Ethics, Bias, and Governance: Regulatory Perspectives on AI in Drug Development

Abstract

This comparative analysis of AI regulations in key markets provides an overview of the current state of AI regulations in the pharmaceutical industry. The use of AI in drug development is a rapidly evolving field, with regulatory agencies around the world establishing guidelines and regulations to ensure the safe and effective use of AI. The analysis highlights common themes and lessons that can be learned from global regulatory frameworks, including the importance of transparency, data quality, human oversight, and validation. The FDA's framework for AI-related software, the EU's AI regulatory framework, Japan's regulatory sandbox, China's AI-driven healthcare reform, and India's AI-driven healthcare initiatives are discussed as examples of regulatory approaches to AI in drug development. The importance of collaboration, industry-academia partnerships, government support, and public-private partnerships is also emphasized. The analysis concludes that regulatory agencies must stay up-to-date with global developments and best practices to ensure the safe and effective use of AI in drug development.

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