ARTIFICIAL INTELLIGENCE-DRIVEN TRANSFORMATION IN REGULATORY AFFAIRS: A COMPARATIVE ASSESSMENT OF EMA AND CDSCO

Artificial intelligence (AI) is poised to transform regulatory sciences by enabling data-driven decision making and automation. This review compares the European Medicines Agency (EMA) and India’s Central Drugs Standard Control Organization (CDSCO) in their readiness and approaches to AI integration. EMA has taken a practical stance, publishing a joint multi-annual AI and big-data workplan (2023–2028) with Heads of Medicines Agencies (HMA), developing AI guidance (e.g. clinical and pharmacovigilance AI reflection paper), launching pilot tools (e.g. Scientific Explorer, DARWIN EU network) and aligning with the new EU AI Act.[1] By contrast, CDSCO’s current processes are largely manual or governed by its digital platforms (e.g. SUGAM licensing portal, NSWS single window).[2] No authorized AI strategy or guidelines have been released by CDSCO[3] (no official guidance found), although the regulator is seeking efficiency gains through AI.[4] Key differences include EMA’s extensive data infrastructure[5] (EU health data space, real-world evidence systems) versus India’s emerging digital health ecosystem (Ayushman Bharat Digital Mission).[6] We identify gaps in CDSCO’s AI readiness (policy, data integration, workforce skills, governance) and propose a phased roadmap with six steps (assessment, infrastructure, pilots, governance, capacity-building, scaling) to guide future alignment. A coordinated framework of data protection impact assessments, algorithm oversight (algorithmovigilance) and cross-agency sandboxes is recommended for both regions.