Revolutionizing Drug Safety: The Role of Artificial Intelligence and Machine Learning in Pharmacovigilance

Vani Pathuri

Authors

Vani Pathuri Pharmacovigilance Department, Nexpro Technologies Inc, Hillsborough, New Jersey, United States of America. Author

Keywords:

Pharmacovigilance, Adverse Drug Reactions (ADRs), Artificial Intelligence (AI), Machine Learning (ML), Drug Safety Monitoring, Real-World Data

Abstract

Pharmacovigilance is a crucial process in maintaining drug safety. This article explores the role of artificial intelligence (AI) and machine learning (ML) in advancing pharmacovigilance practices, focusing on their application in adverse drug reaction (ADR) detection and risk management. We examine how AI and ML technologies can streamline real-world data analysis, predict safety signals, and improve decision-making in drug safety monitoring. The paper also discusses the importance of regulatory collaboration, healthcare provider involvement, and patient education in strengthening pharmacovigilance efforts. By integrating these advanced technologies and collaborative frameworks, AI and ML offer significant potential to enhance drug safety, improve patient outcomes, and foster a more efficient pharmacovigilance system.

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