Grant List
Represents Grant table in the DB
GET /v1/grants?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=1424&sort=program_officials", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=program_officials", "prev": null }, "data": [ { "type": "Grant", "id": "2977", "attributes": { "award_id": "1919614", "title": "RCN-UBE Incubator: Creating a Multi-Institution and -Disciplinary STEM Network to Improve Undergraduate Biology Education", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "UBE - Undergraduate Biology Ed" ], "program_reference_codes": [], "program_officials": [], "start_date": "2019-08-01", "end_date": "2021-07-31", "award_amount": 74327, "principal_investigator": { "id": 9086, "first_name": "Alison", "last_name": "Hyslop", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1004, "ror": "", "name": "Saint John's University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 9082, "first_name": "Lawrence J", "last_name": "Hobbie", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 9083, "first_name": "Michael J", "last_name": "Pullin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 9084, "first_name": "Jessica", "last_name": "Santangelo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 9085, "first_name": "Jacqueline", "last_name": "Lee", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1004, "ror": "", "name": "Saint John's University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "The Sustainable, Transformative Engagement across a Multi-Institution/Multidisciplinary STEM, (STEM)^2 (\"STEM-squared\"), Network will be a regional group that aims to increase the academic success of biology majors including those who transition from community colleges to four-year institutions. The (STEM)^2 Network will bridge the disciplines of biology, chemistry, and math, as well as the barriers that exist between the participating two- and four-year institutions. The multidisciplinary nature of the Network's approach will extend its impact beyond biology, while the inclusion of public two-year and private four-year schools will ensure that outcomes are applicable across institution types. The network will be unique among the organizations that exist to support STEM education reform because 1) the focus will be on identifying areas for interdisciplinary curricular and educational collaborations; and 2) the multilevel approach will target individual classroom behaviors, curricular collaboration across disciplines, and institutionalization of innovations. As such, it will empower faculty to be change agents for STEM reform, creating new directions in research and education. It is anticipated that student academic success and retention will increase which, in turn, will help meet the need for a larger and more diverse STEM workforce.\n\nThe (STEM)^2 Network will use a series of collaborative studio workshops to achieve the overarching goals of 1) promoting collaboration between regional public community colleges and four-year private institutions; 2) empowering faculty to create change beyond their classrooms; and 3) creating enduring pedagogical collaborations across STEM disciplines encountered by undergraduate biology majors. The theoretical foundations of the network include systems design for organizational change, an emergent outcomes model for diffusion of STEM innovations, and the principles underlying Communities of Transformation. Participants will align the guiding educational documents of the disciplines of biology, chemistry, and math to encourage cross-disciplinary collaboration. They will directly enhance undergraduate biology education by developing institutional systems maps to strategically identify opportunities for sustainable change. The (STEM)^2 Network will contribute to knowledge generation by documenting the development of the network from an industrial/organizational psychology perspective and assessment of interdisciplinary communication and collaboration, institutional structures, and faculty attitudes to catalyze change in undergraduate biology education. Co-funding for this project is being provided by the Improving Undergraduate STEM Education (IUSE: EHR) program in recognition of the project's alignment with the overarching goals of the IUSE: EHR program.\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": "15995", "attributes": { "award_id": "1IK2HX003695-01A2", "title": "Improving Specialty Care Through Virtual Care Models", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2026-01-01", "end_date": "2030-12-31", "award_amount": null, "principal_investigator": { "id": 44448, "first_name": "Rebecca", "last_name": "Tisdale", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3442, "ror": "", "name": "VETERANS ADMIN PALO ALTO HEALTH CARE SYS", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "1 Background: Specialty care deserts—the absence of specialists in geographic regions—have led to an access 2 crisis for the VA. In addition to increasing wait times and causing delays in care, these access needs drive many 3 Veterans to seek care outside VA, resulting in fragmented care, increased risks for hospitalization and hospital 4 readmission, and higher costs. In response, VA has launched the Clinical Resource Hub (CRH) program, which 5 seeks to deliver virtual care from “hub” to “spoke” sites in VA. VISN 21 has begun implementing this model in 6 cardiology at several spoke sites, but little is known about how care utilization and quality within the program. 