Abstract
Artificial intelligence (AI) has emerged as a transformative force in healthcare, with applications spanning diagnostics to drug development. However, its integration into drug regulation remains nascent, with varying degrees of adoption and implementation across different regulatory bodies worldwide. This review aims to provide a comprehensive overview of the current state of AI in drug regulation, encapsulating AI-related policies, initiatives, and its practical application in regulatory agencies globally. It further discusses the challenges and future prospects of AI in this field. The findings reveal that numerous agencies have launched action plans and initiatives to incorporate AI, aiming to streamline regulatory processes and enhance data-driven regulatory decision-making. Moreover, AI's deployment in safety surveillance, workflow optimization, and regulatory science research is expanding, highlighting its increasing impact on drug regulation. Nonetheless, key challenges persist, such as data quality and reliability, technical limitations, talent shortage and the absence of standards. The review concludes that interdisciplinary collaboration is crucial to harness AI's full potential in drug regulation and overcoming its current limitations. In the future, AI may become a pivotal catalyst in drug regulation, promising a new era of enhanced scrutiny, efficiency, and innovation that will benefit public health on a global scale.