Abstract

Applying Systems Thinking to Regenerative Medicine—A Workshop was organized by the National Academies of Sciences, Engineering, and Medicine’s Forum on Regenerative Medicine. The meeting brought together leaders from government, academia, industry, professional associations, foundations, patient communities, and other stakeholder groups to address the potential for cross-disciplinary systems thinking to advance regenerative medicine. Discussions during the meeting covered the role of data science in regenerative medicine and the importance of data science training and data literacy for the current and future regenerative medicine workforce.

Details

Title
Implementing systems thinking and data science in the training of the regenerative medicine workforce
Author
Plant, Anne L. 1   VIAFID ORCID Logo  ; Piscopo, Nicole 2 ; Saha, Krishanu 3   VIAFID ORCID Logo  ; Zylberberg, Claudia 4 ; Roy, Krishnendu 5 ; Tsokas, Katherine 6 ; Schumm, Samantha N. 7   VIAFID ORCID Logo  ; Beachy, Sarah H. 7   VIAFID ORCID Logo 

1  National Institute of Standards and Technology, Biosystems and Biomaterials Division, Gaithersburg, USA (GRID:grid.94225.38) (ISNI:000000012158463X) 
2  CRISPR Therapeutics, Cambridge, USA (GRID:grid.94225.38) 
3  University of Wisconsin-Madison, Department of Biomedical Engineering, Madison, USA (GRID:grid.14003.36) (ISNI:0000 0001 2167 3675) 
4  Akron Bio, Boca Raton, USA (GRID:grid.14003.36) 
5  Georgia Institute of Technology, Department of Biomedical Engineering, Atlanta, USA (GRID:grid.213917.f) (ISNI:0000 0001 2097 4943) 
6  Janssen Research and Development LLC, Spring House, USA (GRID:grid.497530.c) (ISNI:0000 0004 0389 4927) 
7  Health and Medicine Division, National Academies of Sciences, Engineering, and Medicine, Washington, USA (GRID:grid.451487.b) 
Pages
76
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20573995
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41536-022-00271-2
ProQuest document ID
2757876456
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.