All applications to this funding opportunity announcement should fall within the mission of the Institutes/Centers. The following NIH Offices may co-fund applications assigned to those Institutes/Centers.
The Division of Cancer Treatment and Diagnosis (DCTD) and the Center for Biomedical Informatics and Information Technology (CBIIT) at the National Cancer Institute (NCI) announce the Digital Twins Radiation Oncology (DTRO) administrative supplement opportunity that seeks to support collaborative, multidisciplinary research in radiation oncology in the development of digital twins. For the purposes of this notice, a digital twin as defined by the Digital Twin Consortium (DTC) is a a virtual representation of real-world entities and processes, synchronized at a specified frequency and fidelity. The DTC definition notes that:
Digital twins accelerate holistic understanding, optimal decision making, and effective action;
Real-time and historical data are used to represent the past and present and to predict the future; and
They are motivated by outcomes, tailored to use cases, powered by integration, built on data, guided by domain knowledge, and implemented in information technology (IT) and operational technology (OT) systems and may involve data streams via the internet of things (IOT) and other new technologies such as quantum sensors.
As such, the research funded by these supplements must be responsive, adaptive, dynamic computational models and software implementations (implemented in IT/OT/IOT systems). Simple look-up tables will not be considered responsive due to their lack of dynamic input and real-time updating capacity as defined above. In this context, DTRO applications must propose a new collaborative digital twin project that intersects data science with predictive radiation oncology and must include at least one innovative use of patient specific dynamic (changing over time) data to augment predictions and ultimately treatment decisions.
Innovative use of multiscale data is required.
Examples of scales and test or data at each scale:
Example of Scale
Example of Data Elements at that Scale (list is not exhaustive)
Blood test, mass spectrometry, ctDNA, methylation, genetic sequencing
Extracellular vesicles and their component analysis
Pathology/histology imaging, traditional and automated/AI driven
Functional exams, imaging (e.g. MRI, PET)
Validated performance tests and questionnaires, family history data, EHRs
Locations/geographical data (place science), economic toxicity analysis, diversity and bias science
Digital twins promise to provide numerous advantages as a translational tool in the conduct of translational and clinical research as well as patient care delivery.
This administrative supplement funding opportunity seeks to leverage the existing infrastructure in radiation oncology, radiation biology and data science to facilitate new high-quality collaborative opportunities that integrate across disciplines and data scales. The programmatic intent of the DTRO program is to enable new cross-correlatives and response measures leading to the optimization of treatment approaches using digital twins for human cancer. It is our intention that ultimately these supplements provide the tools to test hypotheses in clinical trials.
Examples of types of predictive oncology questions where a digital twin could be deployed are:
Should radiopharmaceuticals be considered for this patient, and if so, when and which type?
On which clinical trial should the patient be enrolled?
What is the best frequency for follow-up monitoring (intervals/plan)?
What clinical tumor volume (CTV) margin should be used?
What is the patients specific risk for secondary cancer (unique biology and exposure history)?
What is the biologic dose of radiation based on the physical dose for a specific patient?
What are the possible short- and long-term complications and how can they best be avoided?
At the conclusion of the support period, all digital twins and/or their components (i.e. data and models) must be containerized and well documented.
Application and Submission Information
Applications for this initiative must be submitted using the following opportunity or its subsequent reissued equivalent.
PA-20-272 - Administrative Supplements to Existing NIH Grants and Cooperative Agreements (Parent Admin Supp Clinical Trial Optional)
Applicants are strongly encouraged to notify the NCI Program Director assigned to the parent award and Jeff Buchsbaum (firstname.lastname@example.org) that a request has been submitted in response to this NOSI to facilitate efficient processing of the request.
Eligibility and Eligible Individuals (Program Director/Principal Investigator):
Projects through this administrative supplement opportunity are to be co-led by a current NCI grantee and at least one partnering collaborator who is not named on the parent award. Either the PI of the parent award or the collaborator must have demonstrated data science-oriented translational research expertise.
The parent award must be an active grant or cooperative agreement (R00, R01, R21, R35, R37, U01, P01, P30, P50, U19, U24, or U54) with an NCI primary assignment.
The proposed DTRO collaborative project must include research that supports development of digital twins and radiation oncology clinical treatment optimization goals and be based on multiple scales of data. It is encouraged to incorporate dynamic data (multiple measurements over time, in particular during treatment) as part of the projects digital twin component.
The parent award must be able to receive funds in FY24 and be active throughout the 1-year project period. The parent award must not be in an extension period (e.g., cost or no-cost extension).
A DTRO collaboration team, at a minimum, must be composed of the PI/MPI of an active NCI parent grant and a collaborator PI who is not listed on the NCI parent grant. The partnering collaborator PI does not need to hold a current active award but must be eligible to apply for an independent NIH research grant.
Either the parent award or the collaborating partner(s) proposed research plan must include a digital twin research component. The research plan for the proposed DTRO project must include multiple scales of biological data as per Table 1 of examples of what is meant by scales. The collaboration must involve a novel research question and must be within the broad scope of the parent award.
For supplements to parent awards that include multiple program directors/principal investigators (PD/PIs), the supplement may be requested by any or all of the PD/PIs on that award (in accordance with the existing leadership plan) and must be submitted by the awardee institution of the parent award.
