Schaeffer Center white paper outlines FDA reforms to boost pharmaceutical innovation and expand access 

(Press-News.org) Rapid scientific advances are accelerating the development of medical innovations, from personalized treatments to curative gene therapies and advanced diagnostic tools. But significant policy and regulatory reforms at the Food and Drug Administration are needed to fully harness the game-changing potential of these technologies, according to a new white paper from the USC Schaeffer Center for Health Policy & Economics.

The white paper offers comprehensive recommendations for how FDA can modernize drug development by streamlining clinical trials, providing clearer guidance to drugmakers about newer technologies, and improving agency efficiency amid substantial staff reductions. Taken together, these steps could reduce the considerable time and cost of bringing new drugs to market, pushing down prices and improving patient access while maintaining rigorous safety and effectiveness standards.

“We are entering a transformative era in medical innovation that could improve the lives of millions of Americans. To fully realize this potential, FDA must provide clear, dependable guidance that helps drugmakers navigate the growing complexities around evaluating new technologies,” said Schaeffer Nonresident Senior Scholar Lowell Schiller, the lead author and former acting chief counsel and principal associate commissioner for policy at FDA.

Supporting newer clinical trial methods

Technology has made it easier to generate evidence for new drugs outside of traditional randomized controlled trials, which can be time-consuming, costly and are not always feasible, particularly for rare diseases. Although use of innovative approaches like real-world evidence and external control arms has become more common, they remain difficult to implement, and drugmakers often face uncertainty about whether they will pass muster with FDA.

That uncertainty could discourage drugmakers from pursuing riskier projects or inflate development costs.

The authors recommend that FDA increase early interactions with drug developers who are using innovative trial designs, systematically share insights and best practices, and formalize guidance documents to help developers better identify appropriate use of these methods.

“Before spending hundreds of millions of dollars on developing a new treatment, drugmakers want to know that FDA won’t eventually send them back to square one,” Schiller said. “Proactive guidance on emerging technologies and challenging areas of clinical development will help build certainty, driving investment in innovation.”

Better leveraging data on how drugs perform in real-world settings could also improve FDA’s accelerated approval program, which has provided expedited access to hundreds of treatments for serious diseases based on early evidence of effectiveness. However, required follow-up studies to confirm treatment benefit are notoriously challenging. As part of a broader set of recommended reforms for the accelerated approval program, FDA should make clear how drugmakers can incorporate real-world evidence in these studies.

Investing in AI use and oversight
Strategic expansion of advanced computing technologies like artificial intelligence and machine learning at FDA can make new drug reviews better and faster.

FDA’s recent rollout of a generative AI tool to assist with drug reviews is an important step in this direction, but the agency’s implementation of this and other advanced tools is still in early stages. Going forward, FDA can maximize the potential of such tools by establishing strong principles and guardrails. For instance, FDA should optimize its tools for high-value use cases and require that any “algorithmic-informed” decisions are transparent and ultimately made by human reviewers who understand the limitations and risks of AI systems.

Deployed responsibly, these tools can do more than just summarize documents. Analytical platforms could help agency reviewers more effectively identify data quality issues or conduct sophisticated analyses within the increasingly large data sets that FDA receives, allowing them more time to ensure agency guidance and precedent are applied consistently.

FDA should also clearly define goals and use cases for integrating AI and similar tools into drug reviews, helping drugmakers and the public understand how the technology is being used responsibly.

Focusing on what matters most to patients
Regulators and patient communities have at times clashed over how some treatments are evaluated and approved. This tension is most common with rare diseases, which affect 30 million Americans and often have no FDA-approved treatments.

Better incorporating patient perspective into how trials for drugs and biologics are designed and evaluated could build patient trust and encourage more efficient trials focused on outcomes that matter most to patients. Particularly with rare diseases, this would better account for patients’ willingness to accept less certain benefits and risks in exchange for faster access to new therapies.

While FDA has been more flexible in evaluating rare disease treatments, it should work with Congress to formalize its approach to ensure consistency, including in how the agency accounts for patient preferences. Data on patient preferences should also inform Medicare coverage of new treatments and may be especially helpful for drugs approved through the accelerated pathway.

About this white paper
The white paper’s recommendations are organized into six sections: (1) Modernize Evidence Generation, (2) Advance Innovation for Rare Disease, (3) Enhance Supply Chain Oversight, (4) Strengthen the Accelerated Approval Pathway, (5) Invest in FDA’s Use and Oversight of Artificial Intelligence and Other Advanced Computing Technologies and (6) Advance Drug Competition.

Eunjoo Huisung Pacifici, associate professor at the USC Mann School of Pharmacy and Pharmaceutical Sciences, and Barry Liden, director of public policy at the USC Schaeffer Center, are also co-authors. This white paper was supported by the Schaeffer Center. A complete list of supporters of the Schaeffer Center can be found in our annual report, available here

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