Your SlideShare is downloading. ×
Data Mining and Signal Detection in Pharmacovigilance
Upcoming SlideShare
Loading in...5

Thanks for flagging this SlideShare!

Oops! An error has occurred.

Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Data Mining and Signal Detection in Pharmacovigilance


Published on

  • Be the first to comment

  • Be the first to like this

No Downloads
Total Views
On Slideshare
From Embeds
Number of Embeds
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

No notes for slide


  • 1. Data Mining and Signal Detection in Pharmacovigilance Dr. Bhaswat S. Chakraborty Sr. Vice President, R&D, Cadila Pharmaceuticals Evidence based medicine – novel entity, new delivery system or equivalent generics alike – needs to be potent, efficacious and safe. However, when it comes to assurance of safety, pre-market clinical trials despite their designs cannot capture all the adverse drug reactions (ADRs) causally related to the experimental drug. For a complete qualitative and quantitative mapping of all ADRs, post- marketing surveillance of safety is legally required. The primary responsibility of such surveillance lies with the sponsor or manufacturer of the drug. However, if patient groups, scientists, physicians and regulatory agencies do not take active interest in this activity, the sponsors alone cannot accomplish it entirely. Currently, the reporting of ADRs is mainly done on a voluntary basis – albeit the legal requirement. The voluntary reports go to the national (usually part of the national regulatory agencies) and international (e.g., WHO Uppsala Monitoring Centre (UMC)) where the individual case report forms, background data and particular organ based data are organized, analyzed and interpreted for the use of medical practitioners and patients. Voluntary reports are also published in medical journals. In recent years, there has been an increased effort to analyze the data bases from the likes of aforementioned sources for potential ADR signals that were not apparent during clinical or epidemiology trials. Such efforts are known as signal detection (SD) in pharmacovigilance. The role of SD and PV do not end by establishing a drug–ADR pair only, prompt regulatory actions need to be taken to appropriately restrict or ban the use of that drug. In the recent past, critical opinions have been aired about the sale of many drugs from some countries that have been banned in other countries. In the developed world, nimesulide has been withdrawn, but unfortunately it still continues to be sold in many developing countries. Another drug (rofecoxib) that has been voluntarily withdrawn recently by the manufacturer is still sold in India. The presentation will examine whether the present premarket approval by the regulatory agencies often allows premature conclusions about safety. It will look at the timeframes of “black-box” warnings in PDR. As the main body of the presentation, different approaches to data mining for SD will be discussed with an analysis of relative merits and demerits. Some important problems related to quantitative SD and their plausible solutions will be discussed. *********