Signal Detection and their Assessment in Pharmacovigilance
Anoop Kumar1, *, Henna Khan2
Identifiers and Pagination:Year: 2015
First Page: 66
Last Page: 73
Publisher Id: PHARMSCI-2-66
Article History:Received Date: 6/2/2015
Revision Received Date: 11/6/2015
Acceptance Date: 27/10/2015
Electronic publication date: 17/12/2015
Collection year: 2015
open-access license: This is an open access article licensed under the terms of the (https://creativecommons.org/licenses/by/4.0/legalcode), which permits unrestricted, noncommercial use, distribution and reproduction in any medium, provided the work is properly cited.
Signal detection and its assessment is the most important aspect in pharmacovigilance which plays a key role in ensuring that patients receive safe drugs. For detection of adverse drug reactions, clinical trials usually provide limited information as they are conducted under strictly controlled conditions. Some of the adverse drug reactions can be detected only after long term use in larger population and in specific patient groups due to specific concomitant medications or disease. The detection of unknown and unexpected safety signals as early as possible from post marketing data is one of the major challenge of pharmacovigilance. The current method of detecting a signal is predominantly based on spontaneous reporting, which is mainly helpful in detecting type B adverse effects and unusual type A adverse effects. Other sources of signals detection are prescription event monitoring, case control surveillance and follow up studies. Signal assessment is mainly performed by using Upsala Monitoring scale & Naranjo scale of probability to analyze the cause and effect analysis. Signal detection and their assessment is very vital and complex process. Thus, the main objective of this review is to provide a summary of the most common methods of signal detection and their assessment used in pharmacovigilance to confirm the safety of a drug. Recent developments, challenges, & future needs have also been discussed.