Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=2&sort=-abstract
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-abstract", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=-abstract", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=-abstract", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-abstract" }, "data": [ { "type": "Grant", "id": "6519", "attributes": { "award_id": "3U19DE028717-02S3", "title": "The National Dental PBRN Administrative and Resource Center", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Dental and Craniofacial Research (NIDCR)" ], "program_reference_codes": [], "program_officials": [ { "id": 21850, "first_name": "LILLIAN", "last_name": "SHUM", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-06-07", "end_date": "2026-05-31", "award_amount": 106094, "principal_investigator": { "id": 21851, "first_name": "GREGG H", "last_name": "GILBERT", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 612, "ror": "https://ror.org/008s83205", "name": "University of Alabama at Birmingham", "address": "", "city": "", "state": "AL", "zip": "", "country": "United States", "approved": true }, "abstract": "“The project summary [for the Overall Component] is a succinct and accurate description of the proposed work… This section is limited to 30 lines of text… This application continues funding for “The National Dental PBRN”, a national collaborative of practices and organizations across the United States that engages practitioners in the excitement of discovery for the benefit of everyday clinical practice and patients. Consistent with specifications in the FOA itself, the Specific Aims will be to: (1) maximize efficiencies to conduct national oral health research studies in general and specialty dental practices on topics of importance to practitioners and their patients; (2) provide evidence useful in daily patient care; (3) facilitate the translation of research findings into clinical practice; (4) continue our work during the 2005-2019 funding period to demonstrate consistent growth and productivity by streamlining the implementation of clinical research across the network, facilitating practitioner and patient recruitment and retention, and developing public-private partnerships (to develop projects of interest to specific dental groups and specialties, practice types, special populations, and patient advocacy groups). The National Dental PBRN will accomplish these aims by building upon the many lessons learned from its highly-productive current national network. We aim to build on our experiences from these past 13 years using the same funding mechanism and administrative structure mandated in the FOA. The effectiveness of this structure is evident from our network's high level of productivity, as judged by number of publications and completed studies, the size, scope, quality, and diversity of studies, and impact on health and daily clinical practice. The network will comprise six regional nodes, one specialty node, a central administrative core based at the University of Alabama at Birmingham (UAB), and a central Coordinating Center. Other key elements of the governing and administrative structure will include an Executive Committee, Node Directors Committee, Steering Committee, Node Coordinators Committee, Director of Communications & Dissemination, Director of Practitioner Recruitment & Engagement, Practitioner Training Component, Practitioner & Patient Compensation System, Publications & Presentations Committee, Central IRB, Data & Safety Monitoring Board, and NIDCR staff. Nodes will be based at Health Partners Institute (Minneapolis, MN); Kaiser Permanente (Portland, OR); UAB (Birmingham, AL); University of Florida (Gainesville, FL); University of Illinois (Chicago, IL); University of Rochester (Rochester, NY); and the University of Texas Health Science Center (San Antonio, TX).", "keywords": [ "Achievement", "Alabama", "Belief", "Chicago", "Clinical", "Clinical Research", "Clinical Trials Data Monitoring Committees", "Communication", "Communities", "Contracts", "Data", "Data Collection", "Dental", "Dental Care", "Dental General Practice", "Dental Group Practice", "Dental Specialties", "Development", "Effectiveness", "Elements", "Ensure", "Environment", "Financial compensation", "Florida", "Fostering", "Funding", "Funding Mechanisms", "Geographic Locations", "Goals", "Growth", "Health", "Health Sciences", "Human Resources", "Illinois", "Infrastructure", "Institutes", "Institutional Review Boards", "Journals", "Learning", "Manuscripts", "Measures", "Movement", "National Institute of Dental and Craniofacial Research", "Office Visits", "Oral health", "Outcome", "Patient Care", "Patient Recruitments", "Patient Representative", "Patients", "Peer Review", "Performance", "Phase", "Process", "Productivity", "Public Health", "Publications", "Research", "Research Personnel", "Resources", "Scandinavia", "Science", "Specific qualifier value", "Standardization", "Structure", "System", "Testing", "Texas", "Text", "Training", "Translational Research", "United