7 Significance/Impact: This work seeks to better understand the effects of a virtual model of specialty care, in 8 this case cardiology care, on Veterans’ care access and quality. In addition, it aligns closely with several VA and 9 HSR&D priorities, chiefly access to care, virtual care/telehealth, and advancing the goals of the MISSION Act. 10 Innovation: The CRH program and the virtual care model at its core have yet to be studied in depth, and there 11 is no research in progress regarding specialty CRH despite strong interest at the national VA level in 12 understanding how specialty CRH is used and associated outcomes. Given that virtual cardiology care was very 13 limited prior to the COVID-19 pandemic, cardiology CRH is particularly novel. Hence, this project would add to 14 the limited body of research examining virtual cardiology care in the VA. In addition, the proposed work seeks to 15 evaluate this virtual care model at a time of unprecedented choice for Veterans between in-person and virtual 16 care, and limited data on how best to integrate these modalities. 17 Specific Aims: The proposed CDA will offer mentorship and training for me to pursue the following aims: 18 Aim 1. Evaluate quality of cardiology care associated with CRH implementation with administrative data. 19 I will use adjusted difference-in-difference event studies to compare cardiology quality metric achievement for 20 patients who received cardiology care via CRH versus those who received conventional VA-based cardiology care. 21 Aim 2. Assess Veteran perceptions of quality of cardiology care delivered via CRH. 22 I will interview Veterans participating in the CRH program and their caregivers regarding their experiences and 23 perceptions of quality of CRH cardiology care and elicit suggestions for key metrics to focus on for improvement. 24 Aim 3. Construct intervention to track and improve access to high-quality, equitable care through CRH. 25 Building on finding from Aims 1 and 2, I will interview clinicians and employ a facilitated deliberative process with 26 an expert advisory group to construct and pilot an intervention to improve quality. 27 Methodology: In Aim 1, I will use a difference-in-difference event study design to assess the impact of the program 28 on a battery of validated and/or guideline-based quality of cardiology care metrics. In Aim 2, guided by the Fortney 29 model of care access and quality, I will conduct semi-structured interviews of Veterans and caregivers receiving 30 care through the VISN 21 CRH program to understand their experiences with the CRH program and what outcomes 31 they recommend to include in a quality improvement intervention. In Aim 3, I will interview clinicians (Aim 3.1) and 32 conduct a facilitated deliberation process (Aim 3.2) to inform the construction of an intervention (proactive panel 33 management using a clinical dashboard tool) to track and improve quality of care and pilot the intervention. 34 Next Steps/Implementation: To continue moving this research into practice to improve health outcomes for 35 Veterans, I will extend the analysis of cardiology quality of care to compare cardiology care in the community to 36 CRH care. In addition, I will assess the effect of the intervention constructed in Aim 3 on patient outcomes and 37 clinician satisfaction via a hybrid implementation-effectiveness trial. I will continue to work with operational partners 38 to ensure cardiology CRH is improving access to high-quality cardiology care for Veterans. This project supports 39 my goal of becoming an independent VA health services researcher and leader in optimizing cardiovascular 40 disease care access, value, and equity for Veterans through virtual care innovations and implementation.", "keywords": [ "Achievement", "Address", "Area", "COVID-19 pandemic", "California", "Cardiology", "Cardiovascular Diseases", "Cardiovascular system", "Caregivers", "Caring", "Characteristics", "Cladribine", "Clinical", "Clinical Services", "Communities", "Community Health Care", "Dangerousness", "Data", "Disease", "Ensure", "Equity", "Evaluation", "Event", "Geographic Locations", "Goals", "Guidelines", "Health", "Health Services", "Health Services Accessibility", "Heart failure", "Homogeneously Staining Region", "Hospitalization", "Hospitals", "Improve