Summary
Background: Drugs can treat human diseases through chemical interactions between the ingredients
and intended targets in the human body. However, the ingredients could unexpectedly
interact with off-targets, which may cause adverse drug side effects. Notifying patients
and physicians of potential drug effects is an important step in improving healthcare
quality and delivery.
Objective: With the increasing popularity of Web 2.0 applications, more and more patients start
discussing drug side effects in many online sources. These online discussions form
a valuable source for mining interesting knowledge about side effects. The main goal
of this paper is to investigate the feasibility of exploiting these discussions to
discover unrecognized drug side effects.
Methods: We propose methods that can 1) build a knowledge base for drug side effects by automatically
integrating the in -formation related to drug side effects from different sources;
and 2) monitor online discussions about drugs and discover potential unrecognized
drug side effects.
Results: Experiment results show that the online discussions indeed provide useful information
discovering unrecognized drug side effects. We find that the integrated knowledge
base contains more information than individual online sources. Moreover, both proposed
detection methods can identi -fy the side effects related to the four recently recalled
drugs, and the information from online discussions makes it possible to make the detection
much earlier than official announcements. Finally, the proposed genera -tive modeling
method is shown to be more effective than the discriminative method.
Conclusions: We find that it is possible to monitor online discussions to detect un -recognized
drug side effects. The developed system is expected to serve as a com -plementary
tool for drug companies and FDA to receive feedbacks from the patients, and it has
the potentials to expedite the discovery process of unrecognized drug side effects
and to improve the quality of healthcare.
Keywords
Algorithms - adverse effects - online discussions