Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1392&sort=-program_officials
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-program_officials", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1405&sort=-program_officials", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1393&sort=-program_officials", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1391&sort=-program_officials" }, "data": [ { "type": "Grant", "id": "10404", "attributes": { "award_id": "2223678", "title": "EFRI ELiS: Living Microbial Sensors for Real-Time Monitoring of Pathogens in Wastewater", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "EFRI Research Projects" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-01-01", "end_date": "2026-12-31", "award_amount": 1999271, "principal_investigator": null, "other_investigators": [], "awardee_organization": { "id": 357, "ror": "", "name": "William Marsh Rice University", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "SARS-CoV-2 is the virus that causes COVID. It can be detected in wastewater. Its detection can act as a signal to a community that the infection is spreading locally. The goal of this project is to develop living sensors that can continuously monitor wastewater for the presence of SARS-CoV-2. Living microbial sensors are robust and low-cost. They can regenerate themselves and can be engineered to detect a specific biomolecular target of interest. The modular design can be easily repurposed to detect and monitor a variety of chemical and biological targets in the environment. Training undergraduate, graduate, and postdoctoral researchers will advance the development of a competitive bioeconomy workforce. The project will also establish new K-12 outreach programs in collaboration with Houston-area public schools. Enhancing current programs that offer research opportunities to community college students and K-12 teachers is another objective. Engaging the public and relevant stakeholders to address ethical, legal, and social implications of living microbial devices is another important aspect of this project.\n\nDevelopment and deployment of living microbial sensors is the overall objective of this project. These sensors will be based on engineered electroactive microorganisms. Addressing broader societal challenges related to the potential adoption of engineered microbial devices, including safety, legal, and regulatory concerns is another important aspect of the project. Several fundamental science and engineering challenges must be met to make such devices. Establishing methods for engineering microbes that can directly detect large macromolecules, such as the SARS-CoV-2 spike protein is one. Developing scalable methods for processing engineered microorganisms into functional biohybrid materials is another. Designing compact and low power devices that can amplify electronic signals delivered by the electroactive microbes is a third. Ultimately, evaluating the stability and performance of these devices in different environmental settings, including wastewater, will be critical to establishing the efficacy of these devices The project team will also identify and conduct in-person semi-structured interviews with vested stakeholders such as regulators, public health experts, infectious disease specialists, and environmental advocates. The interviews will identify major public concerns and regulation that could impede implementing the proposed bioelectronic technology. Altogether, this work will provide a solid foundation and analysis for understanding, developing, and translating living microbial sensors as real-time and low-cost environmental sensors.\n\nThis project is jointly sponsored by the National Science Foundation, Office of Emerging Frontiers and Multidisciplinary Activities (EFMA) and the Department of Defense – Defense Threat Reduction Agency (DTRA).\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10405", "attributes": { "award_id": "2229267", "title": "FMSG: Eco: Off-Grid Construction via Sustainable Compression Curing of Vegetable Oil-Impregnated Sediments", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "FM-Future Manufacturing" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-10-01", "end_date": "2024-09-30", "award_amount": 494685, "principal_investigator": null, "other_investigators": [], "awardee_organization": { "id": 197, "ror": "https://ror.org/05p1j8758", "name": "Kansas State University", "address": "", "city": "", "state": "KS", "zip": "", "country": "United States", "approved": true }, "abstract": "Additive manufacturing (AM) has effectively revolutionized how engineers and architects design and fabricate products due to its layer-by-layer building approach. New levels of product complexity/customization not offered by