Access", "Intervention", "Interview", "Medical", "Mentors", "Mentorship", "Methodology", "Methods", "Modality", "Modeling", "Morbidity - disease rate", "Nevada", "Outcome", "Pacific Islands", "Patient-Focused Outcomes", "Patients", "Perception", "Persons", "Physicians", "Policies", "Positioning Attribute", "Process", "Qualitative Methods", "Quality of Care", "Recommendation", "Research", "Research Design", "Research Personnel", "Resources", "Risk", "Rural Health", "Safety", "Site", "Specialist", "Structure", "Suggestion", "Telemedicine", "Telephone", "Testing", "Time", "Training", "Training Activity", "Veterans", "Visit", "Wait Time", "Work", "adverse outcome", "care fragmentation", "care seeking", "care utilization", "clinical implementation", "connected care", "cost", "dashboard", "design", "effectiveness/implementation trial", "experience", "follow-up", "health economics", "hospital readmission", "hospitalization rates", "implementation efforts", "implementation science", "improved", "innovation", "insight", "interest", "intervention effect", "medical specialties", "mortality", "novel", "operation", "patient subsets", "pilot test", "preference", "programs", "rapid growth", "research to practice", "response", "rural counties", "satisfaction", "sociodemographics", "southern nevada", "telehealth", "therapy design", "tool", "virtual", "virtual delivery", "virtual health care", "virtual model" ], "approved": true } }, { "type": "Grant", "id": "10495", "attributes": { "award_id": "75N93022C00047-0-9999-1", "title": "REAL-TIME SURVEILLANCE OF VACCINE MISINFORMATION FROM SOCIAL MEDIA PLATFORMS", "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": "2022-08-08", "end_date": "2023-08-07", "award_amount": 300000, "principal_investigator": { "id": 26502, "first_name": "JINGCHENG", "last_name": "DU", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1763, "ror": "", "name": "MELAX TECHNOLOGIES, INC.", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "To develop digital tools to identify and combat malicious digital bots that spread misinformation about infectious disease treatments and vaccines, including COVID-19 vaccines.", "keywords": [ "Basic Science", "COVID-19 vaccine", "Coronavirus", "Misinformation", "Severe Acute Respiratory Syndrome", "Time", "Vaccines", "combat", "digital", "infectious disease treatment", "social media", "tool" ], "approved": true } }, { "type": "Grant", "id": "10511", "attributes": { "award_id": "1U01CK000671-01", "title": "Midwest Virtual Laboratory of Pathogen Transmission in Healthcare Settings (MVL-PATHS)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2025-09-29", "award_amount": 299761, "principal_investigator": { "id": 26517, "first_name": "Majid", "last_name": "Bani Yaghoub", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 753, "ror": "", "name": "UNIVERSITY OF MISSOURI KANSAS CITY", "address": "", "city": "", "state": "MO", "zip": "", "country": "United States", "approved": true }, "abstract": "Midwest Virtual Laboratory of Pathogen Transmission in Healthcare Settings (MVL-PATHS) Project Summary Antimicrobial Resistant (AMR) pathogens have become a significant public health threat. Also, the COVID-19 pandemic has further revealed disparities in healthcare settings. By developing and implementing novel mathematical and computation models, the long-term goals are to optimize AMR control and preventive interventions and to improve the health equity. The central hypothesis is that the outputs of mathematical and computation models will provide optimized and effective guidelines to reduce the threat of AMR pathogen spread and reduce health disparities in healthcare settings. The rationale underlying this project is to fill the critical gap in modeling workforce capacity and develop a new generation of mathematical models for healthcare research. The central hypothesis will be tested by pursuing three specific aims to develop and employ a, (i) One Health modeling approach to understand the source, distribution and spread of AMR Enterobacteriaceae with a focus on Extended- spectrum beta-lactamase (ESBL)-producing E. coli, (ii) a novel Real-Time modeling approach to identify AMR pathogen transmission by asymptomatic spreaders and contaminated medical devices in hospitals, (iii) a novel Agent-Based Nested modeling approach to identify the effects of caregivers as vectors of disease spread, and effects of limited staffing and specialized care on equitable quality of care in nursing homes. We will pursue these aims using an innovative combination of mathematical and computational modeling techniques. These include both recently developed techniques of including human behavior in models and more-established techniques that have been applied very little to the study of health equity and AMR pathogen spread. The workforce development objectives of this proposal are to (i) enhance mathematical and computational