Abi Olvera
In 2024, Joseph Coates was preparing for death at age 37. His medical team had informed him that his rare blood disorder—which leads to kidney failure, numb limbs, and an enlarged heart—was untreatable. Then, a doctor whom Coates and his girlfriend had met a year earlier at a rare disease summit saved his life, thanks to an artificial intelligence model that suggested an unconventional drug combination.
The doctor, David Fajgenbaum, and his team at the University of Pennsylvania used a model that sifts through thousands of existing medications to find unexpected treatments for rare diseases, coming up with a combination of chemotherapy, steroids, and immunotherapy for Coates. Drug repurposing using artificial intelligence offers hope to patients who have diseases that affect relatively few patients—and that pharmaceutical companies therefore see as unprofitable research targets.
Stories like Coates’ fuel headlines that make bold claims about artificial intelligence: AI will cure cancer, reduce climate change risks, and unlock the secrets of the brain. Tech companies promise a future shaped by machine-driven discoveries, and machine intelligence can certainly help in some aspects of science.
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