Here’s how drug developers can best approach interactions with the agency following last year’s seismic changes to its leadership, workforce and policies.
The FDA is coming off a year of seismic change. Multiple senior officials left the agency in the first year of President Trump’s second term, including Richard Pazdur, Norman Stockbridge and Paul Lee. The rapid exodus included regulatory experts with deep institutional knowledge who understood not just what the guidelines say but also how to apply judgment when the science does not fit neatly inside their boundaries.
Naturally, the industry is concerned about turnover at the FDA. “This constant turmoil is undermining America’s leadership in biotechnology, creating unprecedented regulatory instability and unpredictability,” BIO President and CEO John Crowley said in a recent BioSpace interview.
As a longtime regulatory strategist and employee of the contract research organization Veristat, I’ve followed developments at the FDA closely. Here are some important considerations for working with the agency amongst this unpredictability in 2026.
The Implications of Staffing Turnover
It will take time for the FDA to make up for the loss of seasoned veterans. As of April 2025, the FDA also eliminated 3,500 positions as part of a sweeping plan to cut 10,000 jobs across its parent agency and consolidate operations (it later announced plans to rehire about 300 staffers). New employees are learning how to review new drug applications, but they are not experienced in determining what is acceptable, what is not and what makes sense in specific situations. Therefore, their tendency is to lean heavily on guidelines, which may be already be familiar to drug developers or outdated. Unfortunately, this pattern will continue to affect the nature of the input the FDA gives drug sponsors, as well as review times.
Under these circumstances, it is vital to ask the agency for clarification on its guidance. Alignment matters, especially for smaller companies reluctant to take a risk without FDA agreement. Emerging biotech companies and mid-sized sponsors typically want upfront knowledge that their study design is likely to deliver accurate results.
One point remains unchanged from previous years: FDA input is valuable, especially when it comes to the viability of a protocol to serve as the basis of approval. Sponsors should seek clarification from the FDA to resolve any ambiguities. Clarity is essential.
AI Prognosis in Drug Development
Artificial intelligence (AI) is not new—but also not yet mainstream in the regulatory process, although this appears to be changing. The FDA released “Guiding Principles of Good AI Practice in Drug Development” in January, a result of a collaboration between the agency’s Center for Biologics Evaluation and Research (CBER), Center for Drug Evaluation and Research (CDER) and the European Medicines Agency (EMA). The FDA’s Center for Devices and Radiological Health (CDRH) has also published guidance and is currenlty ahead of the AI curve.
All regulatory guidance on AI emphasizes guarding against bias. For instance, how can sponsors get an unbiased, balanced assessment from an AI tool? Are sponsors asking the right questions and employing the right source documentation to produce a fair, accurate, unbiased answer? It is easy to inadvertently introduce bias, especially with AI.
When using AI to generate text for submission, the FDA suggests sponsors prespecify the research question, understand the context of use for the computerized query, pre-specify the underlying data source and then assess the output for accuracy. Ultimately, the sponsor remains responsible for the submission’s quality and accuracy.
In 2026, AI will play a growing role in the review of marketing applications. Likewise, sponsors will use it to write parts of their applications. Even as the use of AI expands, the technology will still require human oversight. Humans must verify and own the correctness and completeness of the information.
Concerns remain about AI use, especially in critical applications such as generating a summary of efficacy data for approval. When AI is used to analyze trial data, regulators will demand to know how the model was trained and insist on total transparency.
Moving forward, expect more clarity from regulators on how to use AI tools to accelerate clinical trials. At the same time, sponsors, contract research organizations and technology providers will continue to work to build AI into medical writing, protocol development and other functions to save time without removing human oversight.
What Determines Regulatory Success in 2026
Going forward, companies should continue to engage with the FDA early in development. This includes providing well-written and succinct scientific summarization to facilitate agency review.
Appropriate use of AI will aid the preparation of accurate documentation. This is especially important for educating FDA staff on properties of new therapeutic products. Special pathways exist for rare diseases, but success still depends on having the right data package regardless of the means used to reach conclusions and on early FDA engagement.
Success in 2026 will also be predicated on factors beyond sponsors’ control, such as the FDA’s timely communication during the early phases of development. The FDA is still largely operating according to established timelines and remains responsive to most informal requests for clarification. Ongoing regulatory feedback is key to keeping drug development programs on track.
Despite 2025’s turmoil, the FDA is working hard to meet PDUFA goals. In 2026, success will be based on the ability of the agency to complete reviews on time, and it will be incumbent upon sponsors to deliver information needed for approval according to the pace of the review. Continuous collaboration will rule the day.
Success will go to those sponsors who respect the value of FDA agreements and recognize that they must demonstrate—not just promise—that their therapy works.
