AI Poised to Accelerate Drug Discovery, But Success Depends on Data Quality
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AI could dramatically speed up the decade-long process of designing, finding, and testing new drugs by churning through options faster. This could help avoid dead ends and focus on less lucrative cures.
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Techniques like Cell Painting allow AI to see how cells change with diseases or treatments. This helps spot connections and patterns humans would miss.
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Startups are using AI to fail faster, rank potential treatments, and make predictions without physical tests. This greatly accelerates the preclinical phase.
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There are still unanswered questions around relying on AI, as well as biases in training data and other sources. Success will depend on improving quality and business outcomes.
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AI-informed drugs are now in early stage trials. If successful, it could help disorders that don't currently attract enough funding and attention. The value rests in improving the bottom line.