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Can AI Run a Drug Discovery Lab on Its Own?

1What It Would Mean for AI to Run a Lab2The Drug Discovery Pipeline in Plain Terms3Where AI Already Helps Today4Closing the Loop: Self-Driving Labs5Real Examples of AI-Run Lab Systems6Where Autonomy Breaks Down7What Still Needs a Human
The Drug Discovery Pipeline in Plain Terms

From Target to Candidate

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So the chain we named has four links, and the first one is a choice, not an experiment. Target identification and validation means picking a biological molecule or process that looks like it drives the disease, then gathering enough evidence that interfering with it would actually change the disease course.
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The pipeline begins with target identification and validation: choosing a biological molecule or process that seems to drive the disease and gathering evidence that acting on it would change the disease course. It then moves to hit finding, where a very large space of molecules is searched for a few that interact with the target. Lead optimization refines those hits, and preclinical testing plus candidate selection ends with one molecule chosen to carry forward.

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