| Summary: | Background: Pharmacovigilance (PV) is the science and activities involved in monitoring and developing the safety profile of all marketed medicines. Adverse drug reactions (ADRs) for medicinal products can be identified through postmarketing studies by methods of signal detection. Traditional, qualitative methods involve clinical review of cases, and coupled with modem, quantitative methods which have evolved as PV has grown, may help surveillance of the large number of medicinal products on the market today. This research aimed to investigate combining traditional and modern methods of signal detection by adding statistical weighting to adverse event telms identified as requiring further monitoring pre-marketing, to improve identification and evaluation of ADRs post -marketing. Methods: Four anti-diabetic drugs currently marketed were chosen to model the concept: gliclazide, pioglitazone, rosiglitazone and vildagllptin. Review of pre-marketing information for safety concerns highlighted two medical concepts: cardiac failure and acute pancreatitis. The Delphi method was adapted to identify and pliolitise terms for these concepts to add statistical weighting to. The weightings were applied to two datasets, both from the UK Yellow Card. Scheme (YCS): a two-year dataset (2005-2007) and a ten-year dataset (2000- 2010).
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