Imaging, Biomarkers and Digital Pathomics for the Early Detection of Premetastatic Aggressive Cancer (R01 Clinical Trial Optional) | PAR 19 264

Opportunity Information: Apply for PAR 19 264

The grant opportunity "Imaging, Biomarkers and Digital Pathomics for the Early Detection of Premetastatic Aggressive Cancer (R01 Clinical Trial Optional)" (PAR 19-264) is a National Institutes of Health (NIH) discretionary grant program designed to push early cancer detection beyond today’s limitations, especially in the difficult zone where clinicians are trying to figure out which early findings are truly dangerous and which are unlikely to progress. The central focus is premetastatic aggressive cancer, meaning cancers (or precancerous lesions) that have not yet spread but are biologically poised to behave aggressively. The program is built around the idea that earlier detection only helps patients if it can reliably distinguish lethal disease from indolent or slow-growing disease, and if it reduces the real-world harms of unnecessary workups and treatments.

The FOA supports state-of-the-art projects that develop and rigorously characterize integrated approaches combining imaging, biomarkers, and digital pathomics, with room to incorporate other "omics" data streams (for example, genomic, transcriptomic, proteomic, metabolomic, or epigenomic signals) when they strengthen performance. A major theme is data integration rather than single-modality advances. Applicants are encouraged to use N-dimensional, co-registered and cross-correlated imaging data (in other words, multiple imaging types and features aligned in space and time) and to pair that with multiplexed biomarker results and computational pathology derived from digitized tissue slides. The goal is to create detection and risk-stratification methods that are more sensitive (finding real aggressive disease earlier) and more specific (avoiding alarms for findings that will not become clinically meaningful).

A key emphasis is reducing diagnostic uncertainty in clinical decision-making. This opportunity is intentionally technology agnostic, meaning it does not insist on one imaging modality, one biomarker class, or one computational approach. Instead, it prioritizes measurable improvements in diagnostic performance and clinical relevance. The kinds of analytic strategies explicitly encouraged include artificial intelligence and other advanced computational methods for pattern recognition and feature fusion across modalities. The FOA also highlights visualization approaches, including virtual reality visualization, as potential tools to help researchers explore complex, multi-dimensional datasets and potentially reveal relationships that are difficult to see with conventional displays.

Projects funded under this FOA are expected to align with and contribute to the broader Consortium for Imaging and Biomarkers (CIB) Research Program, meaning awardees will not operate as isolated labs. The CIB’s program-level goals are straightforward and clinically grounded: (1) improve diagnostic performance by developing methods that can identify lethal cancer early and distinguish it from non-lethal disease, (2) minimize or better manage overdiagnosis (a major problem in screening programs where detecting more abnormalities can lead to overtreatment), and (3) reduce false positives and false negatives, which drive patient anxiety, unnecessary invasive follow-up procedures, missed opportunities for early treatment, and overall inefficiency in care.

The funding mechanism is an NIH R01, which typically supports mature, hypothesis-driven or development-and-validation research projects with a clear plan, milestones, and a strong justification for why the proposed approach can move the field forward. The label "Clinical Trial Optional" indicates that applicants may include a clinical trial if it is appropriate for the proposed work, but a clinical trial is not required. The activity category listed for the opportunity is Education and Health, and the CFDA numbers associated with it are 93.393 and 93.394. The original posting date is May 1, 2019, and the original closing date shown is December 10, 2021.

Eligibility is broad and includes many types of organizations that commonly participate in biomedical research, such as state, county, city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments; tribal organizations that are not federally recognized; public housing authorities/Indian housing authorities; nonprofit organizations with or without 501(c)(3) status; for-profit organizations other than small businesses; and small businesses. In addition, the FOA explicitly notes other eligible applicants such as Alaska Native and Native Hawaiian Serving Institutions, Asian American Native American Pacific Islander Serving Institutions (AANAPISISs), Hispanic-serving Institutions, Historically Black Colleges and Universities (HBCUs), Tribally Controlled Colleges and Universities (TCCUs), faith-based or community-based organizations, eligible federal agencies, regional organizations, U.S. territories or possessions, and even non-U.S. (foreign) entities. This breadth signals an intent to draw in diverse institutional perspectives and datasets and to accelerate progress through a wide research ecosystem.

In practical terms, this FOA is aimed at teams that can bring together radiology or other medical imaging, laboratory biomarker development and validation, digital pathology, and strong computational/data science capabilities, then demonstrate that the combined system improves early identification of aggressive disease while reducing errors and unintended consequences. The most competitive projects under this kind of announcement are typically those that can show a realistic path to clinically meaningful performance, explain how multi-modal data will be aligned and analyzed, and define how success will be measured in ways that matter to patients and clinicians (for example, fewer unnecessary biopsies, better prediction of aggressive progression, and fewer missed aggressive cancers).

• The National Institutes of Health in the education, health sector is offering a public funding opportunity titled "Imaging, Biomarkers and Digital Pathomics for the Early Detection of Premetastatic Aggressive Cancer (R01 Clinical Trial Optional)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.393, 93.394.
• This funding opportunity was created on 2019-05-01.
• Applicants must submit their applications by 2021-12-10. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.

Apply for PAR 19 264

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