As AI becomes integral to healthcare, ensuring transparency and trust through regulatory compliance is critical. Multi-agent systems, where different AI agents specialize in distinct tasks, are gaining traction for their ability to promote explainability and human-in-the-loop decision-making. By integrating AI systems optimized for different functions, these models can help identify risks, minimize errors, and ensure regulatory standards are met. This panel will explore how multi-agent AI systems can be leveraged for transparency and accountability throughout the drug development pipeline. The session will focus on the regulatory feedback needed for AI in healthcare, such as what "good"looks like in terms of transparency, human oversight, and explainability. Additionally, panelists will highlight the innovative use of AI as a tool for verifying the accuracy of other AI-driven models, fostering trust within the industry.