traditional manufacturing processes are now achievable, resulting in weight reduction, enhanced conformability, joint consolidation, and higher efficiencies through design. This project combines faculty in engineering, chemistry, architecture, and geology to innovate a solar-powered compression/curing technique that additively fabricates building materials made of tung oil and local sands for sustainable, raw-earth construction. This manufacturing method can leverage available natural resources within the U.S., therefore reducing any reliance on international raw materials. It also responds to a growing need to innovate and overcome remote construction constraints exacerbated by urban-to-rural migration driven by the COVID pandemic and climate change. The remote AM of raw earth materials will help reduce the large carbon footprint associated with concrete-based AM construction which relies on heavy gantry-based material extrusion systems that must be transported to worksites. Architecture students will be trained on a commercial binder-jet AM system for integrating new knowledge in sustainable AM processes into their designs. Guest lectures will be provided to engineering and architecture undergraduate students to broaden their perspectives and creativity to ensure future innovation in the U.S. advanced manufacturing industries.\n\nThe goal of this fundamental manufacturing research project is to design and test a new binder/powder-based AM process for the fabrication of earth-sourced composites for structural applications. Through modeling and experimentation, the AM process will be designed for off-grid use while remaining completely sustainable. Tung oil will be employed for binding sands of highly variable sizes, shapes, and chemistry. Employed sands will be characterized using microscopy and flowability measurements. These measurements will be correlated with the sediment’s ability to spread into a thin layer with minimal voids when acted upon by a custom-designed roller. Binder rheological properties will be varied until effective jetting and sediment infiltration are realized. The binder will be cured via free radical polymerization triggered by a combination of heat and ultraviolet (UV) radiation. The latent heat required for uniform binder curing in the presence of unrefined sediments will be related with concentrated solar energy/spectra for aiding the design of a solar power/heating unit. First order energy balances and entropy minimization will guide power/heating unit design. A proof-of-concept manufacturing system will be constructed and instrumented for conducting “brick” building experiments. Thermomechanical tests will be performed to determine the strength of these manufactured composite bricks.\n\nThis project is jointly funded by the Division of Civil, Mechanical, and Manufacturing Innovation and the Established Program to Stimulate Competitive Research (EPSCoR).\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10406", "attributes": { "award_id": "2141473", "title": "EAGER: Compact Field Portable Biophotonics Instrument for Real-Time Automated Analysis and Identification of Blood Cells Impact Impacted by COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "EPMD-ElectrnPhoton&MagnDevices" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": "2024-08-31", "award_amount": 220000, "principal_investigator": null, "other_investigators": [], "awardee_organization": { "id": 257, "ror": "https://ror.org/02der9h97", "name": "University of Connecticut", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "COVID-19 pandemic quickly overwhelmed the healthcare resources in even advanced economies with large scale global fatalities not seen since the Spanish Flu of 1918. This project intends to investigate the impact of the COVID-19 virus on human red blood cells using an automated low-cost, field portable bio-photonics instrument. These studies can lead to better understanding of the impacted blood cells and precise measurement of cell anomalies for potential early detection of COVID-19. Accurate, rapid, and low-cost analysis and diagnosis of COVID-19 from blood cells with a compact field portable bio-photonics instrument interfaced with mobile devices will be a substantial advance toward widespread testing, medical diagnosis, early detection, disease prevention, and relevant data collection, particularly in remote areas without access to dedicated healthcare facilities. The proposed cross disciplinary project is based on a transformative biophotonics sensing approach for real-time analysis and disease detection and offers an alternative to conventional labor- and resource- intensive bio-molecular approaches. This analysis and capability would enable medical researchers to study and gain increased understanding