This podcast episode explores the emerging paradigm of decentralized drug discovery, where artificial intelligence (AI) empowers startups, academic labs, and smaller organizations to drive therapeutic innovation. It highlights how generative AI can streamline the drug design process. At the same time, agentic AI systems can automate experimental workflows, thereby reducing the costs and timelines associated with early-stage research, which has traditionally been dominated by large pharmaceutical firms. The episode also addresses the limitations of decentralization, including the high cost of clinical trials, restricted access to proprietary datasets, and ongoing regulatory complexities. These challenges underscore that AI, while transformative, is not a standalone solution. Instead, the conversation presents a vision where technological advances are coupled with supportive policy, open data initiatives, and collaborative infrastructure to build a more inclusive and efficient drug discovery ecosystem. Produced by Prof. Jake Chen.