Mining the Web for Pharmacovigilance: the Case Study of Duloxetine and Venlafaxine

TL;DR

This paper explores how internet data sources like social media and search trends can be used for pharmacovigilance, focusing on adverse reactions to Duloxetine and Venlafaxine in Major Depressive Disorder.

Contribution

It demonstrates the use of diverse online data sources for pharmacovigilance and provides a comparative analysis of drug reactions using publicly available data.

Findings

Internet data sources can reveal drug adverse reactions.

Google Trends and Google Correlate are useful for pharmacovigilance.

Comparative analysis of Duloxetine and Venlafaxine reactions.

Abstract

Adverse reactions caused by drugs following their release into the market are among the leading causes of death in many countries. The rapid growth of electronically available health related information, and the ability to process large volumes of them automatically, using natural language processing (NLP) and machine learning algorithms, have opened new opportunities for pharmacovigilance. Survey found that more than 70% of US Internet users consult the Internet when they require medical information. In recent years, research in this area has addressed for Adverse Drug Reaction (ADR) pharmacovigilance using social media, mainly Twitter and medical forums and websites. This paper will show the information which can be collected from a variety of Internet data sources and search engines, mainly Google Trends and Google Correlate. While considering the case study of two popular Major depressive Disorder (MDD) drugs, Duloxetine and Venlafaxine, we will provide a comparative analysis for their reactions using publicly-available alternative data sources.