Empowering Pharmacovigilance: Unleashing the Potential of Generative AI in Drug Safety Monitoring

Pharmacovigilance plays a crucial role in ensuring drug safety and promoting patient well-being throughout the life cycle of medicinal products. However, this field faces several challenges, including underreporting adverse events, data quality issues, complexity signal detection large datasets. To address these challenges enhance monitoring, there is growing interest harnessing potential generative artificial intelligence (AI) techniques. This article explores applications implications AI pharmacovigilance. It provides an overview popular models their working principles, highlighting ability to analyse databases, medical literature, real-world sources identify drug-drug interactions, signals. Moreover, it emphasizes importance human validation expert oversight interpreting acting on insights generated by algorithms. The integration with traditional pharmacovigilance methods creates synergistic approach, combining computational power expertise. can lead improved detection, efficient case report generation, proactive risk assessment, optimized resource allocation. Additionally, addresses related quality, interpretability, model applications, emphasizing need for standardized protocols collaborative efforts among stakeholders. Overall, vast. By leveraging its capabilities, we facilitate early improve outcomes. ethical considerations, ensure privacy, maintain foster responsible effective implementation practices.