Exploring the Role of AI in Pharmacovigilance for Early Detection of Adverse Drug Reactions

DOI: https://doi.org/10.63345/ijrmp.org.v10.i5.3

Manoj Thakur

Independent Researcher

Muzaffarpur, Bihar, India

Abstract

Pharmacovigilance—the process of detecting, assessing, understanding, and preventing adverse effects related to drugs—has long been a critical aspect of public health and clinical safety. In recent years, Artificial Intelligence (AI) has emerged as a promising tool to revolutionize this field by enabling early detection of adverse drug reactions (ADRs) through advanced data analysis and pattern recognition. This study explores the integration of AI methodologies into pharmacovigilance systems, reviewing historical developments up to 2020 and analyzing contemporary applications. Using a combination of literature synthesis and statistical analysis of ADR reporting datasets, the study demonstrates that AI can significantly enhance signal detection, reduce lag time in identifying safety issues, and improve overall patient outcomes. The implications of these findings suggest that incorporating AI into pharmacovigilance protocols may lead to more proactive and responsive healthcare practices. The study also outlines the methodologies used, discusses results in context, and provides insights into the potential and limitations of AI-enhanced pharmacovigilance.

Keywords

Keywords: Pharmacovigilance, Adverse Drug Reactions, Artificial Intelligence, Signal Detection, Healthcare Analytics

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