modeling research capabilities of the public health workforce and (ii) increase the number of junior modeling professionals that are trained and experienced in modeling transmission of pathogens in healthcare settings partly incorporated with health disparities. The expected outcomes of this work are the successful training of five predoctoral fellows and creating a virtual laboratory of enhanced mathematical models to identify strategies for reducing the threat AMR pathogen spread and reducing health disparities. The results will have an important positive impact immediately because the virtual laboratory can also be used by healthcare professionals to further investigate the drivers of disease spread and estimate the relative benefits of multiple control and prevention strategies in a timely and cost-effective manner. In addition, the research outputs of this project will expand and strengthen national one-health efforts to combat resistance and will have a direct impact on CDC and its public health partners’ ability to reduce the costs, morbidity and mortality of healthcare associated infections.", "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": "10519", "attributes": { "award_id": "1R43IP001195-01", "title": "mRNA-BASED VACCINE AGAINST MULTIPLE COVID-19 VARIANTS", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2023-09-29", "award_amount": 252010, "principal_investigator": { "id": 26528, "first_name": "Mohammed", "last_name": "Bouziane", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1937, "ror": "", "name": "SUNOMIX THERAPEUTICS", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Over the last 25 months humanity has been confronting COVID-19 pandemic caused by the new Corona Virus 2 (SARS-CoV-2) infection. Mutations and deletions often occur in the genome of SARS-CoV-2 (predominantly in the Spike protein) resulting in more transmissible and pathogenic “variants of concern” (VOCs). Our long- term goal is to develop a potent COVID-19 vaccine to stop/reduce SARS-CoV-2 infections and/or COVID-19 disease caused by multiple VOCs. Major gaps: Out of the 50 mutations that occur in the genome of OMICRON variant, 32 mutations are concentrated in the Spike protein sequence alone. Because most mutation and deletion that produced the 20 known VOCs are mostly concentrated on the Spike protein sequence, there is a risk that some of current COVID-19 sub-unit vaccines, that used mainly the Spike protein as antigen, fail to protect against future VOCs despite inducing strong virus-specific neutralizing antibodies. This emphasizes two major gaps in knowledge: The need to design alternative second-generation coronaviruses vaccines that (1) will include non- structural epitopes and antigens (Ags), other than the Spike protein; and (2) will incorporate conserved B and T cell epitopes to induce cell-mediated immune responses (in addition to humoral responses). Preliminary Results: We: (1) Identified potential human T cell target epitopes (the part of a virus antigens that the immune system recognizes) from the whole SARS-CoV-2 genome; and (2) Produced a first prototype multi-epitope COVID-mRNA vaccine candidate using the scalable and proven mRNAs vaccine platform, and (3) Generated a novel “humanized” susceptible HLA-DR/HLA-A*0201/hACE2 triple transgenic mouse model in which to test additional COVID-mRNA-based vaccine candidates. We hypothesize that one of our 5 COVID-19 vaccine candidates will protect “humanized” mice from infection and COVID-like disease caused by intranasal inoculation with SARS-CoV-2 a, b, g, d and Omicron VOCs. Our Specific Aims are: Aim 1: To construct 5 additional multi- epitopes COVID-mRNA-based vaccine candidates, that will incorporate conserved B and T cell epitopes from SARS-CoV-2 VOCs that circulate in the United Sates and other 200 other countries. Aim 2: To test in our novel “humanized” mouse model the safety, immunogenicity, and protective efficacy against SARS-CoV-2 a, b, g, d or Omicron VOCs of 5 multi-epitope COVID-mRNA vaccine candidates, delivered intranasally. The durability of protection and its correlation with blocking/neutralizing antibodies and the number and function of tissue-resident SARS-CoV-2-specific CD4+ and CD8+ TRM cells in the lungs and brains will be determined. If successful, the lead vaccine that protects against most VOCs, will be tested in non-human primate for safety (SBIR Phase II) and subsequently could be moved quickly into an FDA Phase 1 clinical trial.", "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": "10583", "attributes": { "award_id": "1U01CK000675-01", "title": "TRANSMIT: Training Research Acumen iN Students Modeling Infectious Threats", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2025-09-29", "award_amount": 297120, "principal_investigator": { "id": 26605, "first_name": "Frederick R.", "last_name": "Adler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26606, "first_name": "Lindsay