This podcast episode explores how artificial intelligence (AI) agents are revolutionizing drug discovery through collaborative partnerships with human scientists. It highlights how advanced AI systems—ranging from AI co-scientists to multi-agent orchestration frameworks—support hypothesis generation, research proposal development, and autonomous task execution across biomedical research. Case studies include tools like AI Co-Scientist, PharmaSwarm, Agentic-Tx, Biomni, and the Virtual Lab, all of which demonstrate how AI-human collaboration can accelerate discovery timelines, reduce costs, and enhance interdisciplinary insight. The discussion also highlights the potential of AI in large-scale data analysis, workflow automation, and dynamic research feedback, while emphasizing the importance of a human-in-the-loop (HITL) approach to ensure the ethical, transparent, and trustworthy deployment of AI. With AI systems increasingly acting as co-pilots in research, this episode presents a compelling vision for how next-generation therapeutics can be developed more efficiently and responsibly. Produced by Prof. Jake Chen.