of the effects of COVID-19 infections on blood cells. The proposed approach may provide a fast and reliable testing mechanism with the potential for widespread deployment, which is critical in dealing with pandemics, such as COVID-19, with high rates of infection and mortality. The success of the proposed approach would allow for automated low cost, rapid and highly accurate assessment of the impact of COVID-19 on blood cells, which is not currently possible using conventional methods. The proposed research provides new capabilities and benefits including real-time sensing and diagnosis; early detection with high accuracy, specificity, and sensitivity, and low cost field portable deployment in under resourced healthcare systems for real-time monitoring of pandemics.\n\n\nInvestigating the impact of COVID-19 on blood cells and making detailed real-time measurements of the COVID-19 induced changes and anomalies of the blood cells at sub-micron scales would provide valuable research insights to fight COVID-19 and future pandemics. The proposed approach employs computational multi-dimensional sensing and imaging at sub-micron scales to analyze morphology and motility of blood cells. Specially embedded algorithms are integrated with mobile devices to analyze opto-biological signatures of blood cells in real time to find potential clues to the impact and presence of COVID-19 for rapid (real-time) COVID analysis and detection. The measurements and analysis of the infected cells will be performed at sub-micron scale lateral resolution and nano scale longitudinal resolution. The proposed project investigates blood cells morphology and temporal motility quantitatively with high precision using high resolution self-referencing digital holographic in compact 3D-printed platforms. Multidimensional bio-optical signature data, including spatial structure, refractive index, stiffness, and dynamic temporal behavior of the blood cells will be investigated to understand the influence of COVID-19 in blood cells. The use of dedicated machine learning algorithms associated with the analysis of anomalies in blood cells due to COVID-19 are intended to produce accurate detection and analysis.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10407", "attributes": { "award_id": "2133205", "title": "Collaborative Research: Optimized Testing Strategies for Fighting Pandemics: Fundamental Limits and Efficient Algorithms", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "CCSS-Comms Circuits & Sens Sys" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": "2025-08-31", "award_amount": 225000, "principal_investigator": { "id": 4638, "first_name": "Weiyu", "last_name": "Xu", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 220, "ror": "https://ror.org/036jqmy94", "name": "University of Iowa", "address": "", "city": "", "state": "IA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 220, "ror": "https://ror.org/036jqmy94", "name": "University of Iowa", "address": "", "city": "", "state": "IA", "zip": "", "country": "United States", "approved": true }, "abstract": "Large-scale high-throughput prevalence and diagnostic testing is essential for the containment and mitigation of pandemics. The testing bottleneck in the COVID-19 pandemic has led to a resurgence of interest in group testing, where several people's biological samples are mixed together and examined in a single test. When the rate of infection in the population is low, this method can significantly reduce the total number of tests per subject and increase the throughput of the existing testing infrastructure. However, traditional group testing has the following limitations: First, efficient group testing based methods for the estimation of prevalence have been largely overlooked in the literature. Second, traditional group testing usually assumes that the testing results are qualitative (positive versus negative), not quantitative (providing viral load information). Third, the theoretical study of group testing rarely takes practical constraints, such as the sensitivity of the pooled tests and the dilution effect, into consideration, which hinders the applicability of the testing schemes in practice. The goal of this project is to overcome these limitations of traditional group testing and design advanced pooled testing strategies for efficient prevalence tracking and accurate infection diagnosis. It will develop optimized pooled testing strategies with strong theoretical performance guarantees yet feasible and cost-effective in practice.