States", "Universities", "Work", "base", "clinical decision-making", "clinical implementation", "clinical practice", "collaborative environment", "electronic data", "evidence base", "experience", "flexibility", "improved", "interest", "journal article", "medical specialties", "named group", "operation", "patient advocacy group", "protocol development", "public-private partnership", "recruit", "research study", "research to practice", "routine practice" ], "approved": true } }, { "type": "Grant", "id": "6517", "attributes": { "award_id": "3U19DE028717-02S2", "title": "The National Dental PBRN Administrative and Resource Center", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Dental and Craniofacial Research (NIDCR)" ], "program_reference_codes": [], "program_officials": [ { "id": 21846, "first_name": "LILLIAN", "last_name": "SHUM", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-06-07", "end_date": "2021-05-31", "award_amount": 272634, "principal_investigator": { "id": 21847, "first_name": "GREGG H", "last_name": "GILBERT", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 612, "ror": "https://ror.org/008s83205", "name": "University of Alabama at Birmingham", "address": "", "city": "", "state": "AL", "zip": "", "country": "United States", "approved": true }, "abstract": "“The project summary [for the Overall Component] is a succinct and accurate description of the proposed work… This section is limited to 30 lines of text… This application continues funding for “The National Dental PBRN”, a national collaborative of practices and organizations across the United States that engages practitioners in the excitement of discovery for the benefit of everyday clinical practice and patients. Consistent with specifications in the FOA itself, the Specific Aims will be to: (1) maximize efficiencies to conduct national oral health research studies in general and specialty dental practices on topics of importance to practitioners and their patients; (2) provide evidence useful in daily patient care; (3) facilitate the translation of research findings into clinical practice; (4) continue our work during the 2005-2019 funding period to demonstrate consistent growth and productivity by streamlining the implementation of clinical research across the network, facilitating practitioner and patient recruitment and retention, and developing public-private partnerships (to develop projects of interest to specific dental groups and specialties, practice types, special populations, and patient advocacy groups). The National Dental PBRN will accomplish these aims by building upon the many lessons learned from its highly-productive current national network. We aim to build on our experiences from these past 13 years using the same funding mechanism and administrative structure mandated in the FOA. The effectiveness of this structure is evident from our network's high level of productivity, as judged by number of publications and completed studies, the size, scope, quality, and diversity of studies, and impact on health and daily clinical practice. The network will comprise six regional nodes, one specialty node, a central administrative core based at the University of Alabama at Birmingham (UAB), and a central Coordinating Center. Other key elements of the governing and administrative structure will include an Executive Committee, Node Directors Committee, Steering Committee, Node Coordinators Committee, Director of Communications & Dissemination, Director of Practitioner Recruitment & Engagement, Practitioner Training Component, Practitioner & Patient Compensation System, Publications & Presentations Committee, Central IRB, Data & Safety Monitoring Board, and NIDCR staff. Nodes will be based at Health Partners Institute (Minneapolis, MN); Kaiser Permanente (Portland, OR); UAB (Birmingham, AL); University of Florida (Gainesville, FL); University of Illinois (Chicago, IL); University of Rochester (Rochester, NY); and the University of Texas Health Science Center (San Antonio, TX).", "keywords": [ "Achievement", "Alabama", "Belief", "Chicago", "Clinical", "Clinical Research", "Clinical Trials Data Monitoring Committees", "Communication", "Communities", "Contracts", "Data", "Data Collection", "Dental", "Dental Care", "Dental General Practice", "Dental Group Practice", "Dental Specialties", "Development", "Effectiveness", "Elements", "Ensure", "Environment", "Financial compensation", "Florida", "Fostering", "Funding", "Funding Mechanisms", "Geographic Locations", "Goals", "Growth", "Health", "Health Sciences", "Human Resources", "Illinois", "Infrastructure", "Institutes", "Institutional Review Boards", "Journals", "Learning", "Manuscripts", "Measures", "Movement", "National Institute of Dental and Craniofacial Research", "Office Visits", "Oral health", "Outcome", "Patient Care", "Patient Recruitments", "Patient Representative", "Patients", "Peer Review", "Performance", "Phase", "Process", "Productivity", "Public Health", "Publications", "Research", "Research Personnel", "Resources", "Scandinavia", "Science", "Specific