T.", "last_name": "Keegan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26607, "first_name": "DAMON", "last_name": "TOTH", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26608, "first_name": "YUE", "last_name": "ZHANG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 202, "ror": "https://ror.org/03r0ha626", "name": "University of Utah", "address": "", "city": "", "state": "UT", "zip": "", "country": "United States", "approved": true }, "abstract": "The ongoing COVID-19 pandemic has overwhelmed healthcare and public health systems, underscoring the need to anticipate disease outbreaks and prepare resources such as hospital beds and staff. One cost-effective and timely way to prepare resources to respond to these outbreaks is through the use of mathematical modeling. Models can act as a virtual laboratory to explore a variety of scenarios, interventions, or applications in a timely manner to inform policy interventions. While the COVID-19 pandemic highlighted the gaps that models can fill, it also highlighted a considerable gap in modeling: there is a lack of modeling professionals trained in developing and applying transmission models to healthcare settings. In this proposal, we detail three projects aimed to train three predoctoral fellows in different aspects of mathematical modeling of healthcare associated pathogens. These projects tackle different pathogens and components of disease transmission in a healthcare setting; and, while each project is distinct, they dovetail nicely, resulting in a cohesive research program. Project 1 tackles a critical component of disease transmission in healthcare settings: COVID-19 in long-term care facilities (LTCFs). Throughout the pandemic, LTCFs bore a disproportionate burden of mortality. Yet, while it is clear that LTCFs important with regards to disease outcomes, whether or not they exert selective forces on SARS-CoV-2 that have shaped global patterns of pathogen evolution is not yet known. Here, we will develop models to quantify the phylogenetic relationships between community and long-term care facility lineages to understand the viral diversification attributable to healthcare settings. Project 2 explores the risk factors of patients hospitalized with SARS-CoV-2 for acquiring multi-drug resistant organisms (MDROs). The rapid spread of SARS-CoV-2 has changed to hospital infection control and antimicrobial stewardship policies. One such change has been widespread potentially unnecessary antibiotic use among hospitalized patients. Here, we will identify the characteristics of the sub-population disproportionately impacted by co-infections with MDROs for patients hospitalized with SARS- CoV-2. Project 3 integrates with both Project 1 and 2, to explore the evolution of antibiotic resistance due to variable dose and off-target antibiotic use in healthcare settings. Patients in hospitals and residents of LTCFs are exposed to a wide range of pathogens and treatments, and many of these organisms have themselves been exposed to a wide range of environmental antibiotics. Here, we will develop models of evolution to investigate the conditions that lead to the most intractable infections.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10479", "attributes": { "award_id": "272201600013C-P00026-9999-16", "title": "MICROBIOLOGY AND INFECTIOUS DISEASES BIOLOGICAL RESEARCH REPOSITORY (MID BRR) - SARS-CoV-2 THERAPEUTICS RESEARCH RELATED ACTIVITIES", "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": "2022-05-05", "end_date": "2023-05-04", "award_amount": 2924707, "principal_investigator": { "id": 24837, "first_name": "TIMOTHY", "last_name": "STEDMAN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1788, "ror": "https://ror.org/03thhhv76", "name": "American Type Culture Collection", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1788, "ror": "https://ror.org/03thhhv76", "name": "American Type Culture Collection", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "This contract provides unique and quality-assured infectious reagents and resources to the scientific community for use in basic research and product development. The scope of this contract includes the acquisition, authentication, production, preservation, storage, and distribution of research and reference reagents to the research community. These reagents span the pathogens in the Division of Microbiology and Infectious Diseases portfolio, and include the National Institutes of Allergy and Infectious Disease (NIAID) Category A, B and C Priority Pathogens and emerging infectious diseases.", "keywords": [ "2019-nCoV", "Basic Science", "COVID-19", "COVID-19 therapeutics", "Categories", "Communicable Diseases", "Communities", "Contracts", "Emerging Communicable Diseases", "Microbiology", "National Institute of Allergy and Infectious Disease", "Production", "Reagent", "Research", "Resources", "Therapeutic Human Experimentation", "biological research", "pathogen", "preservation", "priority pathogen", "product development", "repository", "research and development" ], "approved": true } }, { "type": "Grant", "id": "10575", "attributes": { "award_id": "1R43GH002389-01A1", "title": "Rapid COVID-19 Mutation Discrimination Test for Global SARS-CoV-2 Variant Surveillance", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2023-03-31", "award_amount": 275766, "principal_investigator": { "id": 26597, "first_name": "Janet L", "last_name": "Huie", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1947, "ror": "", "name": "JAN BIOTECH, INC.