\n\nThe proposed research is organized in three research thrusts as follows. Thrust 1 aims to design effective sampling and testing algorithms to estimate the prevalence in communities and track its evolution, under scarce testing resource constraints. Thrust 2 focuses on the design of optimized pooling and decoding algorithms for compressed sensing based (COVID-19) virus diagnostic testing. Thrust 3 validates the accuracy and efficiency of the proposed pooled testing through experiments on anonymized COVID-19 samples. This project bridges group testing and online learning, the two largely disconnected areas, with the objective to effectively allocate limited testing resources for efficient prevalence tracking. Such integration leads to novel sampling strategies, broadens the paradigm of group testing, and advances the state of the art of online learning. Moreover, the proposed compressed sensing based diagnostic testing leverages quantitative measurements provided by advanced testing technologies, which can significantly increase test throughput, reduce the number of needed tests, decrease the consumption of scarce reagents, and provide results robust against observation noises and outliers. The rich compressed sensing theory provides possible approaches to the rigorous mathematical certification of the correctness of the decoded results. Besides, the clinical constraints on pooled testing also lead to novel problem formulation and theoretical characterization, enriching the study of compressed sensing.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10408", "attributes": { "award_id": "2133170", "title": "Collaborative Research: Optimized Testing Strategies for Fighting Pandemics: Fundamental Limits and Efficient Algorithms", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "CCSS-Comms Circuits & Sens Sys" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": "2025-08-31", "award_amount": 274774, "principal_investigator": null, "other_investigators": [], "awardee_organization": { "id": 219, "ror": "", "name": "Pennsylvania State Univ University Park", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Large-scale high-throughput prevalence and diagnostic testing is essential for the containment and mitigation of pandemics. The testing bottleneck in the COVID-19 pandemic has led to a resurgence of interest in group testing, where several people's biological samples are mixed together and examined in a single test. When the rate of infection in the population is low, this method can significantly reduce the total number of tests per subject and increase the throughput of the existing testing infrastructure. However, traditional group testing has the following limitations: First, efficient group testing based methods for the estimation of prevalence have been largely overlooked in the literature. Second, traditional group testing usually assumes that the testing results are qualitative (positive versus negative), not quantitative (providing viral load information). Third, the theoretical study of group testing rarely takes practical constraints, such as the sensitivity of the pooled tests and the dilution effect, into consideration, which hinders the applicability of the testing schemes in practice. The goal of this project is to overcome these limitations of traditional group testing and design advanced pooled testing strategies for efficient prevalence tracking and accurate infection diagnosis. It will develop optimized pooled testing strategies with strong theoretical performance guarantees yet feasible and cost-effective in practice.\n\nThe proposed research is organized in three research thrusts as follows. Thrust 1 aims to design effective sampling and testing algorithms to estimate the prevalence in communities and track its evolution, under scarce testing resource constraints. Thrust 2 focuses on the design of optimized pooling and decoding algorithms for compressed sensing based (COVID-19) virus diagnostic testing. Thrust 3 validates the accuracy and efficiency of the proposed pooled testing through experiments on anonymized COVID-19 samples. This project bridges group testing and online learning, the two largely disconnected areas, with the objective to effectively allocate limited testing resources for efficient prevalence tracking. Such integration leads to novel sampling strategies, broadens the paradigm of group testing, and advances the state of the art of online learning. Moreover, the proposed compressed sensing based diagnostic testing leverages quantitative measurements provided by advanced testing technologies, which can significantly increase test throughput, reduce the number of needed tests, decrease the consumption of scarce reagents, and provide results robust against observation noises and outliers. The rich compressed sensing theory provides possible approaches to the rigorous mathematical certification of the correctness of the decoded results. Besides, the clinical constraints on pooled testing also lead to novel problem formulation and theoretical characterization, enriching the study of compressed sensing.