qualifier value", "Standardization", "Structure", "System", "Testing", "Texas", "Text", "Training", "Translational Research", "United States", "Universities", "Work", "base", "clinical decision-making", "clinical implementation", "clinical practice", "collaborative environment", "electronic data", "evidence base", "experience", "flexibility", "improved", "interest", "journal article", "medical specialties", "named group", "operation", "patient advocacy group", "protocol development", "public-private partnership", "recruit", "research study", "research to practice", "routine practice" ], "approved": true } }, { "type": "Grant", "id": "10861", "attributes": { "award_id": "3R01DK122603-04S1", "title": "A Randomized Cross-Over Trial Evaluating Automated Insulin Delivery Technologies on Glycemic Outcomes and Quality of Life in Older Adults with Type 1 Diabetes", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)" ], "program_reference_codes": [], "program_officials": [ { "id": 23175, "first_name": "Guillermo", "last_name": "Arreaza-Rubin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-11-04", "end_date": "2023-04-30", "award_amount": 239044, "principal_investigator": { "id": 26949, "first_name": "Naomi Sage", "last_name": "Chaytor", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26950, "first_name": "Robert J", "last_name": "Henderson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26951, "first_name": "YOGISH C.", "last_name": "KUDVA", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26952, "first_name": "RICHARD E", "last_name": "PRATLEY", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26953, "first_name": "Michael R", "last_name": "Rickels", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26954, "first_name": "Ruth S", "last_name": "Weinstock", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1975, "ror": "", "name": "JAEB CENTER FOR HEALTH RESEARCH, INC.", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "“A Randomized Cross-Over Trial Evaluating Automated Insulin Delivery Technologies on Glycemic Outcomes and Quality of Life in Older Adults with Type 1 Diabetes” (AIDE) Reducing hypoglycemia is an important aspect of management of type 1 diabetes in older adults, many of whom have hypoglycemic unawareness, cognitive impairment, or both. Clinical trials of existing automated insulin delivery systems have not included older adults in sufficient numbers to allow for focused evaluation of efficacy and quality of life impacts that may differ from those observed in younger age groups. The research entitled “A Randomized Cross-over Trial Evaluating Automated Insulin Delivery Technologies on Glycemic Outcomes and Quality of Life in Older Adults with Type 1 Diabetes” aims to evaluate the effectiveness of 1) hybrid closed loop (HCL) technology and 2) predictive low-glucose suspension (PLGS) on glycemic outcomes, QOL indicators and usability compared with sensor-augmented pump (SAP) therapy, as well as evaluate the safety of these technologies, in older adults with T1D. A secondary objective is to directly compare HCL with PLGS on these same outcomes. These aims will be achieved via a multi-center, randomized, crossover trial, consisting of three treatment arms over three 12-week periods, with the HCL treatment arm used during one period, the PLGS treatment arm used during one period and SAP treatment arm (control) used during one period. The crossover trial will be preceded by a run-in phase in which participants will receive training on using the study devices. The randomized trial will include 90 individuals, aged at least 65 years, with T1D for at least one year who have evidence of sensor measured hypoglycemia during the baseline run-in. The primary outcome is percent of time spent with glucose levels less than 70 mg/dl during each period. Other glycemic metrics, QOL assessments and system usability will be secondary outcomes. Occurrences of severe hypoglycemia, diabetic ketoacidosis, falls/fractures, emergency room visits, and hospitalizations also will be assessed. Following the cross-over trial, participants will be given the opportunity to use study devices for an additional 12 weeks to assess choice of system use (PLGS vs. HCL), long-term durability and safety in a more real-world setting with less frequent study contacts. Thus, it is imperative to assess whether more advanced technologies involving automation of insulin delivery can be successfully implemented into diabetes management of older adults. Recruitment was slowed due to the COVID pandemic. As of October 18th, 2022, 70 of the total 90 participants are randomized, 36 of which are still active. Recruitment stalled during the COVID- 19 pandemic; this application is for funding to complete the follow-up of participants until December 1st, 2023, with 4 months for analysis and closeout afterward.", "keywords": [ "Acute", "Adopted", "Adult", "Adverse effects", "Age", "Algorithms", "Automation", "COVID-19 pandemic", "Characteristics", "Clinic", "Clinical Trials", "Cognition", "Cross-Over