Fueling the Future of Cancer Research
Our Mission
The Time is Now
Four pioneering cancer centers—Dana-Farber, Fred Hutch, Memorial Sloan Kettering, and Johns Hopkins—have united with leading tech giants to launch the Cancer AI Alliance (CAIA) in October 2024. With the backing of AWS, Deloitte, Microsoft, NVIDIA, Google, and the Allen Institute for AI, CAIA is set to revolutionize cancer research through cutting-edge AI technology.
This groundbreaking collaboration harnesses the latest AI breakthroughs and unparalleled computing power to create an environment ripe for transformative discoveries. By bridging cancer centers, research disciplines, and industries, we are laying the groundwork to unlock AI's full potential in the fight against cancer.
Now, we need your support to make this vision a reality. Join us in this historic endeavor to unlock CAIA's full potential and end the suffering caused by cancer once and for all.
We are seeking $10 million to complete our first phase of work.
Why Now?
More than 17 million people in the United States are living with cancer. While we've made significant strides in treatments—such as a 50% increase in the five-year survival rate for prostate cancer since 1975 and doubled survival rates for leukemia and myeloma—these successes must become the norm, not the exception.
An Era of Possibility
Cancer in the U.S. By the Numbers
2M
People diagnosed in 2024
611,000
Cancer related deaths in 2024
69%
5-year survival rate for all cancer types
Data as the Key
Each patient represents a wealth of data, growing with every scan, treatment, and year of survival. This data is the fuel for developing advanced AI models that could revolutionize cancer treatment. The true power of this information lies in its aggregate form. Millions of patients' data combined can reveal genetic drivers, molecular similarities, and tumor vulnerabilities, fundamentally changing how we treat cancer.
AI's Potential
Imagine a ChatGPT-like tool specifically for cancer, allowing doctors and researchers to ask sophisticated questions and receive insightful answers. Training an AI model on cancer-specific data and decades of research could unlock new possibilities in our approach to cancer treatment.
Overcoming Data Silos
The data needed to unlock AI's potential already exists but is siloed across 57 National Cancer Institutes due to patient privacy, regulatory, and intellectual property concerns. Federated learning, a recent advancement, offers a solution by allowing AI models to train on distributed data while maintaining security and independence.
Empowering Research With Federated Learning
Federated learning enables AI models to access the necessary data without compromising it. CAIA will leverage this revolutionary approach to empower leading-edge research at every participating cancer center. Scientists at these institutions will be empowered to think bigger and be bolder, developing, validating, and deploying new AI models with an unprecedented amount of information.
How Federated Learning Works
Federated learning lets researchers improve AI models using data from multiple institutions without sharing sensitive information. First, a researcher sends their AI model to a central system. This system then sends the model to different cancer centers to analyze their local data. The results are combined and sent back to the central system. This process repeats multiple times to refine the model, and finally, the improved model is returned to the original researcher - all without any raw patient data ever leaving its home institution.
Why Us?
Build to Succeed
CAIA also unites six major technology companies—AWS, AI2, Deloitte, Google, Microsoft, and NVIDIA—who have committed over $60 million in resources and funding to revolutionize cancer treatment.
Fred Hutch, with its extensive experience in managing large-scale public health projects, serves as CAIA's coordinating center. Notable initiatives include:
"This alliance helps solve the key technical challenges that will enable us to securely use both AI and massive computational power to find breakthrough insights and save more lives."
— Thomas J. Lynch Jr., MD,
Fred Hutch president and director and holder of the Raisbeck Endowed Chair
The founding members of CAIA – Dana-Farber, Fred Hutch, Memorial Sloan Kettering, and Johns Hopkins – have ben pivotal in cancer research, contributing to over 10 Nobel Prizes with groundbreaking discoveries like identifying cancer as a genetic disease, developing adoptive cell therapies, and even pioneering bone marrow transplants.
These institutions will enhance each other’s capabilities and attract other leading cancer centers to CAIA, expanding its invaluable stores of data.
161,000
The Women's Health Initiative, gathering health data from 161,000 women, improving prevention, and saving over $37 billion in healthcare costs.
1,300
The SWOG Cancer Research Network, a collective of 1,300 institutions, leading to FDA approval of 14 new cancer drugs.
100+
The COVID-19 Prevention Network, coordinating clinical trials at more than 100 sites, developing two effective vaccines swiftly.
Dozens
The Early Detection Research Network, bringing together dozens of institutions to accelerate early cancer detection
Building Momentum
In January 2025, leaders from CAIA's founding cancer centers and industry partners met to begin laying the groundwork for this first-of-its-kind endeavor.
Coordinated Workstreams
We aim to have our first model ready by end of 2025. To achieve this, we are establishing working groups across the four cancer centers and our industry partners to drive this work forward with a coordinated approach, ensuring alignment in our efforts and outcomes. Our efforts are focused on 4 key areas:
Making Data Accessible
Procuring Technology
Developing and Prioritizing Use Cases
Meeting Legal and Ethical Requirements
Unified Data Standards
Though researchers will never directly "see" or manipulate data from other centers in the CAIA network, the AI models they use for their research will. For CAIA to be successful, and for researchers to work seamlessly, it is critical that the data is uniform and accessible in the same manner throughout the network. We have developed plans to harmonize the data format at member centers and standardize our methods for storing and accessing it
Be Part of the Breakthrough
What We Need Now
We are working to raise $10 million to support the teams building CAIA's infrastructure and release our first models for testing by the end of 2025.
This effort, spanning the four founding cancer centers, aims to prove the federated learning concept and develop a model for onboarding new members. So far, we have raised $60 million for this phase. While CAIA will be fueled by data, it will be led by experts highly sought after in both the public and not-for-profit sectors.
This is the first step in a larger, $1 billion endeavor to expand CAIA's reach, multiply its data resources, and exponentially increase its impact.
Traditional research funding does not typically support high-risk, high-reward efforts like this. This investment requires visionary leaders who understand the opportunity to transform cancer research with AI and the challenges we must overcome.
CAIA's leaders possess the knowledge, leadership, and innovative spirit to unlock AI's potential. You can provide the spark to launch a new era of groundbreaking research.
