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AI Revolution in Drug Design
This chapter examines the transition from traditional lab work to computational methods in drug design, highlighting the rise of AI and machine learning. It discusses critical advancements in protein structure prediction and small molecule drug design, emphasizing the importance of large datasets and self-supervised learning. The conversation also covers the challenges and potentials of AI, including its applications in understanding biological processes and optimizing drug discovery.