On Jan. 21, President Donald Trump announced the launch of the Stargate Project, a $500 billion artificial intelligence infrastructure project designed to revolutionize healthcare.
This groundbreaking privately funded initiative, developed in collaboration with OpenAI, SoftBank, and Oracle, represents one of the most ambitious investments in leveraging AI to advance disease research and treatment development, with a particular focus on “curing cancer.”
Regardless of whether one agrees with its ambitious projections, the Stargate Project has further positioned the United States as a leader in global AI innovation.
However, even with such unprecedented infrastructure investments, the success of the Stargate initiative will ultimately depend on the direct engagement of domain experts across healthcare, particularly in oncology.
The active participation of NCI-designated cancer centers and their leading translational scientists, who bridge bench-to-bedside research, will be essential for measurable success.
Even with such unprecedented infrastructure investments, the success of the Stargate initiative will ultimately depend on the direct engagement of domain experts across healthcare, particularly in oncology.
Without the direct involvement and insights of cancer centers, this initiative would risk becoming yet another IBM Watson Oncology—a promising technology that ultimately fell short of its potential due to misalignment with the practical needs and expertise of healthcare professionals.
Given the uncertainty surrounding the future expansion of NIH/NCI funding to support fundamental cancer research, now is the time to strengthen collaborations between cancer centers, biotech companies, pharma, and private funding streams.
These partnerships have been shown to be critical to elevating translational research to new heights, ensuring that groundbreaking discoveries are effectively applied to improve patient outcomes. I am hopeful that the lessons learned over the years from such collaborative experiments will inform and enhance the impact of large-scale, technology-focused initiatives like Stargate.
The good news is that we already have strong foundations and successful models of collaboration to build upon. By fostering these partnerships and ensuring alignment with the needs of the research and healthcare communities, we can drive innovation forward and create meaningful change in the fight against cancer.
The expanding role of AI in oncology
While Stargate is seen already as a prominent initiative, it is only one of many emerging AI programs nationally that aim to impact cancer care.
Much smaller-scale collaborations between startups and cancer centers are already demonstrating that partnerships are vital to realizing AI’s full potential in oncology. These collaborations underscore that successful real-world applications of AI often require seamless integration with existing clinical and research workflows.
A notable example is Triomics, a growing startup that has already positioned itself as a leader in using generative AI to optimize clinical trial matching and data extraction.
Their platform analyzes unstructured clinical data to identify patients who meet eligibility criteria for oncology trials.
By automating the screening process of all the patient visits against the trial portfolio, the Medical College of Wisconsin Cancer Center has significantly reduced the workload for research staff, ensuring more patients are evaluated for trial participation.
Early results from this collaboration have been impactful, with 72% of trial enrollments since deploying the platform identified by AI autonomously before patient visits.
This approach not only accelerated the trial enrollment process at MCW but also impacted equity and inclusion in their clinical research. They are currently working on extending the work to also identify gaps in the clinical trial portfolio and a few use cases beyond clinical trials.
This collaborative project, coordinated through the Cancer Center Informatics Society’s initiatives program, was recently published in Nature Digital Medicine. AI’s integration into oncology operations at MCW has now shown to extend beyond technological advancements to include patient-centered initiatives.
MCW’s Patient Navigation Program exemplifies a holistic approach to clinical trial enrollment. Navigators guide patients through logistical challenges, ensuring they have the resources to participate fully in trials.
This combination of AI-driven precision and human support is showing the potential benefits of AI-enhanced clinical trial matching.
Another notable example is Tempus AI Inc., a well-established leader in precision medicine that leverages its multimodal data resources and AI capabilities to integrate genomic and imaging data with clinical records.
This integration aims to provide clinicians with actionable insights. Through longstanding collaborations with health systems and partnerships with pharmaceutical companies, Tempus has validated and published much of its work, demonstrating the power of AI-driven tools that continually learn and improve as more data becomes available.
Much smaller-scale collaborations between startups and cancer centers are already demonstrating that partnerships are vital to realizing AI’s full potential in oncology. These collaborations underscore that successful real-world applications of AI often require seamless integration with existing clinical and research workflows.
Tempus strives to enable each patient to benefit from the treatments of those who came before by using AI-enabled tools to refine care.
Their collaborations with cancer centers and the Cancer Center Informatics Society have further underscored the tangible impact of data science in improving patient outcomes and advancing precision oncology.
Tempus AI went public in 2024.