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10415", "attributes": { "award_id": "1S06GM146122-01", "title": "Environmental Influences Driving Autoimmunity and Autoimmune Disease in Tribal Members", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-20", "end_date": "2026-07-31", "award_amount": 372113, "principal_investigator": { "id": 10936, "first_name": "JUDITH A", "last_name": "JAMES", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1109, "ror": "", "name": "UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR", "address": "", "city": "", "state": "OK", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1813, "ror": "https://ror.org/00p23dy23", "name": "Cherokee Nation", "address": "", "city": "", "state": "OK", "zip": "", "country": "United States", "approved": true }, "abstract": "OMRF Project Summary Rheumatic diseases, such as systemic lupus erythematosus (SLE, lupus), rheumatoid arthritis (RA), scleroderma and osteoarthritis, cause significant morbidity and early mortality in Native American populations. Through ongoing collaborative work between the Cherokee Nation and the Oklahoma Medical Research Foundation, we have found that classic autoantibody associations in rheumatic disease patients of other races are not diagnostic in NA populations, identified novel autoantibodies in tribal rheumatic disease patents and found that tribal patients and controls have unique cytokine signatures; all of which make rheumatic disease care in tribal members more challenging to diagnose in primary care clinics. Surprisingly, we found that Native American individuals without evidence of autoimmune rheumatic disease had the highest rate of autoantibody production (10.5%) of all races, primarily with lupus, systemic sclerosis or rheumatoid arthritis associated antibodies. Autoantibody production is associated with lower levels of 25(OH)D in these individuals. Anti- cardiolipin autoantibodies are also more frequent in NA rheumatic disease patients and controls. Some of the highest rates of infection, poor outcomes and deaths from COVID have occurred in tribal communities, and COVID induces autoantibodies in many otherwise healthy individuals, including anti- cardiolipin responses that associate with thrombosis and anti-cytokine responses that associate with poor disease outcomes. In studies from our group and others, many COVID patients with autoimmunity or autoimmune disease are having prolonged symptoms, which are reminiscent of rheumatic diseases, such as fatigue, arthralgias, myalgias, malaise, rashes, lung and heart involvement. Select environmental factors have strong associations with systemic autoimmune rheumatic diseases. This project will define the impact of environmental influences, such as viral infections (SARS-CoV-2, Epstein-Barr virus, Cytomegalovirus), viral reactivation (Epstein-Barr virus), vitamin D deficiency and smoking exposure, on the development of autoantibodies and autoimmune disease in tribal members. Using single cell mass cytometry time of flight (CyTOF) and single cell genomic sequencing partnered with antibody binding (CITE-seq), shared immune pathways contributing to loss of self-tolerance, autoantibody production and autoimmune rheumatic disease will be determined. Finally, through implementation of a telerheumatology, telementoring program focused on practice-centric, case-based learning, academic detailing, and patient enrollment to clinical research protocols rheumatology capacity within the Cherokee Nation Health System will be developed for current and future patients. The overall goals of this project are to identify and confirm environmental influences associated with autoantibody production, immune dysregulation and autoimmune rheumatic disease, as well as build lasting tribal-based infrastructure to provide ongoing rheumatic disease evaluation and treatment that aid earlier detection, decreased morbidity and improved outcomes in tribal patients.", "keywords": [ "2019-nCoV", "Academic Detailing", "Algorithms", "Antibodies", "Arthralgia", "Autoantibodies", "Autoimmune", "Autoimmune Diseases", "Autoimmunity", "Automobile Driving", "Binding", "COVID-19", "COVID-19 impact", "COVID-19 patient", "Caring", "Case Based Learning", "Cells", "Cellular Indexing of Transcriptomes and Epitopes by Sequencing", "Cessation of life", "Cherokee Indian", "Cherokee Nation Oklahoma", "Cities", "Clinic", "Clinical Research", "Clinical Research Protocols", "Cotinine", "Cytomegalovirus", "Cytometry", "Data", "Degenerative polyarthritis", "Development", "Diagnosis", "Disease Outcome", "Dissemination and Implementation", "Early Diagnosis", "Early Intervention", "Early treatment", "Enrollment", "Environmental