Bringing a new medicine to patients is one of the most ambitious undertakings in the American economy. Years of research, investment, and scientific risk stand all between discovery and an approved therapy. This spring, the U.S. Food and Drug Administration (FDA) opened two RFIs aimed at helping that work move faster: one on deploying artificial intelligence to sharpen decision-making in the earliest, riskiest stage of clinical research, and a second on making it easier to find new uses for drugs already brought to market. The U.S. Chamber submitted detailed comments on each.
Approach efforts aim to address the challenge from different angles but share a unified destination: a drug development ecosystem that is faster and more efficient without ever compromising patient safety or the empirical evidence standards patients and physicians rely on.
Putting AI to Work in Early-Phase Trials Responsibly
Early-phase clinical research is among the most resource-intensive and uncertain stages of bringing a therapy to market. It requires important dosing and safety decisions to be made with limited information and patient access. FDA’s proposed pilot program would explore how AI-enabled tools can support earlier, more informed decision-making while remaining grounded in the National Institute of Standards and Technology’s (NIST) AI Risk Management Framework.
The U.S. Chamber strongly supports this approach and advocates for the following priorities:
- Build on what already exists. The FDA should leverage current frameworks, guidance, and pilots rather than create duplicative obligations, which gives participants regulatory certainty and conserves Agency resources.
- Focus on the use case, not the technology. Expectations should scale with the risk and consequence of the decision an AI tool supports, concentrating scrutiny where the stakes are highest while letting lower-risk uses proceed efficiently.
- Keep it voluntary. The pilot’s lessons should inform future guidance through notice-and-comment and not harden into de facto standards applied outside the program.
- Protect intellectual property. Participation should never require disclosing source code, model weights, or proprietary training data. Documentation-based transparency, such as model cards and validation summaries, can build trust without exposing trade secrets.
- Keep people accountable. AI should augment, not replace, the scientific and clinical judgment of sponsors, investigators, and reviewers. Accountability for trial conduct and patient safety must remain with identifiable human decision-makers.
Crucially, the efficiency gains AI can deliver should help sponsors meet FDA’s safety and effectiveness standards more efficiently. The U.S. Chamber also urged FDA to design the pilot so that emerging biotechs and smaller sponsors can meaningfully participate.
Unlocking the Potential of Existing Drugs
Some of the most promising treatments may already be sitting on pharmacy shelves. Drug repurposing holds real promise for conditions with high unmet need, from metabolic and neurodegenerative diseases to rare conditions and substance use disorders—often at lower cost and in lower time investment.
Yes, but: Even when a medicine is already on the market, establishing a new use requires meaningful clinical research, making it important that the regulatory framework appropriately supports those investments. The Chamber identified the structural fixes needed to make repurposing research worth pursuing:
- Strong, well-calibrated IP protections, including a new pediatric-style exclusivity mechanism for sponsors who run qualifying trials to establish a new indication, modeled on the proven success of pediatric exclusivity under the Best Pharmaceuticals for Children Act.
- Regulatory pathway clarity, including clearer guidance on evidentiary standards, expanded pre-submission engagement, and better use of the 505(b)(2) pathway, so sponsors aren’t deterred by uncertainty about the road to approval.
- Flexible trial designs, adaptive trials, master protocols, and real-world evidence should be applied aggressively where they can generate robust evidence more efficiently.
- Interagency coordination among FDA, NIH, CMS, and VA to align development, approval, and coverage while keeping FDA’s approval decisions grounded solely in safety and substantial evidence of effectiveness, with no role for pricing or market-based factors.
One Goal: Innovation Patients Can Trust
These two initiatives reflect the common conviction the U.S. Chamber brought to both responses: a development system can be made dramatically more efficient while keeping the standards that earn public trust fully intact.
For Americans to benefit from these advances, whether AI-driven or repurposing-driven, they have to be able to trust them.
That means protecting the intellectual property that fuels private investment, keeping people accountable for the decisions that matter, and never trading away the evidence standards that protect patients.
About the author
Erin Delaney
Erin Delaney serves as Senior Director, Health Policy at the U.S. Chamber of Commerce.
