Abstract

Protecting and promoting public health is the mission of the U.S. Food and Drug Administration (FDA). FDA's Center for Devices and Radiological Health (CDRH), which regulates medical devices marketed in the U.S., envisions itself as the world's leader in medical device innovation and regulatory science–the development of new methods, standards, and approaches to assess the safety, efficacy, quality, and performance of medical devices. Traditionally, bench testing, animal studies, and clinical trials have been the main sources of evidence for getting medical devices on the market in the U.S. In recent years, however, computational modeling has become an increasingly powerful tool for evaluating medical devices, complementing bench, animal and clinical methods. Moreover, computational modeling methods are increasingly being used within software platforms, serving as clinical decision support tools, and are being embedded in medical devices. Because of its reach and huge potential, computational modeling has been identified as a priority by CDRH, and indeed by FDA's leadership. Therefore, the Office of Science and Engineering Laboratories (OSEL)—the research arm of CDRH—has committed significant resources to transforming computational modeling from a valuable scientific tool to a valuable regulatory tool, and developing mechanisms to rely more on digital evidence in place of other evidence. This article introduces the role of computational modeling for medical devices, describes OSEL's ongoing research, and overviews how evidence from computational modeling (i.e., digital evidence) has been used in regulatory submissions by industry to CDRH in recent years. It concludes by discussing the potential future role for computational modeling and digital evidence in medical devices.

Highlights

  • Food and Drug Administration (FDA) is to protect and promote public health, and it does so by ensuring the safety, effectiveness and security of FDA-regulated products1 These products include, but are not limited to, medical devices, drugs for humans and animals, and biological products such as vaccines and the blood supply, each of which are managed by separate Centers within the Agency

  • Each Center in the FDA is committed to advancing these efforts, which have accelerated the product development pathway and regulatory review cycle so that new, innovative products can be made available to the American public

  • Computational modeling has enabled the complete “in silico” simulation of clinical trials for medical imaging systems. By this we mean the implementation of different computational models to simulate the entire clinical evaluation of an imaging system, creating a “virtual clinical trial,” where no patients are physically exposed to the imaging system–more on this later

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Summary

Frontiers in Medicine

Bench testing, animal studies, and clinical trials have been the main sources of evidence for getting medical devices on the market in the U.S In recent years, computational modeling has become an increasingly powerful tool for evaluating medical devices, complementing bench, animal and clinical methods. This article introduces the role of computational modeling for medical devices, describes OSEL’s ongoing research, and overviews how evidence from computational modeling (i.e., digital evidence) has been used in regulatory submissions by industry to CDRH in recent years. It concludes by discussing the potential future role for computational modeling and digital evidence in medical devices

INTRODUCTION
Proposed computational modeling methods and approaches
Developing novel ways to use clinical data in evaluating medical devices
MODELING FOR MEDICAL DEVICES
COMPUTATIONAL MODELING RESEARCH
REGULATORY SUBMISSIONS
IN MEDICAL DEVICES
Findings
AUTHOR CONTRIBUTIONS
Full Text
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