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Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation (FDT-BioTech)

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NSF 24-561

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NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

Supports interdisciplinary research projects that explore the mathematical and engineering foundations behind the development and use of digital twins in biomedical and healthcare applications.

Supports interdisciplinary research projects that explore the mathematical and engineering foundations behind the development and use of digital twins in biomedical and healthcare applications.

Synopsis

The Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation (FDT-BioTech) program supports inherently interdisciplinary research projects that underpin the mathematical and engineering foundations behind the development and use of digital twins and synthetic data in biomedical and healthcare applications, with a particular focus on digital, in silico models used in the evaluation of medical devices and the relevance of the developed models in addressing current and emerging  challenges affecting the development and assessment of biomedical technologies. The goal of the FDT-BioTech initiative is to catalyze biomedical technological innovation through new foundational development of methods and algorithms relevant to digital twins and synthetic humans.

Program contacts

Yulia R. Gel
ygel@nsf.gov (703) 292-7888 MPS/DMS
Zhilan J. Feng
zfeng@nsf.gov (703) 292-7523 MPS/DMS
Stephanie George
stgeorge@nsf.gov (703) 292-7825 ENG/CBET
Varun Chandola
vchandol@nsf.gov (703) 292-2656 CISE/OAC
Ashok Srinivasan
asriniva@nsf.gov (703) 292-2122
Laura Biven
odssdt@nih.gov (301)480-4021
Fenglou Mao
odssdt@nih.gov (301)451-9389
Aldo Badano
aldo.badano@fda.hhs.gov (301) 796-2534

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