In April, the FDA debuted a real-time clinical trial model that will allow the agency to monitor safety signals as the trial is being conducted. The first trials were launched in partnership with Houston-based University of Texas MD Anderson Cancer Center, Philadelphia-based University of Pennsylvania, AstraZeneca, Amgen and Paradigm Health.
The announcement comes at a time when clinical trials have become a standard component of oncology care.
Becker’s spoke to 16 oncology leaders about their reactions to the real-time trial news and the potential implication the model may have for oncology care delivery.
Editor’s note: Responses have been lightly edited for clarity and length.
Question: What is the single biggest implication of the FDA’s real-time clinical trial model for oncology care delivery?
Michael Cecchini, MD. Co-Director of the Colorectal Program in the Center for Gastrointestinal Cancers at Smilow Cancer Hospital and Director of the GI Clinical Research Team at the Yale Center for GI Cancers (New Haven, Conn.): The biggest implication of the FDA real-time clinical model is that it changes oversight from retrospective to prospective safety and efficacy measurements. This allows for better risk and benefit assessments for a patient on a clinical trial and also should speed up clinical development.
Christopher Chen, MD. Assistant Professor in the Division of Oncology in the Department of Medicine at Stanford (Calif.) University: Any regulatory reform that expedites review of promising therapeutics is welcome. I look forward to learning more about this initiative and its results.
John Cole, MD. Medical Oncologist at Ochsner MD Anderson Cancer Center (New Orleans): This initiative has the potential to improve the efficiency of clinical trial safety monitoring. While it may not directly address all challenges facing clinical trials in the U.S., including cost and regulatory factors that can delay start up and efficiency, it is a meaningful step forward in improving key aspects of trial operations.
Don Dizon, MD. Chief of Hematology and Oncology at Tufts Medicine (Burlington, Mass.): The process of drug development continues to be a time inefficient endeavor with much human capital required at the site level — from startup to training, to identification of eligible patients, to the collection and transfer of data, and reporting of serious toxicities — to the sponsor.
Often, even with the data you get from your own site, it’s hard to decipher the experience at sites across the study: Are they seeing responses to data? Is their experience mirroring yours? What to make of toxicities? These are all questions that could potentially be helped by allowing AI and newer technologies to improve the efficiencies of recruitment and reporting.
Imagine if a safety signal was seen early and with AI it could be determined with high likelihood it would be a major issue. This alone could help prevent others from the risks associated with an investigational drug and reduce the amount of capital — human and financial — that is expended over a treatment that is not likely to be ultimately approved.
Linda Duska, MD. Gynecologic Oncologist at UVA Health and Associate Dean for Clinical Research at the UVA School of Medicine (Charlottesville, Va.): The FDA’s real-time clinical trial model has the potential to transform the traditional clinical research paradigm by compressing the feedback loop between patient outcomes and regulatory decisions, thereby potentially accelerating drug development and turning oncology delivery systems into continuously learning clinical-research environments. In other words, it is a way of learning from a clinical trial during the study instead of having to wait until the end. Potentially adapting the trial during this learning process to potentially make the trial both more safe and more efficient.
W. Jeffery Edenfield, MD. Executive Director of Medical Oncology at Prisma Health (Greenville, S.C.): This is potentially a boon for the speed of drug development and for faster completion of clinical trials. I am forever optimistic about such ideas although similar attempts in the past have not been uniformly successful. Given that most cancer care is delivered in community settings, there is more resource constraint than at the academic institutions that will be participating in this pilot. Ideally, we would find ways to educate about the value of clinical trials more broadly and enhance enrollment through greater participation.
Karyn Goodman, MD. Professor and Vice Chair of Clinical Research in the Department of Radiation Oncology at Icahn School of Medicine at Mount Sinai and Associate Director of Clinical Research at The Tisch Cancer Institute (New York City): The goal of the FDA’s real-time clinical trial initiative is to accelerate drug development. Under the traditional clinical trial model, the FDA typically reviews safety and efficacy data only after a study has been completed, a process that can take several years. Subsequent trials are often not initiated until the results of earlier studies have been fully analyzed, contributing to the lengthy drug development timeline.
Under the new approach, the FDA can review safety signals and study endpoints as data become available during the course of a trial. This model may also leverage AI to facilitate data collection, analysis and submission for ongoing FDA review. While this represents a significant shift in the regulatory process with the potential to shorten development timelines, it will remain important to ensure that delayed toxicities, long-term outcomes and other effects that may not be apparent during real-time assessments are not overlooked.
Miguel Gonzalez-Velez, MD. Drug Discovery Phase 1 Program-Thoracic Oncologist at the John Theurer Cancer Center at Hackensack (N.J.) Meridian Health: The real-time clinical trial model can improve the current care delivery. Phase 1 oncology usually relies on retrospective, cohort-bound safety reviews: Signals get flagged at Data and Safety Monitoring Board intervals, usually after the adverse event that should have triggered a dose modification. Real-time FDA review compresses that latency from weeks to days, which matters most precisely where we are exposing patients to first-in-human agents. It also enables genuine adaptive dose-finding by decreasing the intra-trial regulatory friction.
The complex part is the infrastructure. Real-time review only works if sites can submit clean adverse event and pharmacokinetics data in almost real time. Most community and even midsized academic centers do not operate that way today. So the secondary implication, and the one health systems should be planning for now, is bifurcation: The trials that benefit from this real-time model will concentrate at sites with the data capture and research coordinator capacity to keep up. If we don’t invest in lifting that floor, real-time trials risk deepening the geographic and demographic disparities in Phase 1 access that already exist.
