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Novel Statistical Tools for Monitoring the Safety of Marketed Drugs
Author(s) -
Almenoff J S,
Pattishall E N,
Gibbs T G,
DuMouchel W,
Evans S J W,
Yuen N
Publication year - 2007
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1038/sj.clpt.6100258
Subject(s) - clinical pharmacology , safety pharmacology , identification (biology) , risk analysis (engineering) , drug reaction , safety monitoring , pharmacovigilance , computer science , patient safety , adverse drug reaction , statistical analysis , medicine , data science , adverse effect , drug , pharmacology , health care , bioinformatics , political science , statistics , botany , mathematics , law , biology
Robust tools for monitoring the safety of marketed therapeutic products are of paramount importance to public health. In recent years, innovative statistical approaches have been developed to screen large post‐marketing safety databases for adverse events (AEs) that occur with disproportionate frequency. These methods, known variously as quantitative signal detection, disproportionality analysis, or safety data mining, facilitate the identification of new safety issues or possible harmful effects of a product. In this article, we describe the statistical concepts behind these methods, as well as their practical application to monitoring the safety of pharmaceutical products using spontaneous AE reports. We also provide examples of how these tools can be used to identify novel drug interactions and demographic risk factors for adverse drug reactions. Challenges, controversies, and frontiers for future research are discussed. Clinical Pharmacology & Therapeutics (2007) 82 157–166; doi: 10.1038/sj.clpt.6100258 ; published online 30 May 2007