Detecting Signals of Adverse Drug Reactions from Health Consumer Contributed Content in Social Media

Adverse drug reactions are causing a substantial amount of hospital admissions and deaths, which cannot be underestimated. Although a great effort has been put on the pre-marketing review during pharmaceutical product development, it cannot identify all possible adverse drug reactions. Currently, post-marketing surveillance is conducted through centralized volunteering reporting systems. However, the reporting rate is low, which makes it difficult to detect the adverse drug reactions signals in a timely manner. With the advance of Web 2.0 technologies and the popularity of social media, many health consumers are discussing and exchanging health-related information with their peers. Many of this online discussion involve adverse drug reactions. In this work, we propose to mine the associations between drugs and adverse reactions from the user contributed content in social media. We have conducted an experiment using five drugs and five adverse drug reactions. The FDA alerts are used as the gold standard to test the performance of the proposed techniques. The result shows that the proposed technique is promising to detect the adverse drug reactions reported by FDA, such as diarrhea, heart condition, depression, and suicidal thoughts. However, adverse drug reaction such as cancer cannot be detected effectively.