This $455,000 Project Grant award from the National Institute of General Medical Sciences (NIGMS) Biomedical Research and Research Training Program (CFDA 93.859) supports research to decrease sepsis mortality in the pediatric population. The key products and services to be delivered include: Development of an AI-guided early sepsis identification tool to enable timely diagnosis and treatment. 2) Performing sepsis phenotyping and creating digital twin patient models to predict personalized...
The National Institute of General Medical Sciences (NIGMS) awarded a 5-year, $2,378,837 Project Grant under the Biomedical Research and Research Training program (CFDA 93.859) to the University of Massachusetts to develop a novel nanopore-based biosensing platform for the rapid, culture-independent detection of sepsis-causing pathogens directly from blood. The key products and services to be delivered include: Engineering nanopore biosensors to meet the clinical needs for accurate and rapid...
This federal Project Grant award from the National Institute of General Medical Sciences (NIGMS) Biomedical Research and Research Training Program (CFDA 93.859) will support research aimed at improving sepsis care through the development of AI-based clinical decision support systems. The $1,218,750 award to The Trustees of the University of Pennsylvania will fund a 5-year project to address key knowledge gaps in leveraging AI/ML methods to enhance sepsis recognition and treatment....
This $305,000 project grant awarded by the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training program (CFDA 93.859), supports the development of a clinical decision support system (CDSS) called Sepsis FLO. The CDSS is designed to precisely guide blood volume diagnosis and treatment for sepsis patients. Key activities include: 1) Developing an alpha prototype of the CDSS through user-centered design; 2) Validating three functional...
This Project Grant award from the National Institute of Allergy and Infectious Diseases (NIAID), under the Allergy and Infectious Diseases Research program (CFDA 93.855), provides $2,583,391 in funding to the Regents of the University of California, San Francisco to conduct research on sepsis. The key objectives are to: Identify known and novel pathogens responsible for septic shock using metagenomic sequencing of host and microbe samples from 1,563 patients enrolled in the CLOVERS clinical...
This federal Project Grant award from the National Institute of Allergy and Infectious Diseases (NIAID), under the Allergy and Infectious Diseases Research program (CFDA 93.855), is focused on developing personalized sepsis therapies by integrating high-frequency physiological data with electronic health records. The $186,221 award, effective from February 1, 2025 to January 31, 2030, aims to achieve the following key products and services: Augment sepsis phenotypes by incorporating...
The National Institute of General Medical Sciences (NIGMS) awarded a $312,974 Project Grant (CFDA 93.859 - Biomedical Research and Research Training) to the University of California, San Diego (UCSD) to develop multi-modal foundation models for early detection of sepsis. Over the 5-year project period, the research team will: 1) curate large-scale electronic health record (EHR) data for pre-training the foundation models, 2) develop multi-modal transformer models to effectively represent...
This $166,204 Project Grant awarded by the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859) will support the development and advancement of cell-free DNA as a novel biomarker with predictive and prognostic applications for sepsis. The principal investigator, Dr. Nicholas P. Semenkovich, will leverage new techniques and deep learning algorithms he has previously developed to analyze cell-free DNA and identify septic...
The National Institutes of Health (NIH) Office of the Director awarded a $450,000 Project Grant under the Trans-NIH Research Support program (CFDA 93.310) to The Ohio State University to develop a Human-Centered Artificial Intelligence (HCAI) system to improve early prediction and decision-making for sepsis. The project aims to create a deidentified sepsis patient database, develop advanced machine learning models for early sepsis risk prediction with uncertainty quantification, and design a...
This Project Grant award from the National Science Foundation (NSF) under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program provides $298,646 to Anvil Diagnostics Inc. to develop a rapid diagnostic test for sepsis-causing pathogens. The proposed technology aims to comprehensively identify and quantify pathogens in small volumes of blood within a few hours, which could significantly improve sepsis detection and treatment, especially for vulnerable newborns. Key innovations...