Project Grant R00CA286966
- Federal Grant Award Summary The University of Chicago received a $372,628 Project Grant from the National Cancer Institute under the Cancer Detection and Diagnosis Research program (CFDA 93.394) awarded on September 12, 2025, with a completion date of August 31, 2028. This award supports the development and advancement of spatiomolecular profiling technologies for human cancer research. Specifically, the project focuses on developing Array-Seq, a large-format spatially resolved transcriptomics...
- Federal Grant Award Summary New York University School of Medicine received a $681,215 Project Grant award from the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394), effective September 1, 2025, through August 31, 2030. The project, titled "A Path Towards Leveraging AI to Enable Point-of-Care MR Devices for Disease Detection," develops artificial intelligence (AI)-driven diagnostic technology to improve early detection of...
- Federal Grant Award Summary The National Cancer Institute awarded a $371,161 Project Grant to the University of Colorado-Denver under the Cancer Detection and Diagnosis Research Program (CFDA 93.394) on September 1, 2025, for a two-year performance period concluding August 31, 2027. The award funds the development of artificial intelligence (AI) algorithms designed to improve cervical cancer screening in low-resource settings. Specifically, the project will create advanced AI risk stratification...
- Federal Project Grant Award Summary The National Cancer Institute, under the Cancer Cause and Prevention Research program (CFDA 93.393), awarded the University of California, Los Angeles $825,627 beginning May 1, 2026, to develop advanced machine learning models for improving breast cancer prognosis prediction. The project, titled "Vision-Language Models with Explainability for Breast Cancer Prognosis Using Image and Clinical Data," will deliver three primary research products: (1)...
- Federal Grant Award Summary Wake Forest University Health Sciences received a $402,728 Project Grant from the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394), awarded July 16, 2025, with completion targeted for June 30, 2027. The award supports development of interpretable deep learning models for multi-modality imaging-based gastric cancer prognosis. The project addresses the critical clinical need to improve prognostic accuracy and...
- Federal Project Grant Award Summary The National Cancer Institute (NCI) awarded Sloan-Kettering Institute for Cancer Research a $693,290 Project Grant effective May 1, 2026, through April 30, 2031, under the Cancer Detection and Diagnosis Research Program (CFDA 93.394). This research initiative focuses on identifying spatial tumor microenvironment (TME) signatures for risk stratification in primary melanoma through comprehensive multiplexed immunofluorescence (MIF) tissue imaging analysis of 450...
- Federal Grant Award Summary Dana-Farber Cancer Institute, Inc. received a $833,467 Project Grant award dated September 17, 2025, from the National Cancer Institute under the Cancer Detection and Diagnosis Research program (CFDA 93.394) to develop and deploy open-source artificial intelligence tools that improve cancer clinical trial feasibility and patient recruitment. The ACTIVATE (AI-Driven Clinical Trial Information and Viability Assessment Tool for EHRs) project will extend the existing...
- Federal Grant Award Summary The National Cancer Institute awarded the University of Illinois a $386,279 Project Grant on July 10, 2025, under the Cancer Detection and Diagnosis Research program (CFDA 93.394) to develop innovative immunotherapy screening capabilities. The grant funds the creation of a microfluidic device cassette and associated functional immune assay protocols designed to enable personalized immunotherapy screening directly on core needle biopsies from cancer patients. This...
- Federal Grant Award Summary DePaul University received a $855,799 Project Grant from the National Cancer Institute under the Cancer Cause and Prevention Research program (CFDA 93.393) awarded on June 16, 2025, with a completion date of May 31, 2028. The project, titled "VS-EDGE: Visual-Semantic Explanations for Diagnostic Guidance," aims to develop and validate a novel Semantic Deep-Learning Neural Network (SDNN) model that creates explainable computer-aided diagnosis (CAD) systems for...
- Federal Grant Award Summary The National Cancer Institute (NCI) awarded The Johns Hopkins University a $249,000 Project Grant under the Cancer Detection and Diagnosis Research program (CFDA 93.394) effective January 1, 2026 through December 31, 2028. This grant supports research titled "Large-Scale Artificial Intelligence Using Radiomics, Deep Learning, and Physics-Based Generative Modeling to Improve Clinical Outcomes in Nuclear Medicine." The project addresses critical challenges...
The National Cancer Institute awarded the University of Chicago a $249,000 Project Grant under the Cancer Detection and Diagnosis Research program (CFDA 93.394) for the period of April 1, 2026 through March 31, 2029. This research initiative develops explainable artificial intelligence (AI) models to predict early-stage melanoma recurrence by integrating multiplexed tissue imaging, spatial transcriptomics, and histopathological data. The project addresses a critical clinical need, as current prognostic tools inadequately identify high-risk patients at the time of diagnosis, limiting opportunities for improved surveillance and personalized treatment interventions. The research deliverables include computational approaches for identifying and quantifying known prognostic features and novel biomarkers through multi-modal analysis of multiplexed imaging and spatial transcriptomic data; development of interpretable machine-learning models with clinical validation capability; and integration of histopathologic imaging with electronic health records to create deployable clinical prognostic tools. By combining single-cell multiplexed imaging data with transcriptomic signatures and clinical information, the project aims to elucidate biological mechanisms driving early-stage melanoma recurrence and produce actionable prognostic tools suitable for clinical deployment following independent validation.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $249.0k | 5/4/26 |