Use of Screening Algorithms and Computer Systems to Efficiently Signal Higher-Than-Expected Combinations of Drugs and Events in the US FDA’s Spontaneous Reports Database

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Data-Driven Prediction of Drug Effects and Interactions (2012, methodology): “Quantitative signal detection algorithms use these data to flag and prioritize drug-event signals for follow-up analysis via formal pharmacoepidemiological studies and to discover complex relationships that are difficult to identify manually [such as drug-drug interactions (DDIs)] ( 4 , 5 ).”
Quantitative signal detection using spontaneous ADR reporting (2009, methodology): “The EBGM is implemented in both Gamma Poisson Shrinker GPS(14) and Multi-item Gamma Poisson Shrinker (MGPS).(16) In practice the Bayesian measures are similar, particularly when the observed count is more than three,(12) and the PRR is close to the observed/ expected ratio.”
Novel Data Mining Methodologies for Adverse Drug Event Discovery and Analysis (2012, methodology): “Both the FDA and the WHO use a Bayesian version of RRR as a basis for monitoring safety signals in their SRSs. 37,38 Other widely used measures and their mathematical definitions are displayed in Table 2 .”