Pharmacovigilance in Social Media Era: a Framework for Social Media Adverse Event Monitoring



Amith Vikram Rangarajan*, HCL Technologies Ltd, chennai, India
Gauri Balani, HCL Technologies Ltd, bangalore, India


Track: Business
Presentation Topic: Health information on the web: Supply and Demand
Presentation Type: Poster presentation
Submission Type: Single Presentation

Building: LKSC Conference Center Stanford
Room: Lower Lobby
Date: 2011-09-18 12:00 PM – 01:00 PM
Last modified: 2011-08-15
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Abstract


Several million people have adopted social media and this user-base is all set to increase rapidly in the future. The patients have started adopting this platform to post and share their disease condition and treatment related experiences. This User-generated media (UGM) on patient care is increasing at the rate of Thousands of posts per day.
There is severe degree of under reporting in the conventional adverse event reporting process especially in hospital settings. It is estimated that around 10% of serious adverse events and 5% of non-serious adverse events get reported to regulatory authorities.This problem can be effectively addressed by implementing adverse event monitoring in social media. The unique feature of drug treatment related data in social media is its high volume and diversity. Social media requires a new kind of pharmacovigilance to well suit its unique attributes.
We propose a social media monitoring framework by synthesizing web crawler and semantic technologies with a unique pharmacovigilance process. We have developed an application that combines webcrawling and semantic functionalities to suit this purpose.
Events that are considered "expected" for a drug are listed in its reference safety information. All "expected" events for the marketed drug of interest will be programmed into the semantic filter of our application. The application shall flag posts related to events that are not in the "expected" list for a particular drug ( "unexpected" events).
Our application can be set to search a list of social media websites for adverse experiences related to a particular marketed drug. It aggregates all such posts and further segregates them in terms of the organ system and its "expectedness" in the final output report.
The output report can be subjected to safety review in a pharmacovigilance unit.The posts in the final output report get processed and followed up depending on their type and entered into safety database accordingly. Our framework allows proactive monitoring of social media. This will lead to more effective, actionable safety signals that can help with ensuring brand success and continued growth in the increasingly stringent global regulatory setting.




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