NDLI: (Q)SAR: A Tool for the Toxicologist.

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(Q)SAR: A Tool for the Toxicologist.

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(Q)SAR: A Tool for the Toxicologist.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Steinbach, Thomas Gad-McDonald, Samantha Kruhlak, Naomi Powley, Mark Greene, Nigel
Description	Country affiliation: United States Author Affiliation: Steinbach T ( EPL, Inc, Res Triangle Park, NC, USA tsteinbach@epl-inc.com.); Gad-McDonald S ( Gad Consulting Services, Raleigh, NC, USA.); Kruhlak N ( Division of Drug Safety Research, US FDA, Silver Spring, MD, USA.); Powley M ( Division of Antiviral Products, Office of New Drugs, US FDA, Silver Spring, MD, USA.); Greene N ( Pfizer Global R&D, Groton, CT, USA.)
Abstract	A continuing education (CE) course at the 2014 American College of Toxicology annual meeting covered the topic of (Quantitative) Structure-Activity Relationships [(Q)SAR]. The (Q)SAR methodologies use predictive computer modeling based on predefined rules to describe the relationship between chemical structure and a chemical's associated biological activity or statistical tools to find correlations between biologic activity and the molecular structure or properties of a compound. The (Q)SAR has applications in risk assessment, drug discovery, and regulatory decision making. Pressure within industry to reduce the cost of drug development and societal pressure for government regulatory agencies to produce more accurate and timely risk assessment of drugs and chemicals have necessitated the use of (Q)SAR. Producing a high-quality (Q)SAR model depends on many factors including the choice of statistical methods and descriptors, but first and foremost the quality of the data input into the model. Understanding how a (Q)SAR model is developed and applied is critical to the successful use of such a tool. The CE session covered the basic principles of (Q)SAR, practical applications of these computational models in toxicology, how regulatory agencies use and interpret (Q)SAR models, and potential pitfalls of using them.
File Format	HTM / HTML
ISSN	10915818
Issue Number	4
Volume Number	34
e-ISSN	1092874X
Journal	International Journal of Toxicology
Language	English
Publisher	Sage Publication
Publisher Date	2015-07-01
Publisher Place	United States
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discipline Toxicology Quantitative Structure-activity Relationship Toxicity Tests Methods Computer Simulation Congresses As Topic Humans Molecular Structure Risk Assessment Journal Article
Content Type	Text
Resource Type	Article
Subject	Toxicology

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