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AI in drug discovery: from prediction to pipelines

Startups and pharmas integrated generative and predictive models into molecular design, with early clinical candidates.

AI in drug discovery: from prediction to pipelines

After AlphaFold, firms used generative molecule models, learned docking, and multi-objective optimization to propose candidates.

Early clinical-trial successes were celebrated cautiously: translational biology remains the hard filter, not only the model.

The sector illustrates AI for science with clearer business and regulatory (FDA) metrics than general chat.