The FDA said this week it is taking steps to implement real-time clinical trials by leveraging AI and cloud computing to accelerate drug development, allowing regulators to view trial data in real time.
This modernized approach aims to give FDA scientists immediate access to safety signals and endpoints as they happen during a clinical trial. The initiative will also help accelerate promising therapies and build toward the FDA's end goal of "running real-time, continuous trials across all phases of drug development," FDA commissioner Marty Makary, M.D., said in a press statement.
"For 60 years, we've been conducting clinical trials in the same way, where key data signals can take years to reach the FDA," Markary added. That lag can unnecessarily delay regulatory decisions and slow down drug development, he said.
On average, it takes 10–12 years for a new drug to make it to FDA approval and reach the hands of patients. A main reason behind that lengthy timeline is early-stage trials, which often have high uncertainty, limited patient populations and inefficient decision-making.
Two proof-of-concept cancer studies are already underway as part of the agency's push to accelerate early-stage clinical research. AstraZeneca is running a phase 2, multi-state trial, called Traverse, focused on treatment-naive mantle cell lymphoma. Meanwhile, Amgen is conducting its phase 1 Stream-SCLC trial in patients with limited-stage small-cell lung cancer, with final site selection still in process, the FDA said.
The regulators have already met with the sponsors of each trial to establish the criteria for reporting signals in real time, according to the press release. The two drugmakers will be using Paradigm Health's platforms for real-time data review. The FDA has already received and validated signals from AstraZeneca's mid-stage trial, the agency reported.
These proof-of-concept studies will serve as the foundational groundwork for a broader pilot program, the FDA said. The agency is seeking public input on the program and evaluating how AI could be used to enhance decision-making in early trials. The program would allow drugmakers to use AI for safety monitoring and medication dose selection, flagging safety signals and improving patient recruitment, which is a common bottleneck in the drug development process.
The comment submission deadline is May 29, according to the press release. The FDA plans to outline the selection criteria for the pilot program in July and choose participants in August, the agency said.
Alivia Kaylor is a scientist and the senior site editor of Pharma Life Sciences.
