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AI-driven drug discovery treats biological data as a clean signal, yet somatic mutations and biological age variance create a level of noise that current algorithms cannot parse. From the 156-year human lifespan cap to the chemical mixtures in pediatric cohorts, the gap between digital prediction and clinical reality is widening.
