The National Cancer Institute (NCI) awarded a $256,487 Project Grant under the Cancer Research Manpower (CFDA 93.398) program to the Sloan-Kettering Institute for Cancer Research in New York, NY. The purpose of this 5-year grant is to develop multimodal predictive models that integrate real-world data from circulating tumor DNA (ctDNA) sequencing, radiomics, tumor registries, and tissue genomics to improve risk stratification and clinical management of non-small cell lung cancer (NSCLC). The...
This Project Grant award from the National Cancer Institute's Cancer Detection and Diagnosis Research program (CFDA 93.394) provides $683,089 to the Sloan-Kettering Institute for Cancer Research to develop an interpretable, non-destructive, and cost-efficient solution for accurately scoring PD-L1 expression in tumor and immune cells. The goal is to improve patient stratification for immunotherapy by addressing the high variability and limited accuracy of current PD-L1 immunohistochemistry...
This federal Project Grant award, funded by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286), supports the development of an AI-powered system to enhance the detection and tracking of metastatic colorectal cancer using computed tomography (CT) imaging. The $718,456 award, with a project period from July 1, 2025 to May 31, 2029, will enable researchers at the...
This Project Grant awarded by the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to Metastx LLC, a small business located in Pittsburgh, PA, provides $399,954 in funding from Jul 1, 2025 to Jun 30, 2026. The project aims to develop a novel predictive model for metastatic potential in early-stage prostate cancer patients by integrating epithelial-mesenchymal transition signature markers with advanced imaging and machine learning techniques. The goal is to...
This federal Project Grant award from the National Cancer Institute (CFDA 93.393 - Cancer Cause and Prevention Research) to the Sloan-Kettering Institute for Cancer Research provides $700,611 to conduct a randomized controlled trial (RCT) evaluating the use of artificial intelligence (AI) to assist dermatologists in diagnosing melanoma. The project aims to determine the potential benefits and barriers to adopting AI technology, as well as assess its impact on reducing the number of unnecessary...
This federal Project Grant award from the National Cancer Institute (CFDA 93.395 - Cancer Treatment Research) provides $684,367 to the Baylor College of Medicine to conduct research aimed at identifying new predictors of response to immune checkpoint inhibitor (ICI) therapy in patients with non-small cell lung cancer (NSCLC). The key objectives are to: 1) Identify intratumoral microbiome profiles predictive of ICI response using whole-metagenome sequencing; 2) Characterize spatial immune...
This federal Project Grant award from the National Cancer Institute (CFDA 93.393 - Cancer Cause and Prevention Research) provides $968,999.00 to the University of North Carolina at Chapel Hill to conduct research titled "OPTIMIZING SURVEILLANCE IN LUNG CANCER SURVIVORS WITH NOVEL IMAGING BIOMARKERS AND DEEP-LEARNING (OPTIMAL)". The overarching goal is to optimize survivorship of early-stage non-small cell lung cancer patients by incorporating a risk-based surveillance strategy that...
This Project Grant award from the National Cancer Institute's Cancer Detection and Diagnosis Research program (CFDA 93.394) provides $657,934 to The Johns Hopkins University from April 1, 2025 to March 31, 2030. The project aims to develop a more precise and broadly applicable neoantigen prediction algorithm by integrating multi-omic data, such as genomic, transcriptomic, and T-cell receptor sequencing, to enhance the selection and validation of neoantigens for cancer immunotherapy. Key...
This Project Grant award of $244,228 from the National Cancer Institute's Cancer Detection and Diagnosis Research program (CFDA 93.394) supports a research project at the University of Texas MD Anderson Cancer Center. The project aims to develop a functional proteomics approach to accurately map patient tumor samples to preclinical lung cancer models. Specifically, the researchers will: Expand proteomic profiling of lung cancer patient-derived xenograft (PDX) models using a reverse-phase protein...
The National Cancer Institute (NCI) awarded a Project Grant under the CFDA 93.394 Cancer Detection and Diagnosis Research program to Exai Bio Inc., a small disadvantaged business located in Palo Alto, California. The $1,280,908 grant, awarded on September 12, 2024, supports the development of a novel liquid biopsy assay and artificial intelligence (AI) model for early detection of non-small cell lung cancer (NSCLC) and prediction of cancer subtypes. The project aims to gather samples and test...