Journal of Pathology, Communicable Diseases and Preventive Medicines

Authors: Dr. Riya Kapoor, Mr. Arjun Mehra

ABSTRACT: Artificial Intelligence (AI) has emerged as a transformative tool in pharmacovigilance, enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This paper provides a comprehensive review of AI applications in pharmacovigilance, including machine learning, natural language processing, and predictive analytics. Key advantages of AI integration, such as accelerated signal detection, improved data quality, and real-time monitoring, are discussed. Comparative insights from global regulatory frameworks, including the US FDA, European Medicines Agency (EMA), and India’s Pharmacovigilance Programme (PvPI), are presented. Challenges in AI adoption, including data standardization, model validation, and regulatory compliance, are also addressed. Tables summarizing AI methodologies, their applications, and regulatory perspectives provide practical guidance for stakeholders. Emphasis is placed on the need for ethical frameworks, transparency, and human oversight to ensure the safe and effective implementation of AI in pharmacovigilance.

KEYWORDS: Artificial Intelligence, Pharmacovigilance, Machine Learning, Signal Detection, FDA, EMA, PvPI, Adverse Drug Reactions