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  • Title: Automated support for pharmacovigilance: a proposed system.
    Author: Bright RA, Nelson RC.
    Journal: Pharmacoepidemiol Drug Saf; 2002 Mar; 11(2):121-5. PubMed ID: 11998536.
    Abstract:
    Governments, manufacturers, and other entities are interested in adverse event surveillance of marketed medical products. FDA's Center for Drug Evaluation and Research redesigned the post-marketing adverse reaction surveillance process to use the advantages of new technology. As part of this effort, a 'Pharmacovigilance Working Group' designed a new strategy for the review and analyses of adverse event reports received by FDA. It created requirements which divided signal detection into five tiers: (1) Single 'urgent' reports would be sent to reviewers' workstations nightly for immediate attention. Reviewers would be able to customize definitions of 'urgent' (events that should not wait for aggregate review). (2) Single urgent reports would be placed in a context matrix containing historical counts of similar events to aid in initial interpretation. (3) In this first level of aggregate review, graphical displays would highlight patterns within all the reports, both urgent and non-urgent, and (4) periodic drug-specific tabled-based reports would display the newly received reports across a pre-defined variety of displays. These four tiers would produce passive and criteria-based results which would be presented to safety reviewers' electronic workstations. (5) Active query capabilities (routine, such as age, sex, and year distributions, as well as ad hoc) would be available for exploring alerted issues. The historical database would be migrated into the new format. All historical and new reaction data would be coded with the new MedDRA (Medical Dictionary for Regulatory Activities) scheme. The strategy was to design a full data capture system which effectively exploits current computing advances and technical performance to automate many aspects of initial adverse event review, supporting more efficient and effective clinical assessment of safety signals.
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