The Cancer AI Alliance (CAIA) brings together cancer centers and technology companies dedicated to transforming cancer research and discovery
Joined August 2025
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Read our latest blog post on how our Cancer AI lab brings clinicians, model developers, computational scientists, and data experts together to solve challenges and optimize federated workflows.
We are establishing a scalable model for cross-institutional cancer discovery
canceralliance.ai/blog/caia-…
When AI models travel to secure edge nodes at cancer centers, what happens?
How do they help researchers understand how patients will respond to complex treatments?
We take a deeper look at how gradient updates help AI models make smarter predictions:
canceralliance.ai/blog/train…
In our latest blog post, we explain why the Cancer AI Alliance chose OHDSI's Observational Medical Outcomes Partnership (OMOP) as its Common Data Model (CDM).
canceralliance.ai/blog/why-t…
ALT Description of CAIA's criteria for a Common Data Model (CDM)
Do cancer centers have to switch to a different cloud environment to participate in CAIA's federated learning network?
The short answer is: No. Cancer centers can continue to operate on the cloud environments that work best for them.
Learn more:
canceralliance.ai/blog/multi…
ALT Five bullet points that explain the Cancer AI Alliance's multi-cloud federated learning approach which emphasize that cancer centers can operate on the cloud environment that works best for them.
In our latest post, we take you behind the scenes of CAIA's data standardization process, exploring the data mapping and cross-institutional coordination required to make multi-site federated learning work.
canceralliance.ai/blog/caia-…
The scale of CAIA's federated learning approach is important when it comes to studying conditions where data is scarce.
Learn more about how we are enabling research into a rare form of brain cancer at @HopkinsMedicine!
canceralliance.ai/blog/insid…
Check out our new blog post featuring a conversation between two of CAIA's leaders on how AI could be used to ensure that every individual receives consistent, expert, and precise care and how we can move to a more proactive form of cancer care.
canceralliance.ai/blog/insid…
At @googlecloud Next, CAIA's Brian M. Bot discussed how we are leading a transformation in cancer research by supporting a multitude of projects simultaneously with our federated learning platform!
canceralliance.ai/blog/cance…
In our latest blog , we are taking a closer look at one of CAIA's AI innovation projects, featuring a team from @MSKCancerCenter!
The goal is to bring together the entire history of a patient to predict the next phase of their medical experience.
canceralliance.ai/blog/msk-c…
Cancer AI Alliance retweeted
.@CAIAorg announces first wave of pilot projects
cancerletter.com/clinical-ro…
In our latest blog, we highlight the projects that CAIA is piloting across its federated network with researchers from @MSKCancerCenter, @DanaFarber, and @fredhutch!
Learn how our federated learning platform is a working engine for AI discovery!
canceralliance.ai/blog/caia-…
Read about how @fredhutch researchers @DrSimoneDekker and Dr. Stephen Salerno are navigating real-world cancer data analysis using AI in collaboration with @allen_ai !
fredhutch.org/en/news/center…
ALT A photograph of Drs. Simone Dekker and Steve Salerno
Delighted to see CAIA's projects featured in a recent news story by @fredhutch!
Read about the work @CGrassberger is doing to predict high-risk bone metases using federated learning! fredhutch.org/en/news/center…
Cancer AI Alliance retweeted
💻 #ASCOAI: Can federated learning accelerate #precisiononcology?
The Cancer AI Alliance (@CAIAorg) is training #AI models across 4 NCI cancer centers—without sacrificing patient privacy.
📝️ Interview with Eliezer Van Allen, MD (@VanAllenLab)
🔗 ascoai.org/articles/2026/02/…
Cancer AI Alliance retweeted
The reasoning revolution applied to cancer data to build robust models that support finding cures
Read our recap of the 2026 @jpmorgan healthcare conference featuring CAIA leaders from @fredhutch @johnshopkins @nvidia and @MadronaVentures!
canceralliance.ai/blog/beyon…
ALT Dr. Alexis Battle: “Bringing together diverse data clarifies weak signals—like a new variant or a slight imaging aberration you've never seen before. With CAIA, the power of aggregating across centers is incredible, specifically for rare disease.”
Read our recap of the 2026 @jpmorgan healthcare conference featuring CAIA leaders from @fredhutch @johnshopkins @nvidia and @MadronaVentures!
canceralliance.ai/blog/beyon…
ALT Dr. Alexis Battle: “Bringing together diverse data clarifies weak signals—like a new variant or a slight imaging aberration you've never seen before. With CAIA, the power of aggregating across centers is incredible, specifically for rare disease.”
Cancer AI Alliance retweeted
Scaling Data driven cancer research is fundamentally a systems problem not just a modeling one.
This article provides a clear, operational blueprint for doing federated, multi-institutional research right. Highly recommended read.
In our latest blog post, we offer a look at the challenges and barriers that the CAIA team dismantled in our mission to accelerate cancer research and discovery.
Read our 5 operational principles for scaling cancer research:
canceralliance.ai/blog/5-ope…
In our latest blog post, we offer a look at the challenges and barriers that the CAIA team dismantled in our mission to accelerate cancer research and discovery.
Read our 5 operational principles for scaling cancer research:
canceralliance.ai/blog/5-ope…
Cancer AI Alliance retweeted
Wed, Jan 14: @JHUBME Prof @alexisjbattle joins her CAIA colleagues at J.P. Morgan's Healthcare Conference in San Fran for the "Federated AI in Oncology" panel. You can watch the livestream. Noon ET. Register: jpmorgan.metameetings.net/ev…
We are kicking off 2026 with a panel at the @jpmorgan Healthcare Conference in San Francisco!
The panel will highlight CAIA’s progress by demonstrating how its federated learning model securely accelerates research through real-world oncology projects.
