National Institutes of Health Develops AI Algorithm to Identify Potential Volunteers for Clinical Trials

AdvaMed, the world’s largest medical technology association representing device, diagnostics and digital technology companies, released a white paper that reviews the current landscape of artificial intelligence (AI)-based applications and products in the health care sector, and identifies steps to accelerate the use of AI in medical technologies. The trade association highlights two main types of tasks that AI is uniquely well suited to tackle (1) identifying and analyzing patterns in patient charts that practitioners might miss; and (2) automating repetitive routine tasks. AI is being incorporated into a range of technologies in the health care sector, and AdvaMed’s white paper focuses primarily on AI/machine learning (ML)-enabled medical devices, which are regulated by the FDA. AdvaMed anticipates that FDA will likely need to issue additional guidance to keep pace with development of AI models, including for adaptive models and approaches to mitigating bias. AdvaMed endorses FDA’s use of “Predetermined Change Control Plans” (PCCPs), which permit manufacturers to outline approaches to future modifications as part of an initial submission, and states that PCCPs should evolve to allow for greater post-market modifications for adaptive algorithms. The trade association also calls for domestic and international harmonization of requirements, including development of common AI standards to advance safe, secure and trustworthy use of AI.

On November 21, 2024, FDA’s Center for Devices and Radiological Health (CDRH) announced a pilot program aimed at improving public notice about potentially high‑risk medical device recalls.

Researchers from the National Institutes of Health (NIH) have developed an algorithm that harnesses AI to help accelerate the process of matching potential volunteers for relevant clinical research trials. The algorithm, called TrialGPT, is intended to help clinicians navigate the vast range of clinical trials available to patients by identifying potential matches and providing a summary of how that person meets the criteria for study enrollment. The team of researchers used a large language model (LLM) to develop an innovative framework for TrialGPT and compared the algorithm to the results of three human clinicians who analyzed over 1,000 patient-criterion pairs. The team also conducted a pilot user study, where two human clinicians reviewed six anonymous patient summaries and matched them to potentially suitable clinical trials. When clinicians used TrialGPT as a starting point, they spent 40% less time screening patients and maintained the same level of accuracy. The research team was selected for the Director’s Challenge Innovation Award, which will allow the team to further assess the model’s performance and fairness in real-world clinical settings. The researchers “anticipate that this work could make clinical trial recruitment more effective and help reduce barriers to participation for populations underrepresented in clinical research.”

In recent days, President-elect Trump has made progress in announcing the names of various individuals he intends to nominate to serve in some of the most senior and influential leadership positions at the Department of Health and Human Services (HHS) and which also require Senate confirmation. The first of these announcements was that President-elect Trump intends to nominate RFK Jr. to serve as HHS Secretary. The HHS Secretary is responsible for overseeing all 13 of the Department’s Operating Divisions, including the FDA, in addition to the Department’s staff divisions. President-elect Trump also recently announced his intent to nominate physician and former Representative Dave Weldon (R-FL) to serve as the next Director of the Centers for Disease Control and Prevention and Dr. Janette Nesheiwat as the next Surgeon General.

FDA and the Department of Veterans Affairs (VA) announced last week that they plan to develop the first intergovernmental health artificial intelligence (AI) lab. This lab would test health-related AI applications for safety and effectiveness in a virtual lab environment. VA Undersecretary for Health Dr. Shereef Elnahal announced the news during the Veterans Health Administration Innovation Experience conference. The VA serves 9 million veterans—the largest health system in the country. The VA operates 170 medical centers nationwide, meaning that the VA could be well positioned to serve as a base for AI assurance labs across the country.

Roughly one out of every ten people in the United States are affected by rare diseases. Many of these conditions are life‑threatening, and most lack FDA-approved treatments. Developing therapies for rare diseases, however, is challenging for various reasons, including the complex biology involved, the limited understanding of disease progression (i.e., the natural history), and the difficulties of conducting clinical trials in small patient populations. FDA engages with many stakeholders in the rare disease community to inform the development of safe and effective therapies and has made, in recent months, major strides in amplifying these efforts.

FDA’s Center for Devices and Radiological Health (CDRH) recently announced a pilot program to provide consumers and health care professionals with key information about clinical trials that supported the FDA’s approval of new medical devices. This program is modeled after the Center for Drug Evaluation and Research (CDER) drug trials snapshots program. The snapshots address questions about who participated in clinical studies of new medical technology and what clinical trial information is available about how it works in different groups of people. Snapshots are currently available for approvals of higher risk devices approved under original premarket approval (PMA) applications from April to July 2024. The snapshots only provide information that was available at the time of approval, and the FDA does not plan to update them over time, with real-world data, for example.

Dr. Michelle Tarver is a visionary public health executive, board-certified in ophthalmology with a doctorate in epidemiology, who serves as the Director of the Center for Devices and Radiological Health (CDRH). She has spent more than 15 years as a medical device regulator, driving strategic initiatives, conducting clinical research and changing organizational culture. Dr. Tarver has held various leadership positions while at the FDA, including the Deputy Director of the Office of Strategic Partnerships and Technology Innovation, and the Program Director of Patient Science and Engagement. Over the course of her career, she has conducted laboratory-based and epidemiological studies, clinical trials and surveys to capture patient preferences, as well as developed registries and patient-reported outcome measures. Dr. Tarver has extensive policy experience in crafting regulations, guidances and conducting premarket and postmarket reviews. She most recently served as the Deputy Center Director for Transformation, steering the development, implementation and direction of CDRH’s transformative projects and strategic initiatives. Under her leadership, CDRH has launched efforts to amplify the perspectives of people living with medical conditions, foster collaboration across the health care ecosystem and stimulate creative evidence generation pathways.