FDA Modernizes Clinical Trial Process with Real-Time Model and AI Tools

FDA Commissioner Marty Makary announced 'the first ever real-time clinical trial' Tuesday at FDA headquarters, enabling regulators to monitor safety and efficacy data from drug trials in real time using AI.

Objective Facts

FDA Commissioner Marty Makary announced the first-of-its-kind real-time clinical trial initiative on April 28, 2026, with AstraZeneca and Amgen as proof-of-concept participants that could reduce 20-40% of overall clinical trial time. The trials rely on a real-time data platform built by Paradigm Health, which allows clinical trial data to be analyzed for key signals in near real time and shared with trial sponsors and the FDA in days, rather than months. FDA Commissioner Marty Makary stated that 'For 60 years, we've been conducting clinical trials in the same way, where key data signals can take years to reach the FDA. The lag time can delay regulatory decisions unnecessarily and slow down the drug development timeline'. The FDA is also soliciting public input through a request for information on a broader pilot program launching this summer, with responses due May 29. FDA Chief Artificial Intelligence Officer Jeremy Walsh, credited as a driving force behind the pilot, said the idea manifested last summer through a confluence of the right personnel, emerging technologies and leadership's drive to modernize the review process, which had not changed much since the 1960s.

Left-Leaning Perspective

A Nature Medicine analysis on clinical trials for continuously monitored and updated AI systems is forcing the field to confront directly that the FDA announced major steps to implement real-time clinical trials on April 28, 2026. According to Clinical Trial Vanguard, the FDA's April 2026 real-time clinical trial initiative is genuinely ambitious and signals that it wants AI and data science integrated into trial infrastructure at the safety monitoring level—not just as an analysis tool, but as a live operational component. However, the regulatory line between a 'significant' model update and routine maintenance is drawn in pencil, not ink, and sponsors face a structural dilemma: disclose every model retrain and risk IND amendments that slow enrollment, or treat updates as maintenance and risk a data integrity challenge at the NDA or PMA stage. Many AI-enabled tools are entering clinical use without rigorous evaluation or meaningful public scrutiny, motivated by growing concerns over regulatory blind spots especially during periods of deregulation and political pressure, as noted in PMC research examining FDA approval practices. Ensuring data quality, interoperability, and patient privacy will be critical to scaling this approach, particularly as interim data interpretation frameworks must be updated. Further, Fred Ledley, director of the Center for Integration of Science and Industry at Bentley University, noted that the tension between speed and quality of reviews is a concern with the new real-time trial program, as it also is for other efforts like accelerated approvals and adaptive clinical trials with interim analyses. Left-leaning coverage has emphasized that Makary's past efforts have faced fair share of criticism—the generative AI tool Elsa has been accused of hallucinating false information, while the Commissioner's National Priority Voucher program has been hit with concerns about corruption, and his tenure has been marked by extensive layoffs and concerns of political interference expressed by former high-level officials. This context suggests progressive skepticism about whether safety protocols can truly be maintained under Makary's leadership vision for speed.

Right-Leaning Perspective

FDA Commissioner Marty Makary announced 'the first ever real-time clinical trial' Tuesday at FDA headquarters, calling it 'a milestone day for us to challenge the assumption that it takes 10 to 12 years for a new drug to come to market'. Right-leaning and industry commentary celebrates this as regulatory modernization. Bullish on X stated 'Dr. Marty Makary's real-time clinical trial initiative is a historic leap for medicine…This move proves that regulatory processes can finally be as dynamic and innovative as the science they oversee and we have to give credit where credit is due'. Jeremy Walsh, Chief AI Officer, told reporters that 'while there is an opportunity to shave off' as much as 40% of the clinical trial time, 'the agency won't be cutting corners on safety' and 'The goal here is to sort of get to a regulatory decision in a faster timeline, without compromising any safety'. Analysts from Evercore ISI wrote in an April 28 note about the proposed AI pilot that 'This is a logical next step from the FDA rather than a major step-change, and is an example of regulators doing what they should do by responding to a fast-moving technology and beginning to define a workable pathway for its use'. The FDA consolidated 40 separate application intake systems into a single system and systematized reduction of duplication of software licenses across multiple centers, saving at least $120 million annually, money Makary noted would be reinvested in the scientific community and rehiring as many as 3,000 new scientists. Right-leaning perspectives view these actions as eliminating unnecessary regulatory friction. Adoption of real-time trials would help the U.S. boost its competitiveness in the international biopharma arena and help respond to future pandemics, Makary added. Conservative commentary frames this as aligning public health with American innovation interests. Biotech entrepreneur Errik B. Anderson on X praised 'Another example of the great work under @DrMakaryFDA and the current @US_FDA,' noting appreciation for 'dedication to good science, good medicine and better velocity,' while epidemiologist Allison Krug tweeted '@DrMakaryFDA crushing it! This is great news'.

