AI in Healthcare

Today's Stories

1. 1

   AI in Hundreds of Clinical Trials: Successes and Gaps

   Applied Clinical Trials Online reports on lessons drawn from hundreds of clinical trials involving AI, covering its successes, gaps, and opportunities. The findings suggest AI has delivered documented results in clinical trials while leaving open gaps that point to where it could be applied next, though the specifics are seen through the outlet's review.

   The takeaway hinges on which gaps the review identifies as most consequential, since that shapes where clinical-trial teams and sponsors focus next.

2. 2

   Twist Bioscience lands Eli Lilly TuneLab deal, stock up 7.02%

   Twist Bioscience signed an agreement to provide antibody characterization data and services to Eli Lilly's AI/ML TuneLab platform, feeding lab data into Lilly's antibody discovery models. The deal gives Twist a visible role in AI-driven drug discovery, a strategic validation that helped push shares up 7.02% and drew analyst attention.

   Whether the AI-driven opportunity translates into revenue remains the test, with Leerink raising its target to $160 and UBS starting coverage at Neutral with a $144 target.

3. 3

   UnitedHealth sued over nH Predict's 90% error rate in care denials

   A proposed class-action filed November 14, 2023 alleges UnitedHealth and subsidiary NaviHealth used nH Predict, an AI tool the complaint says has a 90% error rate, to deny post-acute care to elderly Medicare Advantage patients. Two families say the denials cost them over $220,000 combined. The complaint argues UnitedHealth knew of the tool's error rate and kept using it because most patients would not challenge denials, leaving alleged wrongful coverage cuts uncorrected.

   A federal magistrate judge has ordered UnitedHealth to produce documentation about nH Predict's role, and discovery remains ongoing as of 2026, so the case hinges on what those records show about the tool's link to actual coverage denials.

4. 4

   Takeda's NBA AI boosts new drug uptake about 2.35 times

   Takeda says facilities receiving its NBA (Next Best Action) AI recommendations adopted a new product about 2.35 times more often than others, and sites acting on them about 1.6 times more. Takeda presents NBA as proof that combining its reps, digital channels and AI analysis can lift real commercial results, a core pillar of its go-to-market overhaul.

   The result comes from selected new products, and effects on seasonal vaccines or rare-disease fields with limited past data are still unclear. Watch uptake of Takeda ID, at 58,951 users as of March 2026.

5. 5

   Anthropic opens AI-powered wet lab in San Francisco Bay Area

   Reuters reported that Anthropic PBC opened a wet lab in the San Francisco Bay Area, where robots powered by its Claude large language models will automate certain scientific tasks. The facility suggests Anthropic is widening its life sciences push beyond drug discovery, since a spokesperson said the lab is "not for drug discovery specifically."

   A spokesperson said the Bay Area lab is "not for drug discovery specifically," so its value hinges on whether Claude-driven workflows prove useful across other biology subfields.

6. 6

   Healthcare AI agent moves to Amazon Bedrock AgentCore runtime

   AWS migrated a multi-model healthcare AI agent from Amazon ECS with AWS Fargate to Amazon Bedrock AgentCore runtime, keeping the same healthcare_agentcore.py file and triple-model orchestration. AgentCore runtime handles container lifecycle, scaling, identity, and observability automatically, so teams can focus on agent logic rather than infrastructure, according to AWS.

   The sample is for demonstration, and production medical deployments would use Amazon Bedrock Guardrails for content filtering and grounding validation as a standard control.