The US is at a critical juncture in biomedical innovation, facing the twin towers of high costs and complexity in research. We’re not alone. China is racing ahead in the development and application of Artificial Intelligence (AI) to drug discovery and development. Beijing is actively supporting AI’s role in healthcare technology development with an aggressive and robust national strategy that includes extensive biodata collection, R&D facilitation, and commercialization of medical AI. Alas, inside-the-Beltway, we’re more-or-less standing still.
Without significant attention to revitalizing our processes and procedures for discovery (Hello NIH!), evaluating (Hello FDA!), and paying for new therapies (Hello CMS!), China will leave us in the dust when comes to developing new therapies. Are you ready for this headline, “Who Lost Healthcare?”
For example, Chinese companies are already at the forefront of integrating AI into various stages of drug development, exemplified by its development of ISM3312, an AI-designed drug targeting COVID-19, which has already entered clinical trials in China. That’s what pandemic preparedness means. Where are we? Who Lost Healthcare?
It’s happening in China and it’s not by accident. China is making significant investments to shift from traditional animal-based preclinical models to advanced AI-driven in silico models and digital twin technologies. This transformation is driven by government initiatives, rapid growth in AI biotech startups, and the need to reduce the ethical, financial, and scientific limitations associated with animal testing. Who Lost Healthcare?
If our public health bureaucrats aren’t paying attention, the private sector certainly is. China's advancements in AI-driven drug development have garnered significant interest from innovative pharmaceutical companies. For instance, AstraZeneca, has entered a $2 billion licensing deal with China's CSPC Pharmaceutical Group to develop a small molecule addressing dyslipidemia, extending their existing collaboration focusing on advanced lung cancer research. Similarly, Merck recently signed a $3.3 billion agreement with China-based LaNova Medicines to develop advanced immuno-therapies targeting PD-1 and VEGF proteins. What’s wrong with this picture? Who Lost Healthcare?
China’s National Medical Products Administration (NMPA) -- the equivalent of our FDA --has been actively reforming its regulatory framework to foster the integration of AI-driven technologies, including virtual models, digital twins, and advanced trial designs. This transformation aligns with China’s broader strategic goals under the “Healthy China 2030” plan and the “New Generation Artificial Intelligence Development Plan.” It is a targeted and thoughtful great leap forward for both healthcare innovation and industrial policy. Matching and then overtaking China in AI-driven healthcare must become a national priority. And it need not be driven by government.
Consider Vial, a California-based start-up whose goal is to significantly reduce clinical trial costs through automation, digitization, and streamlined workflows. Their TrialOS platform structures, digitizes, and automates over 200 discrete trial tasks, cutting both time and expenses. This efficiency is crucial for the U.S. to maintain its competitive edge against China's state-supported, rapidly scaling pharmaceutical infrastructure.
By integrating AI-driven target identification, generative chemistry, and automated preclinical testing, Vial also accelerates the drug development pipeline. Their use of organoid and organ-on-a-chip (OOC) technologies reduces reliance on costly animal models, making preclinical data collection faster, cheaper, and more predictive of human outcomes AI is increasingly being used to mitigate dose-related failures in drug development through advanced applications in pharmacokinetic/pharmacodynamic (PK/PD) modeling, dose-response optimization, individualized dosing, and post-marketing surveillance.
Other companies like Unlearn.AI, Phesi, and ArisGlobal are pushing the boundaries in areas including digital twining, synthetic control arms, and regulatory automation. Another player, Insilico Medicine, reports reductions of up to 70–90% in animal testing during preclinical phases. By eliminating the need for extensive animal studies, in silico models can reduce preclinical R&D costs by up to 40%.
This approach aligns with the strategic need to outpace China in drug development. The ability to launch numerous clinical programs simultaneously could give the U.S. a significant advantage, leveraging scale and speed to dominate globally
The FDA needs update its drug development regulations, and the right place to start is by incorporating AI into its clinical trial protocols. FDA should create an "AI Fast-Track" designation similar to its expedited pathways for AI-driven drug discovery. This would promote advanced technologies, reduce administrative hurdles, and bring therapies to market faster, enhancing U.S. competitiveness and enhancing safety and effectiveness.
By embracing technologies that reduce clinical trial costs and accelerate drug discovery—coupled with regulatory reforms to support AI-driven advancements—the U.S. can not only challenge but potentially surpass China's rapid advances in drug development. The future of global health leadership depends on our ability to integrate these innovations into a cohesive, scalable strategy.
