We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often.

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• A compound's AI origin story is not by itself a reason to expect it to do better in the clinic. DLDerek Lowe13 May 2024similar wording
• No AI system today reduces either of the two risks that sink most drugs in the clinic: picking the wrong target, and human toxicity. DLDerek Lowe25 May 2023similar wording
• Better drug candidates do not shorten clinical trials, because a trial's duration is set by operational and regulatory friction rather than by how good the drug is. RTRuxandra Teslo28 Feb 2026similar wording
• Deep learning is not yet ready for the task that would actually add value in drug development: predicting safety and efficacy in humans. ATAlex Telford23 Dec 2023similar wording
• AI's bottleneck was never its algorithms but how little data they were fed, which is why the field needed ImageNet rather than another model. FLFei-Fei Li10 Aug 2026similar wording

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