The AI Health Revolution: Why America Must Lead the Next Bioeconomy Frontier
By Eli Rothenberg, PhD, Professor of Biochemistry and Molecular Pharmacology and Director, Single-Molecule Biophonic, and David Fenyo, PhD, Professor of Biochemistry and Molecular Pharmacology, Director, Systems and Computational Biomedicine Training Program, Director, Biomedical Informatics Training Program, NYU Grossman School of Medicine, NYU Langone Health
Consider the Star Trek medical bay, where a handheld scanner records all of a patient’s biometrics, examines their genome, keeps track of their vital signs, and provides a diagnosis and individualized treatment plan in real time. This isn’t merely science fiction, it represents a plausible future, one that’s nearing reality. By marrying real-time data capture with AI-driven interpretation, we could revolutionize healthcare from bedside triage to molecular medicine.
But achieving that future requires a robust data infrastructure capable of processing and integrating diverse research outputs rapidly. It requires real-time feedback cycles between preclinical innovations and clinical implementation. Most importantly, it demands national ambition.
Current State: Incremental Efficiency Gains—but No Transformation
AI is starting to be embedded in today’s healthcare systems, handling radiology triage, automating billing, optimizing supply chains, and supporting EHR documentation. These incremental improvements will help reduce workload and cost, but they don’t fundamentally transform therapeutic development or decision-making.
The ‘big leap’ will be achieved by creating a preclinical-to-clinical intelligence bridge, using AI to rapidly interpret complex datasets (genomics, proteomics, imaging, organoid models) and translate them into actionable clinical phenotypes. Imagine flagging a drug-sensitive mutation in a patient’s tumor biopsy within hours and matching them to targeted therapy or clinical trials hand-in-hand with bench scientists. That’s not a pipe dream; it’s exactly where early adoption of AlphaFold-style tools is taking molecular drug discovery.
The question before us is simple: Will we invest today to lead tomorrow? Or will we watch the future migrate elsewhere and find ourselves increasingly dependent on others, for our health?
A Strategic Risk: Global Competition and U.S. Talent Decline
In H1 2025, 14 licensing deals worth $18.3 billion were signed between U.S. pharma firms and Chinese biotech companies, up from just 2 in H1 2024. In 2024, 31% of big pharma’s licensing deals involved Chinese biotech, up sharply from prior years. Chinese biotech pipelines are now driven by lower costs, fast trials, and aggressive innovation, particularly in modalities such as bispecific antibodies, ADCs, and CAR‑T.
On talent, China produced over 50,000 STEM PhDs in 2022, with estimates pointing toward 77,000 annually by 2025. The U.S., by contrast, remains stagnant at around 34,000 STEM PhDs per year. While the U.S. still leads in high-impact AI talent, volume matters, especially when you need multiple integrated teams in translational science.
Why This Matters Strategically
The stakes are not just theoretical. More than a third of big pharma’s drug pipelines now rely heavily on Chinese innovations, often at a fraction of the cost. A striking example: Summit Therapeutics licensed a Keytruda-comparable lung cancer drug from Chinese biotech Akeso, and the drug outperformed Merck’s blockbuster in a direct trial. Meanwhile, clinical trial output is also tilting. In 2024, China conducted over 7,100 clinical trials, exceeding the U.S.’s total of approximately 6,000. Lower costs, faster timelines, and fewer regulatory barriers make China an increasingly attractive ecosystem for early validation of therapies. In addition, China’s massive workforce enables rapid iteration and deep investment in new platforms. A recent survey indicated that 79% of U.S. biotech companies now engage with Chinese contract manufacturers. In such a landscape, talent retention and innovation capacity are becoming national security priorities.
The Path Forward: Infrastructure, Talent, and Policy
Addressing this growing imbalance requires an urgent shift in strategy. The U.S. must reinvest in its domestic translational infrastructure. This means building AI-ready data centers, labs designed to process and integrate diverse research modalities, from organoid imaging to long-read sequencing, while also enabling real-time feedback loops between experimentation and insight. Alongside infrastructure, our talent pipelines must be revitalized. Federal support for training the next generation of translational AI scientists is crucial, as is establishing public-private programs to keep that talent in the U.S. We must also strengthen biosecurity and domestic biomanufacturing capacity. The FDA’s recent warnings about vulnerabilities in the U.S. active pharmaceutical ingredient supply chain underscore the need for self-sufficiency. Finally, we must commit to a unified, predictable national roadmap for biotech and AI integration, one that sends a clear signal to institutions, startups, and philanthropic investors alike.
Conclusion: A Future We Must Choose
We are at the dawn of a vast and exhilarating frontier, one marked by rapidly evolving innovations and countless possibilities. This is a moment unlike any we have ever experienced, with transformative discoveries poised to redefine medicine, extend lives, and reshape the very fabric of how we understand health and disease. Its magnitude and reach are still beyond our full comprehension, yet its urgency demands our attention.
This extraordinary moment places the United States at a singular junction. We have before us the opportunity to chart a course that unleashes American innovation, secures leadership, and catalyzes global growth at the outset of this new era, a patient-centric healthcare revolution that delivers comprehensive molecular diagnostics, predictive algorithms, and personalized therapeutics. But this future is not guaranteed. To realize it we need more than AI; we need strategic infrastructure, translational talent, and unified policy. The same frontiers that promise discovery also present immense risk, risks that will not tolerate complacency or delay.
There are precedents that should serve as clear warnings. The U.S. once led the world in semiconductor manufacturing, critical to both defense and innovation, but decades of offshoring and underinvestment eroded that lead. We now face a costly and urgent race to rebuild domestic chip production. The same scenario could play out in healthcare innovation if we allow foundational capabilities, data pipelines, preclinical platforms, translational expertise to drift abroad.
History offers another powerful parallel: the launch of Sputnik in 1957 shocked the United States and ignited the space race. It catalyzed massive investments in science, education, and technology that reshaped global leadership. The bioeconomy as a whole and AI in healthcare are both at a comparable turning point. We have the power to influence the direction of medicine if we take bold action. We run the risk of losing our leadership skills if we hesitate.
But this is not a niche policy issue, nor simply a matter of economic competitiveness or global market share, it is one of the most fundamental challenges facing the American national interest.
The U.S. healthcare system, alongside our biomedical research enterprise and pharmaceutical innovation engine, is a foundational national resource. It is a critical piece of national infrastructure, on par with energy, transportation, communication, and defense. For decades, the U.S. has invested in ensuring self-reliance across these core sectors. Healthcare must now be treated with equal, if not greater, strategic priority.
Without a clear roadmap and immediate strategic investment, the U.S. risks becoming reliant on China to fulfill its future healthcare needs. Leaving such a vital system exposed to global dependencies threatens not only economic stability but also the nation’s health security and sovereign resilience.
The question before us is simple: Will we invest today to lead tomorrow? Or will we watch the future migrate elsewhere and find ourselves increasingly dependent on others, for our health?
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