Conference: Interagency Analysis and Modeling Group/Multiscale Modeling Consortium (IMAG/MSM) Meeting on Operationalizing the NASEM Report on Digital Twins

Information

  • NSF Award
  • 2432168
Owner
  • Award Id
    2432168
  • Award Effective Date
    8/15/2024 - 11 months ago
  • Award Expiration Date
    7/31/2025 - 5 days from now
  • Award Amount
    $ 30,000.00
  • Award Instrument
    Standard Grant

Conference: Interagency Analysis and Modeling Group/Multiscale Modeling Consortium (IMAG/MSM) Meeting on Operationalizing the NASEM Report on Digital Twins

On December 15, 2023, The National Academies of Sciences, Engineering and Medicine (NASEM) released a report entitled: “Foundational Research Gaps and Future Directions for Digital Twins” (“NASEM DT REPORT”). The purpose of this report was to bring structure to the burgeoning field of digital twins by providing a working definition and a series of research challenges that need to be addressed to allow this technology to fulfill its full potential. The concept of digital twins is compelling and has the potential to impact a broad range of domains. For instance, digital twins have either been proposed or are currently being developed for manufactured devices, buildings, cities, ecologies and the Earth as a whole. It is natural that the concept be applied to biology and medicine, as the most recognizable concept of a “twin” is that of identical human twins. The application of digital twins to biomedicine also follows existing trends of Personalized and Precision medicine, in short: “the right treatment for the right person at the right time.” Fulfilling the promise of biomedical digital twins will require multidisciplinary Team Science that brings together various experts from fields as diverse as medicine, computer science, engineering, biological research, advanced mathematics and ethics. The purpose of this conference, the “2024 Interagency Modeling and Analysis Group (IMAG)/Multiscale Modeling (MSM) Consortium Meeting: Setting up Teams for Biomedical Digital Twins,” is to do exactly this: bringing together such needed expertise in a series of teaming exercises to operationalize the findings of the NASEM DT REPORT in the context of biomedical digital twins. As part of outreach and training efforts to broaden the participation within this growing field, this workshop will provide support for both traditionally under-represented categories of senior researchers as well as junior researchers such as graduate students and postdoctoral researchers. <br/><br/>Facilitating the development and deployment of biomedical digital twins requires operationalizing the findings and recommendations of the NASEM DT REPORT, which raises a series of specific and unique challenges in the biomedical domain. More specifically, there are numerous steps that need to be taken to convert the highly complex simulation models of biological processes developed by members of the MSM Consortium into biomedical digital twins that are compliant with the definition of digital twins presented in the NASEM DT REPORT. There are also identified challenges associated with these various steps. Some of these challenges can benefit from lessons learned in other domains that have developed digital twins while others will require the development of new techniques in the fields of statistics, computational mathematics and mathematical biology. This task will require multidisciplinary collaborations between mathematicians, computational researchers, experimental biologists and clinicians. This IMAG/MSM meeting will promote the concepts of Team Science to bring together experienced multiscale modeling researchers and experts from the mathematical, statistical, computational, experimental and clinical communities to form the multidisciplinary teams needed to operationalize the findings of the NASEM DT REPORT. The website for this meeting is at https://www.imagwiki.nibib.nih.gov/news-events/announcements/2024-imagmsm-meeting-september-30-october-2-2024, with the landing page for the Interagency Modeling and Analysis Group at https://www.imagwiki.nibib.nih.gov/.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Troy D. Butlertdbutler@nsf.gov7032922084
  • Min Amd Letter Date
    8/2/2024 - 11 months ago
  • Max Amd Letter Date
    8/2/2024 - 11 months ago
  • ARRA Amount

Institutions

  • Name
    University of Vermont & State Agricultural College
  • City
    BURLINGTON
  • State
    VT
  • Country
    United States
  • Address
    85 S PROSPECT STREET
  • Postal Code
    054051704
  • Phone Number
    8026563660

Investigators

  • First Name
    Gary
  • Last Name
    An
  • Email Address
    gan@med.med.edu
  • Start Date
    8/2/2024 12:00:00 AM

Program Element

  • Text
    STATISTICS
  • Code
    126900
  • Text
    COMPUTATIONAL MATHEMATICS
  • Code
    127100
  • Text
    MATHEMATICAL BIOLOGY
  • Code
    733400

Program Reference

  • Text
    Artificial Intelligence (AI)
  • Text
    Machine Learning Theory
  • Text
    CONFERENCE AND WORKSHOPS
  • Code
    7556
  • Text
    EXP PROG TO STIM COMP RES
  • Code
    9150