AUTHOR=Morrison Tina M. , Pathmanathan Pras , Adwan Mariam , Margerrison Edward 

TITLE=Advancing Regulatory Science With Computational Modeling for Medical Devices at the FDA's Office of Science and Engineering Laboratories

JOURNAL=Frontiers in Medicine

VOLUME=Volume 5 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2018.00241

DOI=10.3389/fmed.2018.00241

ISSN=2296-858X

ABSTRACT=Protecting and promoting public health is the mission of the U.S. Food and Drug Administration (FDA).  The FDA's Center for Devices and Radiological Health (CDRH) regulates medical devices marketed in the U.S., and envisions itself as the world’s leader in medical device innovation and regulatory science.  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 regulatory science priority by CDRH, and also 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 evidence from computational modeling (i.e., 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 digital evidence has been used in regulatory submissions by industry to CDRH in the last year.  It concludes by discussing the potential future role for computational modeling and digital evidence in medical device innovation.