This review identifies 81 studies on artificial intelligence for adverse drug events, indicating promising but challenging applications in clinical research.
Key Points
AI is being used to predict and detect adverse drug events during drug development and post-market phases.
The review covers 81 articles, focusing on AI methodologies like machine learning and their applications in clinical research.
Challenges include data heterogeneity and lack of external validation, affecting model adoption in practice.
Despite challenges, AI-based detection can enhance drug safety in both pre- and post-approval phases.