H Wu1, H Fang, S J Stanhope. 1. University of Delaware, Newark, DE 19716, USA. haow@udel.edu
Abstract
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 information 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 identify 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 generative 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 unrecognized drug side effects. The developed system is expected to serve as a complementary 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.
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 information 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 identify 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 generative 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 unrecognized drug side effects. The developed system is expected to serve as a complementary 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.
Authors: Gregory E Powell; Harry A Seifert; Tjark Reblin; Phil J Burstein; James Blowers; J Alan Menius; Jeffery L Painter; Michele Thomas; Carrie E Pierce; Harold W Rodriguez; John S Brownstein; Clark C Freifeld; Heidi G Bell; Nabarun Dasgupta Journal: Drug Saf Date: 2016-05 Impact factor: 5.606
Authors: Carrie E Pierce; Khaled Bouri; Carol Pamer; Scott Proestel; Harold W Rodriguez; Hoa Van Le; Clark C Freifeld; John S Brownstein; Mark Walderhaug; I Ralph Edwards; Nabarun Dasgupta Journal: Drug Saf Date: 2017-04 Impact factor: 5.606