Peter J. Pitts, a former FDA Associate Commissioner, is President of the Center for Medicine in the Public Interest and a Visiting Professor at the University of Paris School of Medicine.
Robert Goldberg, Ph.D., is co-founder and Vice President of Research at the Center for Medicine in the Public Interest
Without significant attention to revitalizing our processes and procedures for discovery (Hello NIH!), evaluating (Hello FDA!), and paying for new therapies (Hello CMS!), China will leave us in the dust when comes to developing new therapies. Are you ready for this headline, “Who Lost Healthcare?”
For example, Chinese companies are already at the forefront of integrating AI into various stages of drug development, exemplified by its development of ISM3312, an AI-designed drug targeting COVID-19, which has already entered clinical trials in China. That’s what pandemic preparedness means. Where are we? Who Lost Healthcare?
It’s happening in China and it’s not by accident. China is making significant investments to shift from traditional animal-based preclinical models to advanced AI-driven in silico models and digital twin technologies. This transformation is driven by government initiatives, rapid growth in AI biotech startups, and the need to reduce the ethical, financial, and scientific limitations associated with animal testing. Who Lost Healthcare?
If our public health bureaucrats aren’t paying attention, the private sector certainly is. China's advancements in AI-driven drug development have garnered significant interest from innovative pharmaceutical companies. For instance, AstraZeneca, has entered a $2 billion licensing deal with China's CSPC Pharmaceutical Group to develop a small molecule addressing dyslipidemia, extending their existing collaboration focusing on advanced lung cancer research. Similarly, Merck recently signed a $3.3 billion agreement with China-based LaNova Medicines to develop advanced immuno-therapies targeting PD-1 and VEGF proteins. What’s wrong with this picture? Who Lost Healthcare?
China’s National Medical Products Administration (NMPA) -- the equivalent of our FDA --has been actively reforming its regulatory framework to foster the integration of AI-driven technologies, including virtual models, digital twins, and advanced trial designs. This transformation aligns with China’s broader strategic goals under the “Healthy China 2030” plan and the “New Generation Artificial Intelligence Development Plan.” It is a targeted and thoughtful great leap forward for both healthcare innovation and industrial policy. Matching and then overtaking China in AI-driven healthcare must become a national priority. And it need not be driven by government.
Consider Vial, a California-based start-up whose goal is to significantly reduce clinical trial costs through automation, digitization, and streamlined workflows. Their TrialOS platform structures, digitizes, and automates over 200 discrete trial tasks, cutting both time and expenses. This efficiency is crucial for the U.S. to maintain its competitive edge against China's state-supported, rapidly scaling pharmaceutical infrastructure.
By integrating AI-driven target identification, generative chemistry, and automated preclinical testing, Vial also accelerates the drug development pipeline. Their use of organoid and organ-on-a-chip (OOC) technologies reduces reliance on costly animal models, making preclinical data collection faster, cheaper, and more predictive of human outcomes AI is increasingly being used to mitigate dose-related failures in drug development through advanced applications in pharmacokinetic/pharmacodynamic (PK/PD) modeling, dose-response optimization, individualized dosing, and post-marketing surveillance.
Other companies like Unlearn.AI, Phesi, and ArisGlobal are pushing the boundaries in areas including digital twining, synthetic control arms, and regulatory automation. Another player, Insilico Medicine, reports reductions of up to 70–90% in animal testing during preclinical phases. By eliminating the need for extensive animal studies, in silico models can reduce preclinical R&D costs by up to 40%.
This approach aligns with the strategic need to outpace China in drug development. The ability to launch numerous clinical programs simultaneously could give the U.S. a significant advantage, leveraging scale and speed to dominate globally
The FDA needs update its drug development regulations, and the right place to start is by incorporating AI into its clinical trial protocols. FDA should create an "AI Fast-Track" designation similar to its expedited pathways for AI-driven drug discovery. This would promote advanced technologies, reduce administrative hurdles, and bring therapies to market faster, enhancing U.S. competitiveness and enhancing safety and effectiveness.
By embracing technologies that reduce clinical trial costs and accelerate drug discovery—coupled with regulatory reforms to support AI-driven advancements—the U.S. can not only challenge but potentially surpass China's rapid advances in drug development. The future of global health leadership depends on our ability to integrate these innovations into a cohesive, scalable strategy.
Peter J. Pitts, a former FDA Associate Commissioner, is President of the Center for Medicine in the Public Interest and a Visiting Professor at the University of Paris School of Medicine.
Robert Goldberg, Ph.D., is co-founder and Vice President of Research at the Center for Medicine in the Public Interest
