What To Know
- Michelle Tarver, deputy director of the Office of Strategic Partnerships and Technology Innovation at the Center for Devices and Radiological Health at the FDA, highlights the importance of these considerations.
- Advancing the work of measuring health preferences helps support our mission to assure patients have timely and continued access to medical devices of public health importance and to provide reasonable assurance of safety and effectiveness of such devices.
A Medical Device Innovation Consortium (MDIC) program today released a new framework that provides U.S. medical device companies a systematic approach for patient-focused clinical trial design to better meet patient needs and priorities.
The Science of Patient Input (SPI), with representatives from the U.S. Food and Drug Administration (FDA), patient advocacy groups, and the medical device industry, developed the approach so that the studies used to evaluate medical devices can better align with patients’ interests.
The patient-centered framework was developed to help inform researchers interested in conducting rigorous patient preference studies for medical device design, development, evaluation, and regulatory submissions. The approach is detailed in a new SPI framework, “Using Patient Preference Information in the Design of Clinical Trials.” The framework describes the first and only collection of scientifically rigorous methods for integrating patient preferences into clinical trial design.
According to MDIC Science of Patient Input (SPI) Program Director Kert Gunasekaran, “Scientific and technological advancements are accelerating device innovation, but ensuring access to those new therapies takes regulatory science. Our SPI program embraces the opportunity for industry to incorporate patient input more systematically into the process of developing products, enhancing our pathways to deliver unmet needs for patients, and ultimately speeding access to new therapies.”
Before approving a new medical device, regulators evaluate its safety and effectiveness, which includes consideration of the successful achievement of predetermined clinical trial results. To date, patients have had limited input on how clinical trial success is defined.
To ensure patient preferences are included, MDIC encourages clinical trial sponsors to incorporate patient perspectives into the total product life cycle, from research and development, to clinical trial design, and regulatory decision-making.
“Patient preferences may differ from those of clinicians and device manufacturers,” said Dr. Shelby Reed, professor of population health sciences and medicine at Duke University. “Patients and their families have a deep and personal understanding of what it’s like to live with a disease, and they often have valuable insights on how a device could affect their quality of life.”
Patient preference can often be contrary to conventional assumptions. Patient input may reveal patients’ willingness to take a substantial risk that the device may not work in exchange for the potential benefits. Conversely, patient input may suggest that a treatment must provide significant, not-yet-identified benefits before patients would be willing to accept the risk of a new approach.
Because there are unique challenges to this novel approach to collecting, analyzing, and applying patient preferences to clinical trial design, SPI has developed data-driven approaches for regulatory and clinical teams to:
- Identify what matters most to patients
- Measure patient input through proven qualitative and quantitative methodologies
- Engage in advanced planning and communications with the FDA
- Include patients in trial design, recruitment, and outcomes
Dr. Michelle Tarver, deputy director of the Office of Strategic Partnerships and Technology Innovation at the Center for Devices and Radiological Health at the FDA, highlights the importance of these considerations. “A patient-centered approach to the development and evaluation of medical devices along the total product life cycle can make an indelible impact on the lives of people living with serious health conditions. Advancing the work of measuring health preferences helps support our mission to assure patients have timely and continued access to medical devices of public health importance and to provide reasonable assurance of safety and effectiveness of such devices.”
One of the methods reviewed by the framework includes using a Bayesian Decision Analysis (BDA) model, which can help adjust statistical modeling considerations that can impact the study’s optimal sample size and measurements for achieving the study’s goals.
Although BDA was developed decades ago, it was adapted to the patient-centered framework by Massachusetts Institute of Technology (MIT) professor Andrew Lo, who was involved in several case studies featured in the framework. “The goal is to go beyond statistical p-values to also measure patient values,” Dr. Lo said. “The BDA model can be used to compute the greatest good for the greatest number. It measures optimal risk and benefit trade-offs, which can vary widely based on the severity of a disease or the afflicted patient population.”
Potential Benefits of Incorporating SPI Into Clinical Trial Design
- Clinical trial outcome data that matter to patients
- Development of devices that patients find useful
- Increased patient trust in medical devices
- Clear patient preferences regarding risk/benefit of medical devices
- Faster study/research participant recruitment, enrollment, and study completion
- Greater study/research participation, resulting in decreased loss to follow-up
- Streamlined data collection, resulting in better quality data
- Fewer protocol revisions
Available Free to Support Medical Device Companies
The new framework provides key learnings and best practices derived from recent medical device case studies on Parkinson’s disease, heart failure, mitral valve disease, and obesity. The report is one of several free resources available from MDIC’s SPI to encourage medical device companies to incorporate patient perspectives across the total product development life cycle.
