AI in Healthcare

Today's Stories

1. 1

   Community oncologists turn to AI, but not all use predictive models

   Community oncologists are turning to AI, but not all of them use predictive models, according to Managed Healthcare Executive. Their adoption of AI appears uneven, with predictive models not universally embraced, suggesting the tools in use may vary.

   How community oncology practices balance AI adoption with predictive model use remains undecided, and the article provides no further specifics.

2. 2

   Mayo Clinic and Thermo Fisher spin out Precure to target pharma and AI firms with multiomic database

   Mayo Clinic and Thermo Fisher have spun out Precure, a company that will offer a multiomic database to pharmaceutical and AI firms. The new company aims to serve drugmakers and AI companies that need large-scale biological data, which could support drug discovery and AI model development.

   How Precure structures access to the database and whether pharma and AI firms sign on will determine its traction.

3. 3

   Tokyo Science Univ. robot lab targets iPS regenerative medicine

   Tokyo Science University's Robot Future Creation Center, opened in April, is pursuing research where AI plans experiments and the humanoid 'Mahoro' runs them automatically, with iPS cell regenerative medicine a key target. Deputy center director Motonori Kanda warns Japan could end up depending on the US or China for experimental environments without large-scale research bases of its own.

   Whether robot-driven work can stabilize cell quality and lead to lower future treatment costs hinges on whether Japan builds such large-scale research bases. Watch the collaboration between Astellas and Yaskawa's joint venture.

4. 4

   AI device nodoca reads throat images to spot influenza signs

   A team developed an AI medical device called nodoca, which finds signs of influenza virus from images of the throat. The developers say AI gets smarter as it learns from more data, so learning many cases from images could let it detect never-before-seen abnormalities (a view the body presents as an expectation, not a demonstrated result).

   Whether the approach can move from finding signs of a known virus to predicting unknown infectious diseases ahead of time, as the team says it wants to do. The test is whether enough case images can be learned.

5. 5

   Fintech devs push AI into Coder space instances, code fixes

   A software engineer at a large US enterprise fintech company says the firm spent the last 12 months pushing developers to use AI and agentic programs — first in the IDE, then Coder space instances with cloud agents, and now code vulnerability remediation. The push goes beyond developer productivity, raising the question of how to design architectures so sensitive financial data does not unnecessarily leave the environment in regulated industries like fintech and healthcare.

   The concern is that even a little PII slipping into the cloud repeatedly over a long-running integration could add up, so the test is how companies handle PII when data does have to leave.

6. 6

   Twist Bioscience wins Eli Lilly TuneLab deal, stock up 7.1%

   Twist Bioscience agreed to supply antibody characterization data services to Eli Lilly's AI-driven TuneLab drug discovery platform, and its stock rose 7.1%. The agreement ties Twist Bioscience to AI drug discovery, and analysts see a large AI opportunity in its antibody data business.

   The stock's momentum hinges on whether the rally holds, with $155–157 as first support. Leerink raised its price target to $160 from $120.