614

2.  Gene expression profiling and its practice in drug development.

Authors:  Murty V Chengalvala; Vargheese M Chennathukuzhi; Daniel S Johnston; Panayiotis E Stevis; Gregory S Kopf
Journal:  Curr Genomics       Date:  2007-06       Impact factor: 2.236

Review 3.  Analysis of the transcriptome in molecular epidemiology studies.

Authors:  Cliona M McHale; Luoping Zhang; Reuben Thomas; Martyn T Smith
Journal:  Environ Mol Mutagen       Date:  2013-08-01       Impact factor: 3.216

4.  In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity.

Authors:  Arianna Bassan; Vinicius M Alves; Alexander Amberg; Lennart T Anger; Scott Auerbach; Lisa Beilke; Andreas Bender; Mark T D Cronin; Kevin P Cross; Jui-Hua Hsieh; Nigel Greene; Raymond Kemper; Marlene T Kim; Moiz Mumtaz; Tobias Noeske; Manuela Pavan; Julia Pletz; Daniel P Russo; Yogesh Sabnis; Markus Schaefer; David T Szabo; Jean-Pierre Valentin; Joerg Wichard; Dominic Williams; David Woolley; Craig Zwickl; Glenn J Myatt
Journal:  Comput Toxicol       Date:  2021-09-09

5.  Integration of Transcriptomics Data and Metabolomic Data Using Biomedical Literature Mining and Pathway Analysis.

Authors:  Archana Prabahar
Journal:  Methods Mol Biol       Date:  2022

Review 6.  Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing.

Authors:  Jiansong Fang; Andrew A Pieper; Ruth Nussinov; Garam Lee; Lynn Bekris; James B Leverenz; Jeffrey Cummings; Feixiong Cheng
Journal:  Med Res Rev       Date:  2020-07-13       Impact factor: 12.944

Review 7.  Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data.

Authors:  Andreas Bender; Isidro Cortes-Ciriano
Journal:  Drug Discov Today       Date:  2021-01-27       Impact factor: 7.851

8.  Comparison of TNFα to lipopolysaccharide as an inflammagen to characterize the idiosyncratic hepatotoxicity potential of drugs: Trovafloxacin as an example.

Authors:  Michael J Liguori; Amy C Ditewig; Jane F Maddox; James P Luyendyk; Lois D Lehman-McKeeman; David M Nelson; Vasanthi M Bhaskaran; Jeffrey F Waring; Patricia E Ganey; Robert A Roth; Eric A G Blomme
Journal:  Int J Mol Sci       Date:  2010-11-18       Impact factor: 5.923

9.  Prediction of pharmacological and xenobiotic responses to drugs based on time course gene expression profiles.

Authors:  Tao Huang; Weiren Cui; Lele Hu; Kaiyan Feng; Yi-Xue Li; Yu-Dong Cai
Journal:  PLoS One       Date:  2009-12-02       Impact factor: 3.240

10.  Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery.

Authors:  Manish Kumar Tripathi; Abhigyan Nath; Tej P Singh; A S Ethayathulla; Punit Kaur
Journal:  Mol Divers       Date:  2021-06-23       Impact factor: 3.364
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