On my desk, I keep a copy of “The AI Revolution in Medicine: GPT-4 and Beyond,” a book co-authored by Zach Kohane, professor and chair of the Department of Biomedical Informatics at Harvard Medical School, explores the remarkable advancements in artificial intelligence.
Published last year, the book charts AI’s progress from the initial limitations of ChatGPT in 2022 to the revolutionary capabilities of GPT-4.
Smarter, more accurate, and equipped with advanced technical expertise, GPT-4 and its successors are poised to transform medicine, with, in my view, a particularly significant and direct impact on precision oncology.
Through various examples, the book highlights AI’s potential to enhance diagnoses, streamline workflows, accelerate research, and empower patients.
By drawing parallels to innovations from companies like Triomics and Tempus, the authors stress that achieving AI’s full potential will require strong collaboration, rigorous oversight, and a clear understanding of its strengths and limitations.
In a January 2025 New Year newsletter, I referred to 2024 as the “Year of Artificial Intelligence,” and 2025 as the year where this momentum continues, with further advancements in AI transforming oncology.
The upcoming Cancer Center Informatics Society Spring Summit will play another pivotal role in shaping the future of AI in oncology.
Chaired by Dr. Suresh Ramalingam, director of the Winship Cancer Institute at Emory University, the summit will focus on the intersection of cancer research and AI.
With a strong emphasis on innovation, the event will explore how AI can drive advancements in oncology, from diagnostics to treatment delivery.
Adding to this momentum, the U.S. Department of Health and Human Services recently unveiled its AI Strategic Plan, which provides a comprehensive framework for integrating AI across healthcare systems.
The plan emphasizes equitable care, data privacy, and operational efficiencies—principles that resonate closely with the AI-centered discussions at last week’s J.P. Morgan Healthcare Conference, where almost half of the presentations at JPM highlighted AI innovations, covering a range of topics from clinical applications to operational improvements.
This growing focus signals a pivotal moment for AI in healthcare, potentially serving as a launching point for broader adoption and innovation.
As a strong advocate for leveraging AI responsibly to improve cancer outcomes, I look forward to contributing to this movement. Achieving the promise of AI—delivering equitable care and optimizing patient outcomes—will require continued collaboration among technologists, clinicians, and policymakers.
The integration of AI into healthcare requires ethical guidelines to ensure equitable and effective patient care. Transparency, accountability, and fairness are critical principles guiding AI applications.
Ethical frameworks must address challenges such as bias in AI models, data privacy, and the potential misuse of AI technologies. Interdisciplinary collaboration among technologists, clinicians, and ethicists is essential to navigate these challenges and responsibly maximize the benefits of AI. Achieving this requires full alignment with cancer centers worldwide.
Indeed, the launch of the Stargate Project marks a pivotal moment in the integration of AI into cancer research and medical oncology.
While upcoming challenges must be addressed, the transformative potential of AI in revolutionizing cancer care is undeniable.
However, this transformation cannot occur in isolation. Key to its success is the engagement of academic medical centers and their cancer centers, as well as partnerships with notable oncology societies such as ASCO, Ci4CC, AACR, IASLC, ASH, SU2C, and PCF, among others.
The launch of the Stargate Program represents a bold step forward in harnessing artificial intelligence to revolutionize healthcare, with a strong focus on curing cancer.
However, the success of this ambitious endeavor will depend on more than just financial investment—it requires the active engagement and expertise of academic medical centers, cancer centers, and the broader oncology community.
As seen in real-world examples like Triomics and Tempus, smaller-scale collaborations have already demonstrated the critical role of partnerships in unlocking AI’s full potential.
Moreover, initiatives like the HHS AI Strategic Plan and forums such as the Cancer Center Informatics Society 2025 Spring Summit further underline the importance of collaboration, ethical guidelines, and alignment with the practical needs of medical oncologists and cancer researchers.
As AI continues to evolve, ethical frameworks addressing bias, data privacy, and accountability must remain at the forefront, to ensure equitable and responsible application in cancer care.
While large-scale projects like Stargate provide the infrastructure for transformative change, the real impact will come from fostering meaningful partnerships between technologists, clinicians, policymakers, and industry leaders. By building on existing models of collaboration, leveraging the insights of domain experts, and aligning efforts across the healthcare ecosystem, we can ensure that AI delivers on its promise to transform oncology—improving outcomes, advancing precision medicine, and ultimately making a difference in the fight against cancer.
