Register Now: Beyond EDC: Designing a Connected Data Strategy for Predictive Clinical Development
|Articles|June 30, 2015

Mining Twitter Hashtags to Find Unknown Drug Issues

A team of scientists at the University of Vermont has invented a new technique for discovering potentially dangerous drug interactions and unknown side-effects using Twitter hashtags.

 

A team of scientists at the University of Vermont has invented a new technique for discovering potentially dangerous drug interactions and unknown side-effects using Twitter hashtags. 

Previous studies have shown that Twitter can be mined for bad drug interactions, but the Vermont team advances this idea by focusing on the distinctive information contained in hashtags-like “#overprescribed,” “#kidneystoneprobs,” and “#skinswelling”-to find new associations. The overall goal of the project, supported by the National Science Foundation, was to discover is to discover any relationship between two drugs that is not known.

Using their new algorithm, the team has created a website that will allow an investigator to explore the connections between search terms (say "albuterol"), existing scientific studies indexed in PubMed-and Twitter hashtags associated with the terms and studies.

A report on how the algorithm works, and its preliminary discoveries, was published online, June 8, in the Journal of Biomedical Informatics.

 

Read the full release here.


Related to this article

© photon_photo - © photon_photo - stock.adobe.com
Standardized measurement across five oncology centers found that clinical research coordinators rated eSource-enabled workflows positively (Overall Mean Satisfaction 5.79 of 7), with reduced manual entry and electronic data transfer earning strong marks, while perceived reduction in sponsor and monitor queries lagged as the one domain below threshold.
Where the Industry Is Headed as Clinical, Operational, and Real-World Data Connect
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, describes the industry’s trajectory toward a unified intelligence orchestration environment—and explains why the future isn’t one model that knows everything, but a trusted system that brings the right evidence to the right human decision.