FDA Announces New Real-Time Clinical Trial Initiative to Expedite Development, but at What Cost?

On Tuesday, April 28, FDA issued a press release announcing two major steps it is taking to advance the implementation of real-time clinical trials (“RTCTs”), including two proof-of-concept RTCTs, both in oncology, and a Request for Information (“RFI”) for a proposed pilot program.

The goal of this initiative is to address the “lag time” of data being reported “from sites to sponsors, who analyze and subsequently submit data to the FDA.”  In contrast, in an RTCT, FDA “can view safety signals and endpoints in real time as a trial progresses.”  Commissioner Makary stated that this could potentially enable FDA to make regulatory decisions without having to wait for a trial to conclude.  To begin with, FDA’s real-time review will be limited to safety and efficacy endpoints that are agreed upon with sponsors in advance.  FDA’s Chief AI Officer Jeremy Walsh, who was also on the announcement call with Commissioner Makary, stated that while this will not immediately replace formal meetings with the FDA, it could ultimately result in moving away from those interactions, as these touchpoints may not be needed.

The RFI is intended to assess how “AI-enabled technologies can improve efficiency, speed, and quality of decision-making in early phase clinical trials.”  The pilot seeks to explore how AI and data science advances can “improve trial efficiency, enhance safety monitoring, facilitate dose selection decisions, and enable more informed early go/no-go decisions.”  Sponsors conducting early phase clinical trials will be recruited into the pilot, which is planned to begin after the proof-of-concept phase later in 2026.

The RFI also described the potential of AI to address challenges of early-phase trials by:

• Improving recruitment
• Optimizing dose escalation
• Enhancing safety monitoring
• Enabling adaptive designs
• Supporting earlier Phase 1 to 2 decisions
• Improving biomarker assessment
• Improving biomarker-based patient selection/stratification
• Validating endpoints

As part of the RFI, FDA seeks input regarding a variety of aspects related to the potential use of AI in FDA regulatory decision-making as well as aspects (eligibility, duration, metrics, etc.) of the pilot program.  We encourage sponsors to review the RFI closely and to submit comments, as this is an important potential opportunity to inform FDA’s decision-making regarding RTCTs and the use of AI more broadly.  Comments on the RFI may be submitted until May 29, 2026.

We applaud FDA for identifying delays in clinical development as a major issue worth addressing.  Regulatory decision-making based on clear signals is an approach that could be tremendously beneficial for drug development.

What Tradeoffs and Risks Might RTCT Introduce to Already Risky Drug Development?

There are also many questions left unanswered by these announcements and what it would mean practically to run an RTCT.  For example, it is not entirely clear how FDA can communicate with the sponsor about safety or efficacy signals while the sponsor remains blinded to results prior to completion.

There would also seemingly be a risk of a Type 1 or 2 error (i.e., a false positive or false negative conclusion) when relying on data in a rolling fashion, including as related to multiplicity control for real-time data collection.  It is also not clear if, or how, FDA’s analyses would be conducted in accordance with a study’s statistical analysis plan (“SAP”). As we see from FDA reviews, Agency staff often conduct their own, post-hoc analyses of data from completed studies using methods they deem appropriate. What would stop FDA reviewers from taking a similar approach at a time when study conduct is still at risk?

Additionally, this appears to place FDA in a role similar to a DSMB, or other such oversight bodies.  When safety signals are identified, it is not clear how DSMB recommendations may intersect with FDA decision making.

Finally, what exactly is the role of the sponsor when sites or CROs are sending data directly to FDA? How does this impact the sponsor’s regulatory obligations, particularly where FDA may be better informed than the sponsor?  Although this initiative is in early stages, we encourage FDA to consider these and other such pragmatic questions to enable effective implementation of such a program.

Is Shorter Time to Data Analysis Really the Issue We Need to Address in Expediting Drug Development?

Given these risks, it is worth considering whether RTCTs are the best means to address the issue of delays in clinical development in all cases.  FDA’s announcement points to the sequence of data collection, cleaning data, and analyzing the data prior to submission as the cause of delays, as well as the formal meeting structure.  However, these steps are crucial to ensuring that the best quality data are prepared, organized, and analyzed.  We have seen many situations where raw data simply did not tell the most accurate story, whether it is because errors were made in data collection or whether there were intercurrent events or other confounders that impacted outcomes, which may not have been initially captured.  Also, clinical trial data is infrequently “black and white” to interpret – especially in rare disease settings where we typically work – and so the time it takes to meet with FDA is not so much a result of process but of having scientific experts evaluate the results.  This is time well spent when needing to contextualize the data and, as FDA typically requests, explain how a sponsor proposes regulatory standards (e.g., substantial evidence of effectiveness) are being met.  RTCTs may get data to FDA faster, but as we say often, you only get one chance to make a first impression.

Beyond RTCTs, there are certainly many opportunities to expedite clinical development.  This includes initiatives taken recently by the Agency, such as encouraging the use of seamless clinical trials, utilization of AI, addressing the default requirement of two (or more) clinical trials, and encouraging the acceptance of Bayesian statistics.  Additional opportunities lie in encouraging the acceptance of earlier endpoints for slowly progressive diseases; considering trial designs beyond the traditional randomized, controlled trial; and regulatory decision-making based on smaller datasets from earlier phase studies, where warranted.

Most strongly, we would urge against downplaying the importance of FDA meetings.  Real-time submission of data cannot replace opportunities for true engagement between FDA, industry, and the experts that join them around the table for robust scientific exchange.  We have assisted clients in countless situations where the submission of data (even if not real-time) led to an adverse FDA response that was subsequently resolved with the opportunity to have a dialogue with FDA staff.  These meetings are not a source of delays in clinical development, but in our experience facilitate a more expedited development process.  In this sense, data cannot replace dialogue.