Deep Dive

Early-phase clinical trials are a bottleneck in drug development, often characterized by high uncertainty, limited patient populations, and inefficient decision-making processes, with data typically reported from sites to sponsors, who analyze and subsequently submit data to the FDA, but with improvements in AI and data science, sponsors and trial sites have the opportunity to conduct real-time trials in a way that enhances safety monitoring and radically increases efficiency. The FDA's initiative directly addresses a structural inefficiency that has persisted for decades. FDA Chief AI Officer Jeremy Walsh told reporters that on average 45% of the time between a Phase 1 clinical trial and submission of an application to the FDA is 'dead time' spent on paperwork and other administrative tasks. The core tension centers on whether real-time monitoring's benefits outweigh the regulatory and operational risks. The left's case rests on genuine technical concerns: no current guidance delivers a prospective AI versioning standard for investigational use where every model update requires documentation and statistical impact analysis confirming that pre-specified endpoints remain interpretable under the updated model. This is not a rhetorical objection but a specific technical gap that could allow AI systems to drift in meaning over time. The right's case accepts these risks as manageable within a pilot structure and prioritizes the humanitarian cost of delay—Makary states he has informed patients of a new cancer diagnosis more than a thousand times and every time wondered why 'we, as a modern society' can't make powerful treatments available sooner to those willing to try them. What each perspective gets right: Progressives correctly identify that the FDA lacks formal guidance on how AI updates mid-trial affect data integrity and endpoint interpretation. Conservatives correctly note that the status quo causes documented delays and that pilot programs with pre-specified signal criteria can test the model safely. What they omit: The left downplays the genuine bottleneck costs—patients do wait years for treatments that could have been available sooner. The right underestimates the complexity of embedding continuously learning AI systems into trials without robust governance frameworks and does not adequately address Makary's institutional track record, which includes the Elsa hallucination issues and staff turbulence. The immediate watch points: Will the May 29 comment deadline and summer pilot selection process produce substantive guidance on AI governance, or will the program expand without closing the versioning and model-update gaps? Will the pilot truly test failure modes—what happens if AI signals are misinterpreted—or will success bias dominate? Will academic investigators, not just large pharma, participate equally in future cohorts, ensuring the system doesn't entrench incumbent advantages for well-resourced companies with IT infrastructure?

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FDA Modernizes Clinical Trial Process with Real-Time Model and AI Tools

FDA Commissioner Marty Makary announced 'the first ever real-time clinical trial' Tuesday at FDA headquarters, enabling regulators to monitor safety and efficacy data from drug trials in real time using AI.

Apr 28, 2026· Updated May 1, 2026
What's Going On

FDA Commissioner Marty Makary announced the first-of-its-kind real-time clinical trial initiative on April 28, 2026, with AstraZeneca and Amgen as proof-of-concept participants that could reduce 20-40% of overall clinical trial time. The trials rely on a real-time data platform built by Paradigm Health, which allows clinical trial data to be analyzed for key signals in near real time and shared with trial sponsors and the FDA in days, rather than months. FDA Commissioner Marty Makary stated that 'For 60 years, we've been conducting clinical trials in the same way, where key data signals can take years to reach the FDA. The lag time can delay regulatory decisions unnecessarily and slow down the drug development timeline'. The FDA is also soliciting public input through a request for information on a broader pilot program launching this summer, with responses due May 29. FDA Chief Artificial Intelligence Officer Jeremy Walsh, credited as a driving force behind the pilot, said the idea manifested last summer through a confluence of the right personnel, emerging technologies and leadership's drive to modernize the review process, which had not changed much since the 1960s.