Trials", "Data", "Devices", "Diabetes Mellitus", "Diabetic Ketoacidosis", "Effectiveness", "Elderly", "Emergency department visit", "Event", "Family", "Fracture", "Fright", "Funding", "Glucose", "Glycosylated hemoglobin A", "Goals", "Hospitalization", "Hybrids", "Hyperglycemia", "Hypoglycemia", "Impaired cognition", "Individual", "Insulin", "Insulin-Dependent Diabetes Mellitus", "Knowledge", "Measures", "Methods", "Outcome", "Outcome Measure", "Participant", "Patient Care", "Patient Outcomes Assessments", "Patient Preferences", "Patients", "Perception", "Phase", "Population", "Prevention", "Pump", "Quality of life", "Quality-of-Life Assessment", "Randomized", "Research", "Running", "Safety", "Suspensions", "System", "Technology", "Time", "Training", "Translating", "Vulnerable Populations", "age group", "aged", "arm", "automobile accident", "clinical care", "data registry", "diabetes distress", "diabetes management", "effectiveness evaluation", "efficacy evaluation", "fall risk", "falls", "follow-up", "glucose monitor", "glycemic control", "human old age (65+)", "hypoglycemia unawareness", "improved", "indexing", "innovation", "mental state", "mortality", "older patient", "preference", "primary endpoint", "primary outcome", "psychosocial", "randomized trial", "recruit", "safety outcomes", "satisfaction", "secondary outcome", "sensor", "societal costs", "treatment arm", "treatment comparison", "trial design", "usability", "wireless" ], "approved": true } }, { "type": "Grant", "id": "14592", "attributes": { "award_id": "1UM1TR004771-01", "title": "CTSA UM1 at the University of Alabama at Birmingham", "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": [ { "id": 21618, "first_name": "Audie A", "last_name": "Atienza", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-05-01", "end_date": "2031-04-30", "award_amount": 9869052, "principal_investigator": { "id": 31258, "first_name": "PATRICE", "last_name": "DELAFONTAINE", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 11466, "first_name": "Robert P.", "last_name": "Kimberly", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 612, "ror": "https://ror.org/008s83205", "name": "University of Alabama at Birmingham", "address": "", "city": "", "state": "AL", "zip": "", "country": "United States", "approved": true } ] }, { "id": 31259, "first_name": "Orlando M", "last_name": "Gutierrez", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 612, "ror": "https://ror.org/008s83205", "name": "University of Alabama at Birmingham", "address": "", "city": "", "state": "AL", "zip": "", "country": "United States", "approved": true }, "abstract": "– The Center for Clinical and Translational Science (CCTS), the CTSA Hub at the University of Alabama at Birmingham (UAB), serves a region of the country with a disproportionate burden of multiple chronic diseases and health disparities. The COVID-19 pandemic brought into sharp relief the critical importance of translating new scientific discoveries into interventions that improve the health of patients and their communities in an efficient, effective and equitable manner. The unique health challenges faced by our communities previously prompted the creation of the CCTS Partner Network – spanning Alabama, Mississippi and Louisiana – to ensure that our research and training efforts serve the populations in our region while maximizing collaborative synergies in clinical and translational science (CTS) investigation to catalyze discovery and accelerate the dissemination and implementation of evidence toward health impact. As it continues to serve as a national resource for responding to public health emergencies, the CCTS Partner Network will provide programmatic leadership and shared governance (Aim 1) to mobilize the resources and talents throughout the region as it brings together academic, health system, industry and community partners to advance discovery science in concert with the CTSA consortium. The CCTS will further the development of a vibrant, diverse clinical and translational research workforce (Aim 2) by expanding programs that provide both didactic and experiential training to convey new skills, perspectives and understanding of the translation process for faculty, trainees, clinical research professionals and community alike. The Center will promote community and stakeholder engagement (Aim 3) in trusting, bidirectional relationships in all aspects of the research process to develop, demonstrate, disseminate and implement new discoveries to enhance the impact of health insights on those who will most benefit. It will leverage expertise in health informatics, clinical research informatics and translational bioinformatics to extend collaborative, coordinated data analytics and digital innovations across the Partner Network and the CTSA consortium (Aim 4) that allow full utilization of real world data together with rich, deep clinical information to enable discovery research from the bench to the learning healthcare system. The CCTS Hub and Network will support ethical, scientifically rigorous, informative