Exposure", "Environmental Impact", "Environmental Risk Factor", "Epstein-Barr virus early antigen", "Evaluation", "Exanthema", "Fatigue", "Foundations", "Future", "Genomics", "Goals", "Grant", "Health", "Health system", "Heart", "Human Herpesvirus 4", "Immune", "Immune System Diseases", "Immunophenotyping", "Individual", "Infection", "Infrastructure", "Legal patent", "Long COVID", "Lung", "Lupus", "Malaise", "Measures", "Medical Research", "Mentors", "Methods", "Morbidity - disease rate", "Myalgia", "Native American Research Center for Health", "Native Americans", "Oklahoma", "Outcome", "Pathway interactions", "Patients", "Population", "Prevention", "Primary Health Care", "Production", "Provider", "Race", "Rheumatism", "Rheumatoid Arthritis", "Rheumatology", "Rivers", "SARS-CoV-2 infection", "Scleroderma", "Self Tolerance", "Symptoms", "Systemic Lupus Erythematosus", "Systemic Scleroderma", "Testing", "Thrombosis", "Time", "Vaccines", "Viral", "Virus Diseases", "Vitamin D Deficiency", "Work", "autoimmune rheumatologic disease", "base", "care providers", "coronavirus disease", "cytokine", "immunoregulation", "improved outcome", "infection rate", "mortality", "multiple omics", "novel", "participant enrollment", "programs", "proteogenomics", "response", "rheumatologist", "single-cell RNA sequencing", "smoking exposure", "systemic autoimmune disease", "tribal community", "tribal member" ], "approved": true } }, { "type": "Grant", "id": "10419", "attributes": { "award_id": "1P01AI165066-01", "title": "Development of broad nanovaccines targeting diverse coronavirus receptor-binding sites", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-22", "end_date": "2025-08-31", "award_amount": 1244471, "principal_investigator": { "id": 11662, "first_name": "Daniel", "last_name": "Kulp", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1141, "ror": "", "name": "WISTAR INSTITUTE", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1141, "ror": "", "name": "WISTAR INSTITUTE", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "The first project of our pan-CoV proposal is titled ‘Development of broad nanovaccines targeting diverse coronavirus receptor-binding sites’. Our team’s expertise will culminate in structurally guided coronavirus nanoparticle vaccines to broaden CoV vaccine protection. This proposal utilizes our novel platform to develop potent, RBS-focused nanoparticle vaccines to induce broad protection across CoV lineages, escape mutations and potential pandemic CoVs that are of concern. The project aims are: (1) Create a library of mutants that escape coronavirus immunity (2) Develop RBS-focused nanoparticle vaccines to induce broadly neutralizing antibodies to conserved sites using nucleic acid delivery and (3) Develop vaccine regimens to induce broad immunity and protection across diverse CoVs.", "keywords": [ "2019-nCoV", "Address", "Adjuvant", "Antibodies", "Antibody Repertoire", "Antibody Response", "Antigens", "Automobile Driving", "B-Lymphocytes", "Binding", "Binding Sites", "CD8-Positive T-Lymphocytes", "COVID-19 therapeutics", "COVID-19 vaccination", "COVID-19 vaccine", "Coronavirus", "Coronavirus Infections", "Cryoelectron Microscopy", "DNA", "DNA Vaccines", "Development", "Devices", "Disease Outbreaks", "Dose", "Electroporation", "Epitopes", "Escape Mutant", "FDA Emergency Use Authorization", "Frequencies", "Generations", "Genetic", "Genetic Recombination", "Human", "Immune Sera", "Immune response", "Immunity", "Immunization", "Immunization Programs", "Investigation", "Libraries", "Middle East Respiratory Syndrome Coronavirus", "Modeling", "Molecular", "Mutagenesis", "Mutate", "Mutation", "Nucleic Acids", "Phenotype", "Preclinical Testing", "Publishing", "Regimen", "Research Project Grants", "SARS coronavirus", "SARS-CoV-2 spike protein", "Site", "Technology", "Transgenic Animals", "Vaccine Clinical Trial", "Vaccines", "Variant", "Virus", "Widespread Disease", "animal data", "base", "betacoronavirus", "clinical translation", "combat", "coronavirus receptor", "coronavirus vaccine", "cross reactivity", "design", "experimental study", "human coronavirus", "immunogenicity", "interest", "lead candidate", "mutant", "nanoparticle", "nanoparticle delivery", "nanovaccine", "neutralizing antibody", "novel", "novel coronavirus", "nucleic acid delivery", "pandemic disease", "pathogenic virus", "plasmid DNA", "pre-clinical", "programs", "receptor", "receptor binding", "synergism", "universal coronavirus vaccine", "vaccine candidate", "vaccine development", "vaccinology" ], "approved": true } }, { "type": "Grant", "id": "10468", "attributes": { "award_id": "75N95021D00001-P00001-759502200002-1", "title": "STSS COVID-19 EMERGENCY RESPONSE SUPPORT", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Center for Advancing Translational