Project Grant R01EB037022
Award Date
5/1/25
Completion Date
4/30/29
Dollars Obligated
$343K
Federal Agency
National Institute of Biomedical Imaging and Bioenginering
Federal Grant Program
93.286
Assistance Type
Project Grant
Place of Performance
New Jersey, USA
Similar Awards
This National Science Foundation (NSF) Engineering program (CFDA 47.041) project grant of $596,920 awarded to Northeastern University aims to develop a mechanism-informed AI platform to enable flexible and robust biomanufacturing systems. The key research objectives are: (1) creating a multi-scale probabilistic knowledge graph model to integrate heterogeneous data on biological processes across molecular, cellular, and macroscopic scales; (2) developing interpretable federated learning to...
This $274,797 National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant award to Deepseq.ai LLC supports the development of an AI-driven platform to accelerate the identification of highly developable single-domain antibodies for drug discovery. The proposed work aims to create a multimodal AI model capable of rapidly screening large libraries to generate lead molecules with favorable binding affinity, stability, and manufacturability. This project...
This Project Grant award from 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), provides $198,646 to the Colorado School of Mines to advance machine learning-guided development of chaperone-mimetic polymeric carriers for delivering ribonucleoproteins (RNPs) for genome editing applications. The key goals are to: 1) Engineer chaperone-mimetic polymers that...
This $667,013 Project Grant award from the National Institute of Allergy and Infectious Diseases (NIAID), under the Allergy and Infectious Diseases Research program (CFDA 93.855), aims to leverage machine learning to predict antigen-antibody interactions from massive sequencing data. The key products and services to be delivered under this 5-year grant include: Developing and validating deep learning models to accurately identify antibody-antigen interactions and binding epitopes on antigens...
This Project Grant award from the National Institute of General Medical Sciences (NIGMS) Biomedical Research and Research Training Program (CFDA 93.859) will fund the development of machine learning and object detection technologies to enable automated evaluation of student-created physical protein models. The $591,842 award to 3D Molecular Designs LLC, a woman-owned small business, will be used to create two key applications: A student training app that will provide immediate augmented...
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $379,730 to the University of North Carolina at Chapel Hill to develop a continuous monitoring system for therapeutic monoclonal antibodies (mAbs) using an in situ regenerable aptamer sensor. The central aim is to create a technology that can continuously monitor patient-specific levels of the FDA-approved mAb bevacizumab, which is used to treat various cancer types. The research will...
This $285,577 project grant was awarded by the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859) to Ursa Analytics, Inc., a for-profit AI and data analytics company. The grant supports the development of new unsupervised machine learning algorithms for high-throughput, label-free image analysis of chimeric antigen receptor (CAR)-T cell data. The goal is to optimize manufacturing processes for producing consistent,...
This Project Grant award of $408,007 from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to develop a technology called "glycosequencing" that uses next-generation sequencing (NGS) to sequence and quantify glycan structures. The project will first identify an optimal set of lectins, biochemically characterize them, and prepare lectin barcoding for NGS. It will also build a training dataset using recombinant proteins produced in glycoengineered Chinese...
This $752,456 Project Grant award from the National Institute of General Medical Sciences (NIGMS) Biomedical Research and Research Training Program (CFDA 93.859) supports the development and application of innovative computational technologies for the design of small-molecule ligands. The key products and services to be delivered over the 5-year project period include: Creating a large database of predicted protein-ligand complexes to improve the accuracy of structure-based machine learning...
This $275,956 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of an engineered cyber-physical system that combines advanced biological models with artificial intelligence methods. The goal is to create a platform capable of accurately predicting patient responses to anti-cancer therapies, enabling real-time precision medicine. Key innovations include the use of 3D...