Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation | 24 561

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

1. What is the FDT-BioTech funding opportunity?

Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation (FDT-BioTech) is a National Science Foundation (NSF) discretionary grant program that supports research to advance the foundational scientific and engineering building blocks behind biomedical digital twins and synthetic data (including synthetic humans). The focus is on making these approaches credible, useful, and scalable in real-world healthcare settings.

2. What is the main goal of this NSF program?

The goal is to catalyze biomedical technological innovation by developing new underlying capabilities (not just incremental improvements) in the theory and engineering of biomedical digital twins and synthetic data approaches, particularly where these tools can strengthen decision-making in biomedical technology development.

3. What types of projects does FDT-BioTech prioritize?

The program prioritizes inherently interdisciplinary, method-building research that strengthens how digital, in silico models are created, validated, and used. Emphasis is placed on foundational methods and algorithms that improve model fidelity, uncertainty handling, validation strategies, and responsible synthetic data use.

4. Is this program intended to fund routine application development?

No. The opportunity is explicitly described as emphasizing foundational methods and algorithms rather than routine application development. Proposals are expected to advance core scientific and engineering foundations for biomedical digital twins and synthetic data.

5. What does NSF mean here by "biomedical digital twins" and "synthetic data"?

Based on the opportunity description, biomedical digital twins refer to digital, in silico computational models representing biomedical systems used to support biomedical technology development decisions. Synthetic data and related synthetic human approaches refer to methods for generating data or representations that can supplement or stand in for certain real-world testing and evaluation needs, with a strong emphasis on credibility and appropriate validation.

6. What is a central application area highlighted in the solicitation?

A central priority is improving the evaluation of medical devices using digital twins and synthetic human/synthetic data approaches. The program highlights the need for more reliable computational models to assess device safety, performance, and effectiveness, including in conditions that are difficult to test thoroughly through traditional studies alone.

7. How should proposals connect to biomedical technology and healthcare needs?

Proposals are expected to show relevance to current and emerging challenges in biomedical technology development and assessment. In other words, applicants should connect foundational technical advances to pressing needs in the medical device pipeline and the broader healthcare innovation ecosystem.

8. What disciplines or expertise areas are expected to be integrated?

The program is aimed at inherently interdisciplinary research. The description specifically notes integration across areas such as applied mathematics, statistics, computational science, engineering, and biomedical or clinical domains.

9. Who is eligible to apply?

Eligibility is limited to Institutions of Higher Education (IHEs). Only accredited two-year and four-year IHEs (including community colleges) with a campus located in the United States may submit proposals, and they must apply on behalf of their faculty members.

10. Can an individual researcher apply directly?

No. The opportunity states that proposals must be submitted by eligible Institutions of Higher Education on behalf of their faculty members.

11. Are community colleges eligible?

Yes. The eligibility statement includes accredited two-year IHEs, including community colleges, provided they have a campus located in the United States and submit proposals on behalf of faculty.

12. Are non-U.S. campuses or international branch campuses allowed to perform work?

The opportunity includes a specific note addressing international branch campuses of U.S. IHEs. If any project funds would support work performed at an international branch campus (including via subawards or consulting arrangements), the proposal must clearly explain the benefits of conducting those activities there and justify why the work cannot be carried out at the U.S. campus.

13. What does the solicitation require if funds support an international branch campus through subawards or consultants?

If project funds support work at an international branch campus of a U.S. IHE through subawards or consulting, the proposal must provide a clear explanation of the benefits of doing the work at that location and a justification for why it cannot be done at the U.S. campus.

14. What is the funding instrument for this opportunity?

The funding instrument is a grant.

15. What is the activity category for this opportunity?

The activity category is "Science and Technology and Other Research and Development."

16. What is the opportunity number for FDT-BioTech?

The opportunity number is 24-561.

17. What CFDA numbers are associated with this opportunity?

The opportunity record lists CFDA numbers 47.049, 47.070, and 93.310.

18. How many awards does NSF expect to make?

NSF anticipates making about 10 awards.

19. What is the closing date for proposals?

The original closing date listed is 2025-05-05.

20. Is the maximum award amount (award ceiling) provided?

No. The award ceiling is not specified in the provided information. Applicants would need to consult the full solicitation for details such as budget limits, project duration, and any track-specific constraints (if applicable).

21. What kind of advances does NSF want to see from funded projects?

The program encourages mathematically grounded and engineering-forward research that improves the credibility and scalability of biomedical digital twins and synthetic data approaches. The description emphasizes advances that strengthen model fidelity, uncertainty handling, validation strategies, and responsible synthetic data use, with a clear line of sight to better evaluation and advancement of medical devices and other biomedical technologies.

22. How should applicants think about the program in one sentence?

FDT-BioTech is a method-building NSF program for the next generation of biomedical digital twins and synthetic data, designed to enable more reliable, scalable, and decision-relevant computational evaluation of medical devices and related biomedical technologies.