clinical trials and pilot studies by providing a range of specialized services, resources and consultations (Aim 5) guided by NCATS principles of effective translational science. Through these efforts, the CCTS will formalize its CTS Research Program (Aim 6) to identify, develop and test novel approaches to overcome significant roadblocks in biomedical research, generating new insights that can be generalized to other CTSA Hubs. By achieving these aims, the CCTS will harness the Network’s vibrant collaborative energy to accelerate the discovery, dissemination and implementation of new findings, deliver treatments to more people more quickly, reduce the burden of chronic disease and advance health equity in the Deep South and beyond.", "keywords": [ "Acceleration", "Address", "Affect", "Alabama", "Area", "Back", "Bioinformatics", "Biomedical Research", "Biotechnology", "COVID-19 pandemic", "Chronic Disease", "Clinical", "Clinical Research", "Clinical Sciences", "Clinical Trials", "Communication", "Communities", "Complement", "Consultations", "Country", "Data", "Data Analytics", "Dedications", "Deep South", "Development", "Disease", "Disparity", "Dissemination and Implementation", "Diverse Workforce", "Ecosystem", "Ensure", "Equity", "Ethics", "Evaluation", "Faculty", "Feedback", "Future", "Goals", "Growth", "Health", "Health Sciences", "Health system", "Healthcare Systems", "Informatics", "Infrastructure", "Institution", "Intervention", "Investigation", "Knowledge", "Leadership", "Learning", "Louisiana", "Malignant Neoplasms", "Medical center", "Mentors", "Mission", "Mississippi", "National Center for Advancing Translational Sciences", "Neurologic", "Patients", "Persons", "Pilot Projects", "Population", "Process", "Public Health", "Public Health Informatics", "Research", "Research Methodology", "Research Project Grants", "Research Support", "Resource Informatics", "Resources", "Science", "Scientific Advances and Accomplishments", "Services", "Special needs", "Talents", "Testing", "Training", "Training Programs", "Training and Education", "Translating", "Translation Process", "Translational Research", "Trust", "Universities", "Vision", "Work", "burden of chronic illness", "cardiometabolism", "career", "clinical center", "community partners", "community partnership", "data interoperability", "design", "digital", "disease disparity", "evidence base", "health care delivery", "health disparity", "health equity", "high dimensionality", "improved", "industry partner", "innovation", "insight", "multidisciplinary", "novel strategies", "novel therapeutics", "programs", "public health emergency", "research study", "skills", "synergism", "tool" ], "approved": true } }, { "type": "Grant", "id": "8029", "attributes": { "award_id": "4R61HD105591-02", "title": "A data science approach to identify and manage Multisystem Inflammatory Syndrome in Children (MIS-C) associated with SARS-CoV-2 infection and Kawasaki disease in pediatric patients", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [ { "id": 6155, "first_name": "Sai Prasanna", "last_name": "Majji", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-01", "end_date": "2022-11-30", "award_amount": 783833, "principal_investigator": { "id": 23923, "first_name": "Nagib", "last_name": "Dahdah", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 23924, "first_name": "THERESE M", "last_name": "GIGLIA", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 23925, "first_name": "Shelby", "last_name": "Kutty", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 23926, "first_name": "BRIAN W", "last_name": "MCCRINDLE", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 23927, "first_name": "Cedric", "last_name": "Manlhiot", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "– Since the SARS-CoV-2 pandemic began, the emergence of an associated novel multisystem inflammatory syndrome in children (MIS-C) has been reported. Interestingly, patients with MIS-C follow a presentation, management and clinical course that are somewhat similar to that of patients with Kawasaki disease (KD). Currently, the reason for such an overlap in clinical features and management is unclear and whether this overlap is the result of a partially shared etiology or pathophysiology is the subject of fierce debates. The degree of overlap implies that some of the clinical prediction tools that we have developed in the past for KD could be repurposed to accelerate the development of clinical support decision tools for MIS-C. In this study, we will first (R61 component) systematically address the overlap between KD and MIS-C and create salient machine-learning based prediction models for diagnosis/identification (Aim #1), management (Aim #2), and short- and long-term outcomes (Aim #3) of MIS-C based on our previously developed predictive models for KD in a process akin to transfer learning. Secondly (R33 component), we will validate and evaluate the performance and clinical utility of these models in a predictive clinical decision support system for the diagnosis and management