University of Vermont Scientists Using Twitter to Discover New Drug Interactions
The University of Vermont (UVM) recently reported on a new project that mines Twitter data to discover potentially unknown side-effects and dangerous interactions for various drugs.
The computer program, developed by a team of UVM computer scientists, searches millions of tweets for the names of drugs and medicines, and maps connections using hashtags. Findings from those connections can then be tested by researchers. In addition, findings can also be used to generate early public alerts, notifying patients and healthcare providers that a possible issue may exist, before research has begun and before that information appears in medical databases, such as PubMed.
According to the UVM article:
“Our new algorithm is a great way to make discoveries that can be followed-up and tested by experts like clinical researchers and pharmacists,” said Ahmed Abdeen Hamed, a computer scientist at the University of Vermont who led the creation of the new tool. A report on how the algorithm works, and its preliminary discoveries, was published online, June 8, in the Journal of Biomedical Informatics.
“We may not know what the interaction is, but with this approach we can quickly find clear evidence of drugs that are linked together via hashtags,” Hamed said.
…The new approach could also be used to generate public alerts, Hamed said, before a clinical investigation is started or before health care providers have received updates. “It can tell us: we may be seeing a drug/drug interaction here,” Hamed said. “Beware.”
And the research team also aims to help overcome a long-standing problem in medical research: published studies are too often not linked to new scientific findings, because digital libraries “suffer infrequent tagging,” the scientists write, and updating keywords and metadata associated with studies is a laborious manual task, often delayed or incomplete.
“Mining Twitter hashtags can give us a link between emerging scientific evidence and PubMed,” the massive database run by the U.S. National Library of Medicine, Hamed said. Using their new algorithm, the Vermont 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.
…The overall goal of the project, supported by the National Science Foundation, is to “discover any relationship between two drugs that is not known,” said Hamed. But to “ground-truth the hypothesis” — that data-mining in Twitter can find unknown drug interactions — the team wanted to demonstrate that their approach “can produce interactions that are already known,” says Tamer Fandy. He’s a professor of pharmaceutical sciences at the Albany College of Pharmacy’s campus in Vermont, and a co-author on the new study with Ahmed Abdeen Hamedand two other computer scientists, Xingdong Wu and Robert Erickson, professors in UVM’s College of Engineering and Mathematical Sciences.
“It does,” said Hamed. In one example from the new study, a path between aspirin and the allergy medication benadryl, that are known to interact, was detected by the algorithm; in one instance, the two drugs were linked — perhaps not too surprisingly — by the hashtag “#happythanksgiving.”
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