Document Detail


Computational toxicology approaches at the US Food and Drug Administration.
MedLine Citation:
PMID:  20017581     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Chihae Yang; Luis G Valerio; Kirk B Arvidson
Publication Detail:
Type:  Journal Article; Review    
Journal Detail:
Title:  Alternatives to laboratory animals : ATLA     Volume:  37     ISSN:  0261-1929     ISO Abbreviation:  Altern Lab Anim     Publication Date:  2009 Nov 
Date Detail:
Created Date:  2009-12-18     Completed Date:  2010-03-25     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8110074     Medline TA:  Altern Lab Anim     Country:  England    
Other Details:
Languages:  eng     Pagination:  523-31     Citation Subset:  IM    
Copyright Information:
2009 FRAME.
Affiliation:
Office of Food Additive Safety, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, USA. chihae.yang@fda.hhs.gov
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MeSH Terms
Descriptor/Qualifier:
Computational Biology / methods*
Database Management Systems*
Databases, Factual*
Humans
Knowledge Bases*
Pharmaceutical Preparations / chemistry
Quantitative Structure-Activity Relationship
Toxicology / methods*
United States
United States Food and Drug Administration
Chemical
Reg. No./Substance:
0/Pharmaceutical Preparations

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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