of pediatric patients presenting with features indicative of either MIS-C or KD. In this study we will include 3 groups of patients: 1) patients with SARS-CoV-2 infection with MIS-C (CDC criteria) regardless of whether they have overlapping signs of KD, 2) patients with SARS-CoV-2 infection investigated for but eventually not diagnosed with MIS-C, and 3) patients with KD but without SARS-CoV-2 infection. Targeted data will be collected from enrolled patients (900 for training and 450 for validation) for deep phenotyping and biomarker measurements. Physician feedback on the predictions generated by the algorithm will be used to establish clinical utility. Data required for model training will be accrued in the first two years of activity (R61 period of the grant); the development of algorithms and their internal validation will occur concurrently. In the following 2 years (R33 period of the grant), we will perform external validation, establish clinical utility, add real- time epidemiological surveillance data to the models and finally package, and certify the algorithms for future deployment and for the integration in electronic health records. This project will be a collaboration with the International Kawasaki Disease Registry (IKDR) Consortium. The IKDR Consortium has an active KD and pediatric COVID registry in 35 sites across the world and the number of sites is currently expanding to 60+ sites. More than 600 MIS-C patients have already been identified at IKDR centers, making this project clearly feasible and perfectly positioning IKDR to perform this study. We strongly believe that the use of emerging data science methods and of our previously developed algorithms in the context of KD, as opposed to focusing on MIS-C patients alone, will boost our understanding of the etiology and pathophysiology of both MIS-C and KD and will more rapidly lead to the emergence of data-driven management protocols for patients with MIS-C.", "keywords": [ "2019-nCoV", "Address", "Affect", "Algorithms", "Benign", "Biological Markers", "COVID-19 pandemic", "COVID-19 patient", "Centers for Disease Control and Prevention (U.S.)", "Child", "Childhood", "Clinical", "Clinical Data", "Clinical Decision Support Systems", "Clinical Management", "Collaborations", "Complex", "Consultations", "Data", "Data Collection", "Data Science", "Decision Support Systems", "Development", "Diagnosis", "Disease", "Electronic Health Record", "Enrollment", "Epidemiologic Monitoring", "Epidemiology", "Etiology", "Evaluation", "Feedback", "Functional disorder", "Future", "Grant", "Heart Diseases", "Image", "Inflammatory", "International", "Investigation", "Knowledge", "Lead", "Management Decision Support Systems", "Measurement", "Methods", "Modeling", "Mucocutaneous Lymph Node Syndrome", "Multisystem Inflammatory Syndrome in Children", "Newly Diagnosed", "Outcome", "Patients", "Performance", "Phase", "Physicians", "Positioning Attribute", "Probability", "Process", "Protocols documentation", "Recording of previous events", "Registries", "Reporting", "Research Personnel", "Resource-limited setting", "Risk", "SARS-CoV-2 exposure", "SARS-CoV-2 infection", "Signs and Symptoms", "Site", "Syndrome", "System", "Testing", "Time", "Training", "Validation", "Vascular Diseases", "Work", "adverse outcome", "algorithm development", "application programming interface", "base", "clinical decision support", "clinical development", "clinical predictors", "coronavirus disease", "design", "disease registry", "epidemiologic data", "experience", "interoperability", "large scale data", "machine learning algorithm", "machine learning prediction", "medical complication", "novel", "optimal treatments", "pediatric patients", "phenotypic biomarker", "predicting response", "predictive modeling", "prospective", "response", "surveillance data", "tool", "transfer learning", "treatment response" ], "approved": true } }, { "type": "Grant", "id": "8030", "attributes": { "award_id": "1R61HD105591-01", "title": "A data science approach to identify and manage Multisystem Inflammatory Syndrome in Children (MIS-C) associated with SARS-CoV-2 infection and Kawasaki disease in pediatric patients", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [ { "id": 6155, "first_name": "Sai Prasanna", "last_name": "Majji", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-01", "end_date": "2022-04-30", "award_amount": 917957, "principal_investigator": { "id": 23923, "first_name": "Nagib", "last_name": "Dahdah", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 23924, "first_name": "THERESE M", "last_name": "GIGLIA", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 23925, "first_name": "Shelby", "last_name": "Kutty", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 23926, "first_name": "BRIAN W", "last_name": "MCCRINDLE", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 23927, "first_name": "Cedric", "last_name": "Manlhiot", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "– Since the SARS-CoV-2 pandemic began, the emergence of an associated novel multisystem