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Public Health Problem. Covid-19 variant tracking and prevalence is greatly hindered by the lack of quick, high- throughput methods for variant detection. Covid-19 genetic variants are a current and ongoing concern, due to greater transmissibility, morbidity and potential resistance to immunity provided by vaccines. Successful surveillance will likely require full coverage: 100% of people tested (not an extrapolation of sparse or region- specific data). Jan Biotech’s proposed assay quickly detects both known variants and new variants (by detecting unknown sequences through negative results and indicating the need for sequencing) and the probes are easily adapted to detect newly emerging variants of concern and interest. The assay will allow remote and low resource area hospitals and medical centers to quickly and fully assess their community’s SARS-CoV-2 variant index for real-time, evidence-based health mandates. This is both an urgent and very likely a long term need as new variants emerge. Issues with Current Solutions & How Product Meets Unmet Needs. RT-PCR Covid-19 tests provide only a positive or negative result and do not identify genetic variants. Rapid antibody tests for Covid-19 also do not reveal variants. DNA Sequencing of the Covid-19 genome is challenging. The genome is almost 30,000 nucleotides in length and combinations of mutations in different areas of the genome are functional and identifying features of Covid-19 variants. High-throughput RNAseq methods for next-generation sequencing (NGS) require RNA purification, RT-PCR RNAseq library preparation and time-consumptive sequencing and genome assembly. Covid-19 sequencing in any format for identification of variants has not yet been CLIA- or FDA-approved. RT-qPCR assays mined for variant data rely on altered Ct curves, which are nonspecific and can be caused by variations in the assay run. The proposed rapid Covid-19 variant detection and discrimination test, performed in a multiwell plate, is variant-specific and high-throughput. Summary of Approach. We will create RNAamp oligonucleotide-templated photoreduction probe sets specific to the current most prevalent and clinically-significant Covid-19 RNA variants. We will multiplex the Covid-19 variant discrimination RNAamp tests, using different profluorophores for each target and evaluate sensitivity and reliability of multiplex results using negative human saliva samples spiked with multiple Covid-19 variant RNAs. Human samples will be used to assess commercial potential of the multiplexed Covid-19 variant RNAamp test. Covid-19 negative samples will serve as negative controls and the same negative samples spiked with Covid- 19 variant control RNAs will serve as positive controls for each variant test to achieve a statistical correlation of >0.9 with comparison assays as the metric of success. Collaborators and Unique Resources. Jan Biotech, Inc., with expertise in molecular diagnostic development, will obtain human Covid-19 positive and negative test samples from the University of Rochester Medical Center, and, as needed, from Precision for Medicine and BocaBiolistics. Specific Aims Specific Aim 1: Develop multiplexed variant discrimination RNAamp test for Covid-19 strain detection Objective 1.1: Develop and test RNAamp probe sets to differentiate Covid-19 variants of concern. Objective 1.2: Multiplex and test the Covid-19 variant discrimination RNAamp tests. Specific Aim 2: Evaluate variant discrimination RNAamp test on Covid-19 human samples Objective 2.1: Test human samples to assess commercial potential of multiplexed Covid-19 variant RNAamp. Objective 2.2: Statistical determination of assay limit of detection and specificity for each Covid-19 variant will evaluate the utility of the rapid Covid-19 variant discrimination test, including its application to pooled samples. The end result of the project will be a multiplexed Covid-19 variant discrimination test and computational software providing proof-of-concept for Phase II preclinical and clinical evaluation leading towards CLIA or 510(k) approval, clinical trials and commercialization.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1, "pages": 1424, "count": 14236 } } }