Early Stage Investigators (ESIs) are encouraged to apply as part of collaborative teams.
NIH supports the principles of diversity, equity, inclusion, and accessibility (DEIA).
Collaborations with foreign institutions are allowed, but investigators must provide a justification for the collaboration. Please note that some foreign collaborations will require U.S. State Department approval by the NCI, and that may delay receipt of funding.
Application and Award Due Dates:
This is a one-time announcement.
All requests, regardless of the parent award funding mechanism, must be received by 5:00 PM local time on March 21, 2024.
Late applications will not be accepted.
The earliest anticipated award/start date is July 1, 2024.
Supplement budget requests must reflect the actual needs of the proposed one-year project and are limited to $250,000 total costs per project (e.g., for a collaboration between two NIH awardees, each could request up to $125,000 in total costs in independent budgets; for a collaborative project that includes a subcontract, the parent research program award could request up to $250,000 in total costs to support the collaboration, which would include the sub-award).
At least one full year on the parent award or partnering collaborator award (if not utilizing a sub-award mechanism) must remain at the time of funding - the proposed project period cannot exceed that of the parent award.
It is allowable for institutions to waive indirect costs, but not required.
Budget allocation to the parent award or collaborator award/sub-award cannot exceed 70 percent of the total costs for the collaborative partnership (e.g., the proposed financial split between collaborating partners could be between 50-50, 70-30, or 30-70).
Requests for no-cost extensions of the parent grant to accommodate a supplement will not be permitted; however, a no-cost extension of the supplement will be considered if the parent grant is still active.
If the budget includes a request for salary support, a justification and clear details on what each person will be responsible for are required. If supporting students and/or postdocs, please indicate if they are already working in the lab or when they will be recruited. A description of how the student/postdoc will be supported after the conclusion of the one-year supplement must be included. It is not appropriate to have to-be-named personnel listed as part of the budget request.
The administrative supplement awards pursuant to this opportunity are contingent upon the availability of funds from NCI and the receipt of a sufficient number of meritorious requests. Four collaborative awards are anticipated.
Applicants should begin the supplement application abstract by stating This application is being submitted in response to the Notice of Special Interest (NOSI) identified as NOT-CA-24-015.
For funding consideration, applicants must include NOT-CA-24-015 (without quotation marks) in the Agency Routing Identifier field (box 4b) of the SF424 R&R form. Applications without this information in box 4b will not be considered for this funding opportunity.
Page limits: The Research Strategy section of the application is limited to 4 pages (excluding references).
A single application should be submitted. For a collaborative application between two NIH awardees, each awardee should submit independent budgets.
Review and Selection Process
NCI will conduct administrative reviews of applications and will support meritorious applications submitted for consideration based on the availability of funds and programmatic priorities.
Specific Review Criteria
NIH staff will consider the potential impact of the collaborative project on the translation of digital twins research to human outcomes. Collaborations with combined expertise in digital twins and human cancer research are encouraged. Digital twin and radiation oncology components are required. Two examples are listed below:
Example Grant 1: Digital twin optimization of follow-up monitoring to minimize financial toxicity while offering the patient no increased risk of recurrence or non-optimal symptom management.
Example Grant 2: Digital twin evaluation and optimized selection of the current open treatment protocols for disease X for a specific patient, place and time. This optimization of trial selection should be based on multiscale, dynamic factors, in particular patient specific variables (e.g. tumor location, growth kinetics, known treatment sensitivities, tumor heterogeneity, comorbidities, other drugs currently being used, etc.).
Other criteria that will be considered during the review include:
The translational and clinical significance of the specific question being pursued in the collaborative project;
The requirement for and importance of collaborative research to accomplish the goals of the project;
The digital twin product of this supplement focuses on one or more aspect(s) of radiation oncology care delivery;
Robust data assimilation such that the model (digital twin) is updated to reflect the changes in the real system (cancer patient) over time.
Rigor and innovation of the model (digital twin) design with adequate plans to address relevant biological variables, such as sex, age, gender (all proposals will focus on humans only);
Realistic scope of work, given the time and budget requested;
Supportive environments at research institution(s);
Clear articulation of the logistics of the collaboration;
Statement confirming that the digital twin(s) products (data and models) will be uploaded to the appropriate NCI public repository after publication and in accordance with the NIH data sharing policy; and
Collaboration with scientists funded by other agencies doing closely aligned but not duplicative work is permitted.
Note that projects facilitating new collaborations are of particular interest.
Applicants are encouraged to discuss their application with the scientific/research contacts listed in this NOSI prior to submission.
Applications nonresponsive to the terms of this NOSI will not be considered for funding.
Please direct all inquiries to:
Jeff Buchsbaum, M.D., Ph.D., A.M. Division of Cancer Treatment and Diagnosis National Cancer Institute (NCI) Telephone: 240-276-5690 Email: email@example.com
(data science) Emily Greenspan, Ph.D. Center for Biomedical Informatics & Information Technology National Cancer Institute (NCI) Telephone: 301-395-2871 Email: firstname.lastname@example.org
Fenglou Mao Office of Data Science Strategy (ODSS) Telephone: 240-627-1111 E-mail: email@example.com