inflammatory syndrome in children (MIS-C) has been reported. Interestingly, patients with MIS-C follow a presentation, management and clinical course that are somewhat similar to that of patients with Kawasaki disease (KD). Currently, the reason for such an overlap in clinical features and management is unclear and whether this overlap is the result of a partially shared etiology or pathophysiology is the subject of fierce debates. The degree of overlap implies that some of the clinical prediction tools that we have developed in the past for KD could be repurposed to accelerate the development of clinical support decision tools for MIS-C. In this study, we will first (R61 component) systematically address the overlap between KD and MIS-C and create salient machine-learning based prediction models for diagnosis/identification (Aim #1), management (Aim #2), and short- and long-term outcomes (Aim #3) of MIS-C based on our previously developed predictive models for KD in a process akin to transfer learning. Secondly (R33 component), we will validate and evaluate the performance and clinical utility of these models in a predictive clinical decision support system for the diagnosis and management of pediatric patients presenting with features indicative of either MIS-C or KD. In this study we will include 3 groups of patients: 1) patients with SARS-CoV-2 infection with MIS-C (CDC criteria) regardless of whether they have overlapping signs of KD, 2) patients with SARS-CoV-2 infection investigated for but eventually not diagnosed with MIS-C, and 3) patients with KD but without SARS-CoV-2 infection. Targeted data will be collected from enrolled patients (900 for training and 450 for validation) for deep phenotyping and biomarker measurements. Physician feedback on the predictions generated by the algorithm will be used to establish clinical utility. Data required for model training will be accrued in the first two years of activity (R61 period of the grant); the development of algorithms and their internal validation will occur concurrently. In the following 2 years (R33 period of the grant), we will perform external validation, establish clinical utility, add real- time epidemiological surveillance data to the models and finally package, and certify the algorithms for future deployment and for the integration in electronic health records. This project will be a collaboration with the International Kawasaki Disease Registry (IKDR) Consortium. The IKDR Consortium has an active KD and pediatric COVID registry in 35 sites across the world and the number of sites is currently expanding to 60+ sites. More than 600 MIS-C patients have already been identified at IKDR centers, making this project clearly feasible and perfectly positioning IKDR to perform this study. We strongly believe that the use of emerging data science methods and of our previously developed algorithms in the context of KD, as opposed to focusing on MIS-C patients alone, will boost our understanding of the etiology and pathophysiology of both MIS-C and KD and will more rapidly lead to the emergence of data-driven management protocols for patients with MIS-C.", "keywords": [ "2019-nCoV", "Address", "Affect", "Algorithms", "Benign", "Biological Markers", "COVID-19 pandemic", "COVID-19 patient", "Centers for Disease Control and Prevention (U.S.)", "Child", "Childhood", "Clinical", "Clinical Data", "Clinical Decision Support Systems", "Clinical Management", "Collaborations", "Complex", "Consultations", "Data", "Data Collection", "Data Science", "Decision Support Systems", "Development", "Diagnosis", "Disease", "Electronic Health Record", "Enrollment", "Epidemiologic Monitoring", "Epidemiology", "Etiology", "Evaluation", "Feedback", "Functional disorder", "Future", "Grant", "Heart Diseases", "Image", "Inflammatory", "International", "Investigation", "Knowledge", "Lead", "Machine Learning", "Management Decision Support Systems", "Measurement", "Methods", "Modeling", "Mucocutaneous Lymph Node Syndrome", "Multisystem Inflammatory Syndrome in Children", "Newly Diagnosed", "Outcome", "Patients", "Performance", "Phase", "Physicians", "Positioning Attribute", "Probability", "Process", "Protocols documentation", "Psychological Transfer", "Recording of previous events", "Registries", "Reporting", "Research Personnel", "Resources", "Risk", "SARS-CoV-2 exposure", "SARS-CoV-2 infection", "Signs and Symptoms", "Site", "Syndrome", "System", "Testing", "Time", "Training", "Validation", "Vascular Diseases", "Work", "adverse outcome", "algorithm development", "application programming interface", "base", "clinical decision support", "clinical development", "clinical predictors", "coronavirus disease", "design", "disease registry", "epidemiologic data", "experience", "interoperability", "large scale data", "machine learning algorithm", "medical complication", "novel", "optimal treatments", "pediatric patients", "phenotypic biomarker", "predicting response", "predictive modeling", "prospective", "response", "surveillance data", "tool", "treatment