LAS VEGAS — It took 12 doctors at six health systems across four states to diagnose top Trump administration official Amy Gleason’s daughter with a rare immune disease.

But that was before artificial intelligence. As she’s explained over and over while promoting the administration’s efforts to make “health technology great again,” it doesn’t have to be that way today. 

“I truly believe that if she had been diagnosed now instead of in 2010, AI could have picked up what she had way faster than a year and three months it took,” Gleason, the acting administrator of the U.S. DOGE Service and a strategic adviser to the Centers for Medicare and Medicaid Services, told attendees at the Consumer Electronics Show in Las Vegas last week.

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Hope you had a great holiday season. I’m starting off the year in Las Vegas at the Consumer Electronics Show. So far I’ve seen a 3D printer for chocolate and two different brands of fedora-wearing robots; I’ve also learned that Napster is back (and is really into AI music now). If you’re around, let me know!

Also, if you like a lil game as a treat during the day: STAT’s mini crossword is now daily! Check it out here.

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LAS VEGAS — The Food and Drug Administration announced Tuesday that it will ease regulation of digital health products, following through on the Trump administration’s promises to deregulate artificial intelligence and promote its widespread use.

FDA Commissioner Marty Makary indicated that one of the agency’s priorities is fostering an environment that’s good for investors, and that FDA regulation needs to move “at Silicon Valley speed.” He announced the changes during an address to conference attendees at the Consumer Electronics Show.

The agency will soften its approach to the regulation of clinical decision support software, which include AI-enabled products that help doctors navigate diagnoses and treatment options. The agency previously considered products that delivered a single recommendation as FDA-regulated medical devices. Now, those products can enter the market without FDA review as long as they fulfill the agency’s other criteria for escaping regulation. 

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One day, probably in the next year or two, a company will claim it has put the first artificial-intelligence-designed antibody in the clinic. But the industry is divided on what “AI-designed” really means, and how close we are to the technology truly being able to design a medicine.

What exactly does it mean for an antibody to be designed by AI? There are two schools of thought among the antibody and protein AI researchers STAT interviewed. For some, if a computer designs the basic antibody sequence that scientists later tweak to make a clinical candidate, that counts as “AI-designed.” Others say that to be truly AI-designed, an antibody should be ready to go straight into the clinic from the computer, no further lab work needed — a much higher bar to clear. 

In 2025, researchers made it clear that AI can meet the first, easier definition of making an “AI-designed” antibody. But while some startups claim to be making antibodies that are ready to go straight into the clinic, and despite investors shoveling more money into AI-native biotechs at higher valuations compared to traditional biotech startups, even pharma and antibody experts embracing AI find it hard to believe that de novo protein design AI models can meet or beat traditional techniques.

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I saw the Keanu Reeves and Alex Winter Broadway production of “Waiting for Godot” last week, and I’m still so pumped about finally having seen my favorite play. (I got really into Theatre of the Absurd when I was a teenager.)

D.C.-area folks: Flying V at Silver Spring Black Box Theatre is currently putting on “Doctor Moloch,” a play about a humanoid AI doctor who has to learn about empathy. I beg of you, please see this show on my behalf, because I can’t go!

Feedback, tips, questions, “Doctor Moloch” reviews: aiprognosis@statnews.com, or btrang.01 on Signal for confidential tips.

What’s Anthropic doing with life sciences?

Anthropic earlier this week released Claude for Life Sciences — a biology package available to the LLM company’s premium subscribers. 

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BERLIN — The leading professional organization for European oncologists has rolled out its first set of guidance on how its members should use large language models, a type of artificial intelligence, in cancer medicine. 

“The oncology community cannot ignore the potential benefits which AI technology can provide to cancer patients,” the authors of the guidance wrote, while simultaneously acknowledging that there aren’t enough evaluations of the chatbots available to patients or tools available to doctors to address the risks associated with generative AI in medicine.

The guidance’s release — it was published last Saturday in the Annals of Oncology — coincided with the annual meeting for the European Society for Clinical Oncology in Berlin. The American Society of Clinical Oncology has issued its own set of principles for the responsible use of AI in cancer medicine, but has not released recommendations specific to large language models (LLMs).

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