Jennifer Litton, MD. Chief Clinical Research Officer at The University of Texas MD Anderson Cancer Center (Houston): Every day, more patients are being cured and living longer with cancer, but there are many who still need new and better treatments. We are experiencing an explosion of scientific breakthroughs, yet we are challenged with rapidly advancing those breakthroughs through scientifically rigorous clinical trials. We are hopeful that real-time clinical trials will help to speed the process and decrease the dead time in which there is no activity happening on studies for promising agents. There is a significant need to advance our processes for drug development in order to more rapidly gather the information needed to evaluate a new therapy and this is the first major step in that direction.
Elyse MacDonald, PharmD. Director of Pharmacy Services at Stanford Health Care (Palo Alto, Calif.): I think about this answer from two perspectives. From a patient perspective, I think the biggest implication of the real-time clinical trial model is faster drug development. Time is key for oncology patients, so if new, groundbreaking medications can be approved faster with the same focus on ensuring safety and efficacy, then that will be a big win for the real-time clinical trial approach.
From a clinical trial site perspective, I think the biggest implication is operational efficiency. There are some antiquated research practices that are manual and not efficient. In theory, I think the real-time clinical trial approach can help reduce the manual processes, thus building operational efficiencies for research site staff.
Laurie Nightengale, MD. Director of Oncology And Hematology Research at Mercy (Chesterfield, Mo.): The FDA’s Real-Time Clinical Trial model is an important step forward in how we develop and deliver cancer treatments. The biggest impact is speed. By reviewing data as it’s collected, rather than waiting until the end of a trial, the FDA can make decisions sooner. That can shorten the timeline — traditionally 10 to 12 years — to bring new therapies to patients, which matters in diseases where time is limited.
It also allows trials to be more flexible. Instead of sticking to a fixed design, studies can adjust based on what’s being learned along the way, like refining which patients are most likely to benefit or modifying treatment approaches. This helps make trials more relevant to real-world patient needs.
Patient safety is another key benefit. With ongoing data review, concerns can be identified earlier, allowing for quicker response if issues arise. This means faster intervention, reducing risk to patients and ensuring patient trust and trial integrity.
Finally, this approach helps bring clinical care and research closer together. Health systems and clinicians can play a more active role in developing new treatments while continuing to care for patients. This model has the potential to move promising therapies forward more quickly, while still keeping patient safety and scientific standards at the center.
Matt Sherer. Director of the Oncology Service Line at UMC Health System (Lubbock, Texas): From where I sit, the big-picture goal may be faster drug development, but what matters most at the site level is eliminating the delays that slow care and research. At the UMC TLC2 Foundation Cancer Center, trials can get bogged down by manual data entry, query backlogs and slow sponsor review. A real-time data-sharing approach helps us spend less time cleaning up data after the fact and more time managing patient care as things happen.
For our partnership with Texas Tech University Health Sciences Center, that kind of real-time visibility can make a real difference in how we deliver trial-related care in West Texas:
- Better coordination: Our teams can see safety and efficacy signals sooner, which helps us respond faster, manage toxicities earlier and make more timely treatment decisions.
- Less administrative burden: When data flows more efficiently, our research staff can spend less time on manual entry and more time helping identify, enroll and support patients.
At the end of the day, this is about making research a more natural part of everyday cancer care.
Ashwin Somasundaram, MD. GI Cancers Clinical Trial Lead at UNC Lineberger Comprehensive Cancer Center (Chapel Hill, N.C.): The FDA’s real-time clinical trial model will hasten interpretation of data in safety and efficacy in clinical trials. This model will lead to faster decisions for approvals or denials. This concept is long overdue and is an exciting first step in getting new and effective treatments to our patients.
Paul Swiecicki, MD. Associate Professor of Internal Medicine-Hematology/Oncology, Medical Director of the Oncology Clinical Trial Support Unit, and Associate Chief of Clinical Research in the Division of Hematology/Oncology at University of Michigan Rogel Cancer Center (Ann Arbor): The real-time clinical trial model is an exciting pilot which has the potential to streamline development of novel agents while simultaneously optimizing safety by offering the FDA a clean line of sight regarding emerging toxicities. Although promising, long-term success will depend on implementation of novel AI data tools to assist with data extraction and the ability for sites to simultaneously resolve data queries from both the FDA and pharmaceutical sponsors. Time will tell if this pilot translates to improved patient outcomes versus increasing the cost of conducting research without incremental gains over traditional workflows.
Russell Szmulewitz, MD. Associate Director for Clinical Investigation at the UChicago Medicine Comprehensive Cancer Center: All of us involved in clinical research appreciate the inefficiencies inherent in the current processes of drug development. Real-time data acquisition and transmittal to regulators once quality controlled should help address some of these inefficiencies. I am hopeful that this program will be successful and, if so, can be expanded more broadly to further accelerate drug development and clinical research innovation.
Theodoros Teknos, MD. President and Scientific Director for the University Hospitals Seidman Cancer Center at University Hospitals Cleveland Medical Center and Deputy Director of the Case Comprehensive Cancer Center: Efficient and safe conduct of clinical trials is the cornerstone of cutting-edge cancer care. University Hospitals-Seidman Cancer Center supports the FDA’s efforts to incorporate AI-enabled optimization for early phase clinical trials, particularly as it relates to patient identification and enrollment, documentation and regulatory compliance.
However, we are more cautiously optimistic on the reliance of AI algorithms in decisions involving dose escalation and “go-no go” determinations for trial continuation. Large language models must include appropriate physician oversight and the ability to override decisions based on clinical expertise to be maximally effective.
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