Towards on-line ADR detection: an innovative data cube-based approach.

The problem of Adverse Drug Reactions (ADRs) detection is a key issue in the pharmacovigilance community. Although many related researches have been proposed in recent years, majority of them were concerned about the accuracy of the detected adverse drug reactions, very few paying attention to the performance issue of how to quickly accomplish the detection process. In this work, we propose the concept of multivalued-dimension contingency cube (MDC-cube) to facilitate multidimensional, fast and online detection of ADRs, especially those caused by drug interactions.

iADRs: towards online adverse drug reaction analysis.

Adverse Drug Reaction (ADR) is one of the most important issues in the assessment of drug safety. In fact, many adverse drug reactions are not discovered during limited pre-marketing clinical trials; instead, they are only observed after long term post-marketing surveillance of drug usage. In light of this, the detection of adverse drug reactions, as early as possible, is an important topic of research for the pharmaceutical industry.