Machine learning (ML) has the potential to assist with signal detection and supplement traditional pharmacovigilance (PV) surveillance methods

The objectives of this pilot study were to apply a proof-of-concept ML model to detect any potential new safety signals for two of AbbVie’s marketed products and to determine whether the model is capable of detecting safety signals earlier than humans

Our model was able to detect one true safety signal for Drug X six months earlier than humans; model optimization to further improve predictive performance may be needed before implementation

Pharmaceutical companies and health authorities should continue to explore the utilization of artificial intelligence (AI)/ML tools in their PV surveillance methods to aid with the vastly increasing amounts of complex safety data and contribute to the literature