Left says: The tension between speed and quality of reviews is a concern with the new real-time trial program, and the framework required to execute this ambition without destroying the evidentiary foundations of a trial does not yet exist.
Right says: FDA Commissioner Marty Makary called the initiative 'a bold new approach that could fundamentally transform this clinical trial landscape,' noting that 'FDA regulators will view safety signals and clinical endpoints in the cloud in real time as they are occurring,' part of the broader goal of seeing more continuous trials.
✓ Common Ground
Several voices on the left and right acknowledge that the current 60-year-old sequential system where key data signals take years to reach the FDA creates unnecessary lag time that delays regulatory decisions and slows drug development timelines.
Stephanie Morain, Ph.D., a bioethicist at Johns Hopkins University who has sat on institutional review boards, welcomes efforts to cut down on administrative burden, stating 'I will readily accede that there are plenty of ways where, administratively, we could be moving faster'.
Both perspectives recognize that while there is opportunity to reduce clinical trial time, the agency won't be cutting corners on safety and 'The goal here is to sort of get to a regulatory decision in a faster timeline, without compromising any safety', suggesting agreement on the principle even if skeptics doubt execution.
Fred Ledley noted it is good that the FDA is introducing this only as a pilot program and 'It is important to evaluate this concept in practice, not in theory', a position reflecting bipartisan support for measured testing before full rollout.
A number of commentators across the spectrum recognize the RTCT model raises several operational considerations and that continuous data flow may require new infrastructure for data integration, real-time analytics, and secure information exchange, with updated regulatory frameworks needed to define how interim data are interpreted and acted upon.
Objective Deep Dive

Early-phase clinical trials are a bottleneck in drug development, often characterized by high uncertainty, limited patient populations, and inefficient decision-making processes, with data typically reported from sites to sponsors, who analyze and subsequently submit data to the FDA, but with improvements in AI and data science, sponsors and trial sites have the opportunity to conduct real-time trials in a way that enhances safety monitoring and radically increases efficiency. The FDA's initiative directly addresses a structural inefficiency that has persisted for decades. FDA Chief AI Officer Jeremy Walsh told reporters that on average 45% of the time between a Phase 1 clinical trial and submission of an application to the FDA is 'dead time' spent on paperwork and other administrative tasks.

The core tension centers on whether real-time monitoring's benefits outweigh the regulatory and operational risks. The left's case rests on genuine technical concerns: no current guidance delivers a prospective AI versioning standard for investigational use where every model update requires documentation and statistical impact analysis confirming that pre-specified endpoints remain interpretable under the updated model. This is not a rhetorical objection but a specific technical gap that could allow AI systems to drift in meaning over time. The right's case accepts these risks as manageable within a pilot structure and prioritizes the humanitarian cost of delay—Makary states he has informed patients of a new cancer diagnosis more than a thousand times and every time wondered why 'we, as a modern society' can't make powerful treatments available sooner to those willing to try them.

What each perspective gets right: Progressives correctly identify that the FDA lacks formal guidance on how AI updates mid-trial affect data integrity and endpoint interpretation. Conservatives correctly note that the status quo causes documented delays and that pilot programs with pre-specified signal criteria can test the model safely. What they omit: The left downplays the genuine bottleneck costs—patients do wait years for treatments that could have been available sooner. The right underestimates the complexity of embedding continuously learning AI systems into trials without robust governance frameworks and does not adequately address Makary's institutional track record, which includes the Elsa hallucination issues and staff turbulence.

The immediate watch points: Will the May 29 comment deadline and summer pilot selection process produce substantive guidance on AI governance, or will the program expand without closing the versioning and model-update gaps? Will the pilot truly test failure modes—what happens if AI signals are misinterpreted—or will success bias dominate? Will academic investigators, not just large pharma, participate equally in future cohorts, ensuring the system doesn't entrench incumbent advantages for well-resourced companies with IT infrastructure?

◈ Tone Comparison

Left-leaning coverage uses cautious, technical language emphasizing that 'ambition and infrastructure are different things' and flags institutional risks; right-leaning coverage celebrates this as 'a historic leap for medicine' and emphasizes innovation and competitive advantage. Conservative voices trust Makary's leadership; progressive voices note his track record of controversial decisions.