• P-ISSN 0973-7200 E-ISSN 2454-8405
  • Follow us

Journal of Pharmaceutical Research

Article

Data Mining Algorithms Used Byregulatory Bodiesof Differentcountries for Signal Detection in Pharmacovigilance
  • VIEWS 632
  • PDF 114

Journal of Pharmaceutical Research

Year: 2015, Volume: 14, Issue: Special Issue, Pages: 91-91

Original Article

Data Mining Algorithms Used Byregulatory Bodiesof Differentcountries for Signal Detection in Pharmacovigilance

Abstract

Aim: To identify the methods used by regulatory bodies of different countries for U. Krishnasignal detection through the assessment of individual case safety reports.Methods: Literature search is conducted using PubMed and manually. The search terms included data mining algorithms and signal detection.Results: There are quantitative and qualitative methods used by regulatory bodies for signal detection. Under the quantitative methods, disproportionality analysis involves the calculation of frequentist metrics. Some of the widely applied frequentist measures include the relative reporting ratio, proportional reporting ratio adopted by the EMA (Eudravigilance), Italian Regulatory Agency (AIFA) and in UK (MHRA) and reporting odds ratio (ROR) adopted by the Netherlands (LAREB) Pharmacovigilance Center. In addition to the frequentist approaches, more complex data mining algorithms based on Bayesian statistics were developed such as the gamma-Poisson shrinker (GPS), the multi-item gamma- Poisson shrinker (MGPS), and empirical Bayesian geometric means (EBGMs).The GPS and MGPs methods are currently used by the FDA. Moreover, Bayesian Confidence Propagation Neural Network (BCPNN) analysis was proposed based on Bayesian logic where the relation between the prior and posterior probability was expressed as the "information component (IC)". Under the qualitative methods, case series, medical event follow ups, periodic safety records are the methods commonly used in signal detection.Conclusions: The choice of a given DMA mostly relies on local habits, expertise and attitude and there is room for improvement in this area; DMA performance may be highly situation dependent, especially with the so called "designated medical events", for which a case-by-case analysis is mandatory. The most appropriate selection of pharmacovigilance toolsneeds to be tailored to each situation, being mindful of the numerous biases and confounders that may influence performance and incremental utility of DMAs.

DON'T MISS OUT!

Subscribe now for latest articles and news.