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How AI is supercharging drug development
Artificial intelligence is reducing preclinical drug development costs by 70%, but clinical-grade results remain unproven by the FDA.
What: AI models are accelerating the drug discovery process, with projections suggesting a 10% increase in new drug programs over the next three to five years. Despite these gains in the lab, no AI-developed drug has yet secured full FDA approval.
Why it matters: The industry is currently in a 'hype-to-outcome' gap; while AI excels at rapid iteration during the research phase, the rigorous regulatory requirements of clinical trials remain the primary bottleneck for widespread adoption.
Decoder
- Preclinical: The stage of drug development that occurs before a drug is tested in humans, primarily involving laboratory experiments and animal studies.
Original article
AI is cutting preclinical costs and timelines in drug development by up to 70%, driving demand for advanced software and models. This could boost new drug program growth by over 10% in three to five years. However, AI has yet to yield an FDA-approved drug, raising concerns about its impact on patient treatment.
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