ARTIFICIAL INTELLIGENCE IN PHARMACY: REGULATORY CHALLENGES AND JURISDICTIONAL

Abstract

Artificial Intelligence (AI) is reshaping pharmacy through its applications in drug discovery, development, clinical trials, pharmacovigilance, personalized medicine, and supply chain optimization. By enabling faster, data-driven insights, AI holds the potential to reduce costs, accelerate innovation, and improve patient outcomes. However, the regulatory landscape governing AI in pharmacy remains fragmented and inconsistent across jurisdictions. This review provides a comprehensive overview of the evolution and applications of AI in pharmacy, examining ethical and legal implications, existing regulatory frameworks, and jurisdictional disparities. It further analyzes case studies from the United States, European Union, United Kingdom, China, and India to highlight successes and shortcomings in regulatory approaches. Key barriers—including rapid technological evolution, lack of standardization, data governance issues, and limited regulatory capacity—are discussed. Finally, policy recommendations emphasize the need for adaptive, globally harmonized frameworks that balance innovation with patient safety, transparency, and equitable access. By addressing these challenges, regulators can ensure that AI fulfills its promise of transforming pharmaceutical care into a more effective, ethical, and patient-centered system.