Abstract

Pharmacoepidemiology and pharmacovigilance (PV) have evolved into critical disciplines ensuring the safety and efficacy of pharmaceutical products throughout their lifecycle. This comprehensive review examines the current landscape of drug safety monitoring, highlighting persistent challenges, emerging technological innovations, and global strategies for enhancing pharmacoepidemiology, PV systems. The integration of artificial intelligence (AI), machine learning, and real-world data analytics is revolutionizing adverse drug reaction detection and signal processing. Despite significant technological advances, challenges such as underreporting, data quality issues, and regulatory harmonization remain. This scoping review develops an integrated conceptual framework—the “Integrated Digital PV Ecosystem”—that maps how AI, big data analytics, natural language processing, and real-world evidence (RWE) interconnect with regulatory frameworks and patient engagement systems. The review critically examines gaps between current AI-based PV models and regulatory acceptance, identifies barriers to integrating patient engagement data with RWE through harmonized digital systems, and articulates the policy and ethical frameworks needed for AI-based drug safety systems.

Key words: Pharmacoepidemiology, Pharmacovigilance, Artificial Intelligence, Drug Safety, Signal Detection, Global Harmonization