Sciences (NCATS)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-01-01", "end_date": "2022-09-30", "award_amount": 3152000, "principal_investigator": { "id": 24128, "first_name": "SUHAS", "last_name": "SHARMA", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1701, "ror": "", "name": "AXLE INFORMATICS, LLC", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1701, "ror": "", "name": "AXLE INFORMATICS, LLC", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "National COVID-19 Cohort Collaborative (N3C): The National COVID-19 Cohort Collaborative (N3C) sponsors the NIH COVID-19 Data Enclave, https://covid.cd2h.org/, one of the largest data enclaves in the world supporting COVID-19 research. N3C is a partnership among the NCATS-supported Clinical and Translational Science Awards (CTSA) Program hubs, the National Center for Data to Health (CD2H), and the NIGMS-supported Institutional Development Award Networks for Clinical and Translational Research (IDeA-CTR), with overall stewardship by NCATS. The N3C program is essentially a medium sized business, consisting of thousands of researchers, requiring enterprise level information technology (IT) support as part of a virtual research organization (VRO). This contract is necessary to ensure that NCATS and N3C can continue to provide adequate support for a secure, collaborative, VRO. This contract allows for continued support of the VRO which supports all of the required information technology functions to support an environment of over 4,000 users, including cloud-based productivity tools, a service desk, commercial and open-source deployments of analytical tools for the community to use, and expansion of the data types available for analysis, such as imaging, viral variant genomic sequences, etc. The common need is to share a collaborative cloud environment capable of ingesting billions of data points and performing a variety of complex analyses against multimodal data types, ranging from pathology and radiology data, synthetic data, genomic information, electronic health records (EHRs) and a wide variety of others. All of this must be done while meeting the highest levels of security and privacy, given the sensitivity of some of the data types being collected and the importance of the work being done in the environment. This contract provides support for all of these enterprise IT efforts.", "keywords": [ "Area", "Award", "Businesses", "COVID-19", "COVID-19 patient", "Clinical Research", "Clinical and Translational Science Awards", "Collaborations", "Communities", "Complex Analysis", "Contracts", "Data", "Data Analyses", "Data Collection", "Data Science", "Data Set", "Development", "Electronic Health Record", "Emergency response", "Ensure", "Environment", "Genomics", "Health", "Image", "Informatics", "Information Technology", "Ingestion", "National Center for Advancing Translational Sciences", "National Institute of General Medical Sciences", "Pathology", "Privacy", "Productivity", "Pythons", "Radiology Specialty", "Research", "Research Personnel", "Risk Factors", "Scientist", "Secure", "Security", "Services", "Statistical Data Interpretation", "Translational Research", "United States", "United States National Institutes of Health", "Viral", "Visualization", "Work", "analytical tool", "cloud based", "cohort", "coronavirus disease", "data enclave", "data harmonization", "genetic variant", "meetings", "multimodal data", "open source", "open source tool", "programs", "protective factors", "tool", "virtual" ], "approved": true } }, { "type": "Grant", "id": "10469", "attributes": { "award_id": "5U01GH002319-02", "title": "GH21-004, COVID-19 and related public health threats in populations affected by crises: a multi-disciplinary, collaborative research programme", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-02-01", "end_date": "2026-09-29", "award_amount": 165000, "principal_investigator": { "id": 23683, "first_name": "Francesco", "last_name": "Checchi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1630, "ror": "", "name": "LONDON SCH/HYGIENE & TROPICAL MEDICINE", "address": "", "city": "", "state": "", "zip": "", "country": "UNITED KINGDOM", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1630, "ror": "", "name": "LONDON SCH/HYGIENE & TROPICAL MEDICINE", "address": "", "city": "", "state": "", "zip": "", "country": "UNITED KINGDOM", "approved": true }, "abstract": "/ abstract In response to the Centers for Disease Control and Prevention’s Notice of Funding Opportunity to conduct research among crisis-affected and displaced populations in the context of COVID-19, we hereby propose a five- year programme of research and capacity strengthening , focussed on four key crisis-affected countries (the Democratic Republic of Congo, Somalia, South Sudan and