AI-Driven Drug Discovery: The Role of Regulatory Frameworks, Compliance, and Ethical Governance

Pharmaceutical research is changing as a result of artificial intelligence (AI), which speeds up drug discovery, improves molecular design, and makes it possible to predict treatment effects. But the quick adoption of AI in pharmaceutical sciences presents important concerns regarding ethical governance, compliance systems, and regulatory sufficiency. In order to determine the advantages and disadvantages of regulating AI-driven drug discovery, this study looks at international regulatory frameworks, such as those of the European Medicines Agency (EMA), the Central Drugs Standard Control Organization (CDSCO), and the U.S. Food and Drug Administration (FDA). Ethical problems of justice, openness, and patient safety are examined with compliance issues such data privacy, intellectual property rights, and reproducibility standards. The research presents new developments in adaptive regulatory and governance models using a comparative qualitative methodology. The results indicate that although AI presents previously unheard-of possibilities for pharmaceutical innovation, responsible and equitable adoption requires strong regulatory harmonization, improved compliance procedures, and multi-stakeholder ethical governance. In order to strike a balance between innovation and responsibility, the study's conclusion suggests global harmonization efforts, blockchain-enabled compliance, and flexible regulatory models.