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Mohana Ravindranath is a freelance health, science, and tech journalist and a 2025 Association for Health Care Journalists fellow. She was previously a Bay Area health tech correspondent for STAT.

Two decades ago, futurist Ray Kurzweil laid out a bold vision for next-generation medicine in his book “The Singularity Is Near.” Technology, he predicted, could one day help doctors eradicate disease by anticipating and responding to it in real time. 

Personalized health predictions have been an ambitious goal for health systems, insurers, drugmakers, and doctors for years: Virtual models, or “digital twins” that forecast whether individual patients will respond to drugs or surgery, or estimate when someone’s most likely to need a knee replacement. The appeal of the concept is driven by the promise of reduced medical costs, automated clinical trials, and fewer sick patients in beds. 

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Advances in artificial intelligence and the availability of new data on genomics, patient outcomes, and drug performance have pushed the idea of “digital twins” closer to reality than ever before. Today, some early-adopter health systems and enterprising tech companies are putting parts of the idea into practice. 

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