CASE STUDY

How a biopharmaceutical company evaluated social media to monitor off-label drug use


Customer

Global biopharmaceutical company

Goal

Gather intelligence about off-label drug usage by screening patient comments in social media

Challenges

  • Insights about off-label drug usage is difficult to collect for pharmeutical companies which do not have direct contact to patients
  • They need however to monitor off-label use of their drugs in order to comply with regulations
  • Patient records are subject to privacy restrictions and when available they do not allow to reconstruct which medication was prescribed for which condition

Solution

During the initial phase of the project, Cortical.io created a prototype based on Message Intelligence to identify mentions of on- and off-label medication usage in a static set of Reddit posts. Leveraging Cortical.io meaning-based algorithms, the application automatically and accurately filters and classifies Reddit messages and summarizes the results. Cortical.io trained classifiers for each of the example drugs specified by the company using publicly available information.

This solution automatically

  • reviews Reddit posts mentioning medication
  • filter for trade or generic names of medication
  • filter out off-topics and ambiguous posts
  • classify posts by medical conditions
  • identify on- versus off-label usage

Results

  • 2.2 million Reddit post reviewed
  • 92-100% accuracy in classifying on-label versus off-label usage

The Cortical.io Difference

  • Cortical.io Message Intelligence combines human-level accuracy with fast processing and high scalability
  • The solution leverages Semantic Folding to accurately disambiguate posts mentioning multiple medication and filter out off-topic posts
  • The solution is able to accurately process terms it has never seen before
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