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Outcomes from a Postgraduate Biomedical Technology Innovation Training Program: The First 12 Years of Stanford Biodesign

Overview of attention for article published in Annals of Biomedical Engineering, February 2013
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Title
Outcomes from a Postgraduate Biomedical Technology Innovation Training Program: The First 12 Years of Stanford Biodesign
Published in
Annals of Biomedical Engineering, February 2013
DOI 10.1007/s10439-013-0761-2
Pubmed ID
Authors

Todd J. Brinton, Christine Q. Kurihara, David B. Camarillo, Jan B. Pietzsch, Julian Gorodsky, Stefanos A. Zenios, Rajiv Doshi, Christopher Shen, Uday N. Kumar, Anurag Mairal, Jay Watkins, Richard L. Popp, Paul J. Wang, Josh Makower, Thomas M. Krummel, Paul G. Yock

Abstract

The Stanford Biodesign Program began in 2001 with a mission of helping to train leaders in biomedical technology innovation. A key feature of the program is a full-time postgraduate fellowship where multidisciplinary teams undergo a process of sourcing clinical needs, inventing solutions and planning for implementation of a business strategy. The program places a priority on needs identification, a formal process of selecting, researching and characterizing needs before beginning the process of inventing. Fellows and students from the program have gone on to careers that emphasize technology innovation across industry and academia. Biodesign trainees have started 26 companies within the program that have raised over $200 million and led to the creation of over 500 new jobs. More importantly, although most of these technologies are still at a very early stage, several projects have received regulatory approval and so far more than 150,000 patients have been treated by technologies invented by our trainees. This paper reviews the initial outcomes of the program and discusses lessons learned and future directions in terms of training priorities.

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Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Ireland 1 <1%
Unknown 115 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 19%
Researcher 15 13%
Other 14 12%
Student > Master 13 11%
Student > Doctoral Student 9 8%
Other 20 17%
Unknown 24 21%
Readers by discipline Count As %
Engineering 19 16%
Medicine and Dentistry 16 14%
Business, Management and Accounting 8 7%
Nursing and Health Professions 6 5%
Computer Science 6 5%
Other 30 26%
Unknown 32 27%