Identification of structure-activity relationships for adverse effects of pharmaceuticals in humans. Part A: use of FDA post-market reports to create a database of hepatobiliary and urinary tract toxicities.
The Informatics and Computational Safety Analysis Staff at the US FDA's Center for Drug Evaluation and Research has created a database of pharmaceutical adverse effects (AEs) linked to pharmaceutical chemical structures and estimated population exposures. The database is being used to develop quantitative structure-activity relationship (QSAR) models for the prediction of drug-induced liver and renal injury, as well as to identify relationships among AEs. The post-market observations contained in the database were obtained from FDA's Spontaneous Reporting System (SRS) and the Adverse Event Reporting System (AERS) accessed through Elsevier PharmaPendium software. The database contains approximately 3100 unique pharmaceutical compounds and 9685 AE endpoints. To account for variations in AE reports due to different patient populations and exposures for each drug, a proportional reporting ratio (PRR) was used. The PRR was applied to all AEs to identify chemicals that could be scored as positive in the training datasets of QSAR models. Additionally, toxicologically similar AEs were grouped into clusters based upon both biological effects and statistical correlation. This clustering created a weight of evidence paradigm for the identification of compounds most likely to cause human harm based upon findings in multiple related AE endpoints.
Ursem
Carling J
CJ
US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Pharmaceutical Science, Informatics and Computational Safety Analysis Staff (ICSAS), Silver Spring, MD 20993-0002, USA.
Kruhlak
Naomi L
NL
Contrera
Joseph F
JF
MacLaughlin
Philip M
PM
Benz
R Daniel
RD
Matthews
Edwin J
EJ
D016907:Adverse Drug Reaction Reporting Systems; D001660:Biliary Tract Diseases / Q000139:chemically induced*; D056486:Chemical and Drug Induced Liver Injury / Q000209:etiology*; D016000:Cluster Analysis; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions; D023381:Endpoint Determination; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000008:administration & dosage / Q000737:chemistry; D011358:Product Surveillance, Postmarketing; D021281:Quantitative Structure-Activity Relationship; D014481:United States; D014486:United States Food and Drug Administration; D014570:Urologic Diseases / Q000139:chemically induced*
D004364:Pharmaceutical Preparations