Sudan), but with flexibility to conduct data collection in new emergencies and other settings where existing collaborations facilitate this. We present below a set of activities and studies organised along three aims: Aim 1: Establish or strengthen country-based, locally-led, multi-disciplinary humanitarian public health research units in the four key countries. Aim 2: Explore novel cross-cutting methods based on community-led surveillance and data science methods . Aim 3: Generate thematic evidence on the direct and indirect impacts of COVID-19 and other emergent public health threats, as per the following scientific objectives: 1. Generate improved all-cause and cause-specific 2. Quantify of SARS-CoV-2 and other epidemic infections. 3. Explore changes to behaviours, improve monitoring of hygiene behaviours and evaluate mortality estimates. transmission hygiene alternative behaviour change interventions. 4. Quantify and describe COVID-19’s secondary impacts on 5. Quantify COVID-19’s impacts on care models. sexual and reproductive health . non-communicable disease burden and mental health and test novel These activities will be undertaken by a consortium of academic institutions (the London School of Hygiene and Tropical Medicine, London, UK; the Université Catholique de Bukavu, DRC; SIMAD University, Mogadishu, Somalia; Imperial College London) and (the Bridge Network Organisation, South Sudan; the Sudan Youth Peer Network and Adeela for Art and Culture, Sudan). Our partnership is committed to co- production principles and will adopt a decolonial approach to research and humanitarian action. Most team members are former humanitarian workers, and all conduct the majority or all of their research work in or on crisis-affected populations. civil society actors", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10470", "attributes": { "award_id": "75N95021D00029-0-759502200001-1", "title": "N3C TASK", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Center for Advancing Translational Sciences (NCATS)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-02-21", "end_date": "2022-05-24", "award_amount": 5000000, "principal_investigator": { "id": 26481, "first_name": "BRIAN", "last_name": "ZAVERTNIK", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1737, "ror": "", "name": "PALANTIR TECHNOLOGIES, INC.", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "National COVID-19 Cohort Collaborative (N3C): The National COVID-19 Cohort Collaborative (N3C) sponsors the NIH COVID-19 Data Enclave, https://covid.cd2h.org/, one of the largest data enclaves in the world supporting COVID-19 research. N3C is a partnership among the NCATS-supported Clinical and Translational Science Awards (CTSA) Program hubs, the National Center for Data to Health (CD2H), and the NIGMS-supported Institutional Development Award Networks for Clinical and Translational Research (IDeA-CTR), with overall stewardship by NCATS. The N3C Data Enclave is a secure platform storing harmonized clinical data provided by more than 60 contributing members. The Enclave hosts over 670 million clinical observations on over 6.8 million persons, including over 2.2 million COVID cases, amounting to more than 7.8 billion rows of data. To protect privacy, this data consists only of limited data sets, de-identified data sets, and synthetic data sets; there is no personally identifiable information kept in the Enclave. The Enclave resides in the NCATS Secure Scientific Platforms Environment. The Environment is a specialized cloud-based data aggregation and analytics enclave that can integrate, manage, secure, and analyze any kind of scientific data, and provide secure, controlled access to internal and external collaborators. Within the Environment, multiple NIH ICs, Federal agencies, and Federal task forces integrate, manage, secure, and analyze all types of scientific data using dedicated platforms, and, equally importantly, make that data available in specific and controlled collaborations with each other and with external collaborators.", "keywords": [ "Advisory Committees", "Award", "COVID-19", "Clinical", "Clinical Data", "Clinical Research", "Clinical and Translational Science Awards", "Collaborations", "Data", "Data Aggregation", "Data Analytics", "Data Set", "Development", "Environment", "Health", "National Center for Advancing Translational Sciences", "National Institute of General Medical Sciences", "Personally Identifiable Information", "Persons", "Privacy", "Research", "Secure", "Translational Research", "United States National Institutes of Health", "cloud based", "cohort", "coronavirus disease", "data de-identification", "data enclave", "member", "programs" ], "approved": true } } ], "meta": { "pagination": { "page": 1392, "pages": 1405, "count": 14046 } } }