Amgen, Scientists Say AI Speeds Drug Discovery but Is Not a Shortcut

The article frames AI in drug discovery as a tool to accelerate learning rather than replace human scientific judgment. Charles Lin, executive director of Research at Amgen, notes that medicines entering the clinic today often began their journey 10 to 15 years ago, underscoring the long timelines that motivate the search for faster approaches. The roundtable discussion identifies a structural shift in the industry: drug discovery increasingly depends on connecting insights across biology, chemistry, data science, and automation to understand how molecules behave over time and across complex biological systems.

The body emphasizes that the hardest questions—safety and real-world effectiveness—span multiple stages of research and cannot be solved by technology alone. By highlighting the importance of the full lifecycle of drug discovery (a cycle of designing, testing, and refining molecules), the article suggests that AI's value lies not in isolated computational gains but in enabling teams to learn from each iteration and connect decisions across the research process. Amgen's South San Francisco lab expansion exemplifies this philosophy, physically co-locating the disciplines needed for the DMTA cycle rather than treating them as separate functions.