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

The aim was to gather information about off-label use of medicines by screening patient comments on social media. We faced several challenges in doing so: It is difficult for pharmaceutical companies that do not have direct contact with patients to collect information about off-label use of medicines. However, they have to monitor the off-label use of their medicines in order to comply with legal regulations. In addition, patient records are subject to data protection and, if available, it is not possible to reconstruct which drug was prescribed for which condition. Solution: In the initial phase of the project, created a prototype based on SemanticPro Classify & Automate to identify mentions of on- and off-label drugs in a static set of Reddit posts. The application uses's meaning-based algorithms to automatically and accurately filter and classify Reddit posts and summarise the results. This solution automatically screens Reddit posts that mention medicines, filters by trade or generic names of medicines, filters out off-topic and ambiguous posts, classifies posts by medical conditions and identifies on-label and off-label use. As a result, 2.2 million Reddit posts were reviewed and 92-100% accuracy was achieved in classifying on-label and off-label use.