React: Drug Safety in Your Pocket

Team: scikit_hammertime
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Jake Beard: jake at minnow dot io
Anjney Midha: anjney at stanford dot edu
Ankit Kumar: ankitk at stanford dot edu
Jay Hack: jhack at stanford dot edu
Ross Lazerowitz: rosslazer at gmail dot com

Bayes Impact Hackathon 2014
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The Problem:

  • 100,000 Americans die each year due to known drug side effect
  • Existing tools for users to search for adverse drug interactions are clunky, database level query interfaces
  • Existing tools are limited to reported drug events - which are severely prone to underreporting

Solution:

  • We use a distributed representation of the AERS ( Federal Drug Adverse Event Reporting System) dataset classified by the RxNorm hierarchy, using neural networks to predict novel interactions for pairs of drugs that do not have a historical interaction record

Results:

  • We achieve 82% initial accuracy on novel unseen drug interactions
  • Next steps are to include RxNorm features such as chemical composition.

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