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MTI Viewpoints

Insights shared by industry relative to healthcare and the advancement of medical technology.

Jim Foote, Founder and Chief Executive Officer

Jim Foote is the CEO and Co-Founder of First Ascent Biomedical. A lifelong technologist and entrepreneur, Jim began his career building data and decision systems before focusing on healthcare after losing his son, Trey, to cancer.

A Personal Mission Rooted in Loss

In 2025, cancer remains the number one killer of children by disease type in America. ⁽¹⁾ For me, that fact is deeply personal. My son, Trey, was one of those one in three children. I have spent my career in technology, working in data systems and decision intelligence. But during my son’s cancer journey, I witnessed something shocking: how few technological tools doctors had to make treatment decisions for something as critical as cancer. That realization became a lifelong mission to change it.

A National Turning Point for Pediatric Cancer

President Trump’s recent executive order to make AI in pediatric cancer a national priority represents a pivotal shift in how we approach childhood oncology. ⁽²⁾ Many pediatric treatment protocols have not changed in decades. Children are not small adults, and their cancers are not smaller versions of adult diseases. Our therapies and trials must be built for children from the start.

Pediatric cancers are biologically different from adult cancers, yet most drugs were developed for adults and later adapted down. Funding and trial sizes for children are smaller, slowing discovery. Add to that the rarity and diversity of childhood tumors, many with dozens of subtypes, and progress has been far slower than any parent or physician would accept.

The Promise and Limits of AI in Oncology

This new federal prioritization can help accelerate much-needed advancements. However, AI is not a silver bullet. It is a critical piece of the puzzle in the broader quest for personalized cancer care. By combining AI’s ability to analyze massive datasets with the biological insights of Functional Precision Medicine and genomics, we now have the tools to move beyond population-based “best guesses.” This means we can deliver individualized therapies faster, more cost-effectively, and at scale. ⁽³⁾

From Incremental Progress to Transformational Change

This is more than a policy change—it is an inflection point that can transform how we diagnose, treat, and ultimately defeat pediatric cancers. For years, pediatric cancer care has improved incrementally through better versions of the “standard of care.” These approaches, designed for the average patient, have saved lives but also revealed their limits. Every child’s cancer is unique, shaped by distinct genetics, tumor biology, and environment. Treating them as though they are all the same leads to inevitable gaps in efficacy, safety, and outcomes.

Lessons from Global Leadership: Australia’s Zero Childhood Program

The Australian Government recognized this reality early. In 2025, it launched a $143 million expansion of its “Zero Childhood Cancer” programs to advance AI-enabled precision medicine for children. ⁽⁴⁾ When a government signals that AI-driven pediatric oncology is a national imperative, it reshapes the ecosystem. Funding accelerates. Regulatory pathways evolve. Partnerships between hospitals, biotech, and device companies become not just possible but essential. Just as SpaceX’s collaboration with industry reimagined space travel, this public–private alignment in healthcare sets the stage for innovation that is faster, safer, more cost-effective, and ultimately more human.

The End of “Try and Hope” Medicine

Cancer biology is extraordinarily complex. Even within a single cancer type, one child’s tumor can behave entirely differently from another’s. Historically, oncologists have been forced to make decisions based on population-level data in a “try and hope” model. AI changes that equation. It can synthesize genomic, transcriptomic, clinical, and functional data to reveal actionable patterns that humans alone might miss.

Algorithms can forecast drug response, resistance, and toxicity, enabling oncologists to make informed choices rather than educated guesses. ⁽⁵⁾ AI-driven platforms can also shorten the time from sample to treatment decision, making personalized care achievable even in time-sensitive pediatric settings.

The Human Impact of AI-Enabled Precision

For families, this evolution means more effective treatments, fewer side effects, and less uncertainty. For clinicians, it means deeper insight, greater confidence, and the ability to make evidence-based decisions faster. For MedTech innovators, this shift opens the door to a new class of tools, devices, diagnostics, and data platforms that integrate seamlessly into clinical workflows and enable continuous learning across institutions.

Functional Precision Medicine: Where AI Becomes Tangible

Functional Precision Medicine (FPM) is where AI’s promise becomes tangible. A useful analogy is musical composition. Genomics is the sheet music, showing which notes should be played. FPM is the performance, revealing how the music sounds when the orchestra plays it. AI serves as the conductor, listening to the performance and analyzing the harmonics in real-time to enhance the piece. The idea of testing a patient’s tumor against multiple drugs to see what works best is not new, but it was historically limited by time and scalability. Advances in robotics, automation, and AI have changed that completely. What once took five hours in a lab can now often be done in minutes. ⁽⁶⁾

From Hope to Evidence: A New Model for Precision Oncology

A new generation of AI-enabled platforms now directly tests a patient’s own cancer cells against hundreds of FDA-approved drugs and combinations in real time. The resulting data is then analyzed by AI to identify the most promising, patient-specific treatment options. This represents a fundamental shift from “what worked for others” to “what works for this patient.” It’s not incremental progress—it’s a reimagining of oncology itself. Much like how SpaceX revolutionized space exploration, this model transforms cancer care from launching treatments and hoping they succeed to testing first, refining, and delivering with evidence-backed precision.

Rewriting the Clinical Research Model

Federal prioritization also creates opportunities for innovation in clinical research, an area where pediatric oncology has historically struggled. Traditional trials often face small patient populations, slow enrollment, and limited data. AI and FPM flip that model. Real-time functional data identifies which subgroups are most likely to benefit, improving trial success rates. AI accelerates patient matching, including for rare cancers, by aligning genomic and functional profiles with trial criteria. Data-sharing ecosystems across MedTech, pharma, and healthcare institutions become more viable, fueling collaborative discovery. These shifts dramatically shorten the time between discovery and deployment and ensure more children have access to cutting-edge therapies, regardless of geography.

A Broader Ripple Effect

When the federal government designates AI in pediatric cancer as a national priority, the ripple effects reach far beyond oncology. Investment momentum grows as public and private funds flow into AI-driven diagnostics, devices, and clinical decision platforms. Regulatory agencies adapt faster review pathways for AI-enabled solutions. Partnerships between pharma, MedTech, and care delivery organizations become the norm, not the exception. The result is a healthcare system that is more predictive, adaptive, and better equipped to address not only pediatric cancers but other complex diseases as well.

A Future Guided by Precision

For decades, we have fought cancer with blunt tools. Now, we can approach it with surgical precision: guided by real-time data, powered by AI, and validated in the lab before a child ever receives a single dose. That is the future this executive order makes possible—a future where treatment is not based on averages, but on evidence generated from each patient’s unique biology.

It is a future where pediatric cancer care becomes faster, more effective, and more equitable—and where no family must endure the uncertainty of “try and hope” medicine.

Federal prioritization is the spark, but technology, innovation, and relentless clinical validation will be the engines that drive the next era of pediatric cancer care. We now have the tools to transform treatment from something we hope will work into something we know will work. Every child deserves nothing less.

References

1. American Cancer Society. Cancer Facts & Figures 2025.
2. The White House. Executive Order on Artificial Intelligence in Pediatric Cancer Research (2025).
3. Topol, E. (2023). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.
4. Australian Government Department of Health. Zero Childhood Cancer Program Expansion (2025).
5. gov. AI-Driven Oncology and Drug Response Forecasting Studies (2024).
6. Global Pediatric Oncology Consortium. Advances in Robotic Functional Testing and Precision Oncology (2024).

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