Harnessing Artificial Intelligence for Enhanced Pharmacovigilance: A Comprehensive Review

Abstract

Pharmacovigilance (PV) plays a crucial role in ensuring drug safety by monitoring and assessing Adverse Drug Reactions (ADRs). However, the traditional methods of PV are often labor-intensive, time-consuming and limited by human capacity for data processing and analysis. Recent advancements in Artificial Intelligence (AI) present new opportunities to enhance PV activities, enabling more efficient and accurate detection, assessment and prevention of ADRs. This comprehensive review explores the integration of AI technologies, such as machine learning, natural language processing and data mining, into PV systems. It examines the potential of AI to automate the collection, analysis and interpretation of vast amounts of data from diverse sources, including electronic health records, social media and scientific literature. Furthermore, the review discusses the challenges and ethical considerations associated with AI implementation in PV, such as data privacy, algorithmic bias and the need for regulatory frameworks. By synthesizing current research and case studies, this review highlights the transformative potential of AI in PV and provides recommendations for future research and practice in this critical field.

Keywords: Pharmacovigilance; Artificial Intelligence; Adverse drug reactions