Medicine abandons one-size-fits-all as AI predicts individual drug failure
Healthcare shifts from universal protocols to precision prediction of treatment outcomes.
Researchers at London's Institute of Cancer Research and RCSI University of Medicine developed PhenMap, an AI tool that predicts how bowel cancer patients will respond to NHS drugs before treatment begins. The system aims to spare thousands of patients from receiving ineffective medications. The announcement came in April 2026, marking a decisive shift from standard treatment protocols to individualized medical prediction.
This follows the exact trajectory of retail personalization engines. For decades, medicine operated on population averages—if a drug worked for 60% of patients, everyone got it. That assumption has collapsed. Just as Netflix stopped recommending the same movies to everyone and Amazon stopped showing identical product suggestions, healthcare now treats each body as its own dataset. The pattern is identical: collect individual signals, run predictive algorithms, deliver customized outcomes.
When medicine becomes measurement, every patient becomes a walking optimization problem waiting to be solved.
Design health products that assume radical individualization rather than demographic segments. The era of average-based healthcare is ending, making personalized health solutions the competitive baseline.
Source: The Guardian