Twitter opinion mining for adverse drug reactions

Abstract

Although rigorous clinical studies are required before a drug is placed on the market, it is impossible to predict all side effects for the approved medication. The United States Food and Drug Administration actively monitors approved drugs to identify adverse events. The FDA Adverse Event Reporting System (FAERS) contains a database of adverse drug events reported by the healthcare providers and consumers. The ubiquitous online social networks, such as Twitter, can provide complementary information about adverse drug events. Short Twitter postings, or tweets, are often used to express an opinion about drugs, as well as solicit and receive feedback from consumers of a drug. Thus, adverse drug events can be discovered by extracting from tweets users' opinions about drugs. Here, we developed a computational pipeline for collecting, processing, and analyzing tweets to find signals about adverse drug reactions, defined as drug side effects caused by a drug at a normal dose during normal use. Manual examination of processed tweets identified several known side effects of four drugs.