Literature DB >> 20017581

Computational toxicology approaches at the US Food and Drug Administration.

Chihae Yang1, Luis G Valerio, Kirk B Arvidson.   

Abstract

For over a decade, the United States Food and Drug Administration (US FDA) has been engaged in the applied research, development, and evaluation of computational toxicology methods used to support the safety evaluation of a diverse set of regulated products. The basis for evaluating computational toxicology methods is multi-factorial, including the potential for increased efficiency, reduction in the numbers of animals used, lower costs, and the need to explore emerging technologies that support the goals of the US FDA's Critical Path Initiative (e.g. to make decision support information available early in the drug review process). The US FDA's efforts have been facilitated by agency-approved data-sharing agreements between government and commercial software developers. This commentary review describes former and current scientific initiatives at the agency, in the area of computational toxicology methods. In particular, toxicology-based QSAR models, ToxML databases and knowledgebases will be addressed. Notably, many of the computational toxicology tools available are commercial products - however, several are emerging as non-commercial products, which are freely-available to the public, and which will facilitate the understanding of how these programs work and avoid the "black box" paradigm. Through productive collaborations, the US FDA Center for Drug Evaluation and Research, and the Center for Food Safety and Applied Nutrition, have worked together to evaluate, develop and apply these methods to chemical toxicity endpoints of regulatory interest. 2009 FRAME.

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Year:  2009        PMID: 20017581     DOI: 10.1177/026119290903700509

Source DB:  PubMed          Journal:  Altern Lab Anim        ISSN: 0261-1929            Impact factor:   1.303


  5 in total

Review 1.  Designing antimicrobial peptides: form follows function.

Authors:  Christopher D Fjell; Jan A Hiss; Robert E W Hancock; Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2011-12-16       Impact factor: 84.694

Review 2.  From QSAR to QSIIR: searching for enhanced computational toxicology models.

Authors:  Hao Zhu
Journal:  Methods Mol Biol       Date:  2013

Review 3.  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

4.  The eTOX data-sharing project to advance in silico drug-induced toxicity prediction.

Authors:  Montserrat Cases; Katharine Briggs; Thomas Steger-Hartmann; François Pognan; Philippe Marc; Thomas Kleinöder; Christof H Schwab; Manuel Pastor; Jörg Wichard; Ferran Sanz
Journal:  Int J Mol Sci       Date:  2014-11-14       Impact factor: 5.923

5.  A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.

Authors:  Allan Peter Davis; Thomas C Wiegers; Phoebe M Roberts; Benjamin L King; Jean M Lay; Kelley Lennon-Hopkins; Daniela Sciaky; Robin Johnson; Heather Keating; Nigel Greene; Robert Hernandez; Kevin J McConnell; Ahmed E Enayetallah; Carolyn J Mattingly
Journal:  Database (Oxford)       Date:  2013-11-28       Impact factor: 3.451

  5 in total

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