DocumentCode
37981
Title
Grand Challenge: Applying Regulatory Science and Big Data to Improve Medical Device Innovation
Author
Erdman, Arthur G. ; Keefe, Daniel F. ; Schiestl, R.
Author_Institution
Dept. of Mech. Eng., Med. Devices Center at the Univ. of Minnesota, Minneapolis, MN, USA
Volume
60
Issue
3
fYear
2013
fDate
Mar-13
Firstpage
700
Lastpage
706
Abstract
Understanding how proposed medical devices will interface with humans is a major challenge that impacts both the design of innovative new devices and approval and regulation of existing devices. Today, designing and manufacturing medical devices requires extensive and expensive product cycles. Bench tests and other preliminary analyses are used to understand the range of anatomical conditions, and animal and clinical trials are used to understand the impact of design decisions upon actual device success. Unfortunately, some scenarios are impossible to replicate on the bench, and competitive pressures often accelerate initiation of animal trials without sufficient understanding of parameter selections. We believe that these limitations can be overcome through advancements in data-driven and simulation-based medical device design and manufacturing, a research topic that draws upon and combines emerging work in the areas of Regulatory Science and Big Data. We propose a cross-disciplinary grand challenge to develop and holistically apply new thinking and techniques in these areas to medical devices in order to improve and accelerate medical device innovation.
Keywords
biomedical engineering; biomedical equipment; simulation; virtual reality; anatomical conditions; animal trials; bench tests; big data; clinical trials; cross disciplinary grand challenge; design decision impact; expensive product cycles; extensive product cycles; humans; interface; medical device innovation; parameter selections; preliminary analyses; regulatory science; simulation-based medical device design; simulation-based medical device manufacturing; Computational modeling; Data handling; Data models; Data storage systems; Data visualization; Humans; Information management; Big data; medical devices; modeling and simulation; regulatory science; virtual reality; visualization; Animals; Biomedical Engineering; Computational Biology; Computer Simulation; Computer-Aided Design; Device Approval; Equipment Design; Humans; Models, Biological;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2013.2244600
Filename
6425442
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