Artificial intelligence in pharmacovigilance: toward real-time, explainable, and global drug-safety systems
Abstract
The expanding volume and heterogeneity of post-marketing drug-safety data have exposed the limitations of conventional pharmacovigilance systems. Artificial intelligence (AI) offers scalable solutions for detecting adverse drug reactions by integrating electronic health records, spontaneous reporting systems, and patient-generated data. Recent advances in natural language processing and deep learning enable earlier identification of rare and complex safety signals while reducing reporting delays. Nevertheless, issues related to algorithmic transparency, bias, and regulatory oversight remain critical. This letter highlights emerging applications, current challenges, and future directions for responsible AI integration in pharmacovigilance.
Fields of Study & Subjects
Pharmacovigilance and Adverse Drug Reactions
Data-Driven Disease Surveillance
Artificial Intelligence in Healthcare and Education
Publication details
- Journal / source
- Annals of Medicine and Surgery
- Volume
- 88
- Issue
- 2
- Pages
- 2196–2197
- Publication date
- 19 January 2026
- Language
- EN