response" ], "approved": true } }, { "type": "Grant", "id": "6324", "attributes": { "award_id": "3UL1TR001450-06S3", "title": "South Carolina Clinical & Translational Research Institute (SCTR)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [ { "id": 21334, "first_name": "Rashmi", "last_name": "Gopal-Srivastava", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-09-24", "end_date": "2025-03-31", "award_amount": 100000, "principal_investigator": { "id": 21335, "first_name": "KATHLEEN T.", "last_name": "BRADY", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1179, "ror": "https://ror.org/012jban78", "name": "Medical University of South Carolina", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 21336, "first_name": "PATRICK A", "last_name": "FLUME", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1179, "ror": "https://ror.org/012jban78", "name": "Medical University of South Carolina", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true }, "abstract": "– SCTR INSTITUTE Parent Award UL1-TR001450 Since 2009, the South Carolina Clinical and Translational Research Institute (SCTR) has transformed the research environment across South Carolina (SC) by creating a Learning Health System that supports high- quality clinical and translational research (CTR) and fosters collaboration and innovation. Headquartered at the Medical University of South Carolina (MUSC), SCTR has engaged stakeholders and created statewide partnerships to improve care and address social determinants of health across SC. However, greater than 75% of SC is rural, and all 46 counties contain areas designated as medically underserved, so health disparities remain an issue. Over the next five years, SCTR will strengthen its outreach to these medically underserved areas through collaboration with the Clemson University Health Extension Program and the MUSC Telehealth Center of Excellence. With a focus on implementation and dissemination as well as discovery, we will develop and demonstrate innovative technologies and outreach to improve the health of our stakeholders. We will build on prior successes and introduce innovative approaches to expand CTR across SC through the following aims: Aim 1. Extend and enhance high-quality, innovative, flexible curricula and training experiences for all levels of the CTR workforce, with particular emphasis on enhancing workforce heterogeneity and team science. Aim 2. Engage a diverse group of stakeholders as active partners in CTR to address health care priorities while enhancing the scientific knowledge base about collaboration and engagement. Aim 3. Promote greater inclusion across the full translational spectrum of research by engaging investigators from many disciplines and patient populations from diverse demographic backgrounds and geographic areas. Aim 4. Develop, demonstrate and disseminate innovative methods and processes to address barriers and accelerate the translation of research discoveries to improvements in human health that can be generalized to a variety of practice settings. Aim 5. Enhance the conduct of translational research through the development of secure and innovative informatics and digital health solutions, tools and methodologies that affect every aspect of CTR. SCTR’s vision is to be a major force in facilitating the translation of innovative science into practice to address the health priorities of the citizens of SC and beyond. To achieve this vision, SCTR’s mission is to catalyze the development of methods and technologies that lead to more efficient translation of biomedical discoveries into interventions that improve individual and public health. SCTR will serve as the statewide academic home for CTR, one that is well-integrated with SC’s healthcare systems and provides essential support for innovative, efficient, multidisciplinary research and research training. We will work within SCTR, with our partners across SC and with the CTSA Consortium to realize this vision.", "keywords": [ "2019-nCoV", "Address", "Administrative Supplement", "Affect", "Area", "Award", "Biomedical Research", "COVID-19", "COVID-19 pandemic", "Caring", "Clinical", "Clinical Data", "Clinical Research", "Clinical Sciences", "Clinical Trials Network", "Clinical and Translational Science Awards", "Clinical effectiveness", "Collaborations", "Communities", "County", "Databases", "Development", "Discipline", "Diverse Workforce", "Educational Curriculum", "Electronic Health Record", "Emergency Situation", "Environment", "Fast Healthcare Interoperability Resources", "Fostering", "Geographic Locations", "Health", "Health Priorities", "Health Sciences", "Health system", "Healthcare", "Healthcare Systems", "Heterogeneity", "Home environment", "Human", "Individual", "Informatics", "Information Retrieval", "Interdisciplinary Study", "Intervention", "Lead", "Learning", "Link", "Medical", "Medically Underserved Area", "Methodology", "Methods", "Mission", "Modeling", "Natural Language Processing", "Outcome", "Parents", "Patients", "Phenotype", "Population", "Population Heterogeneity", "Process", "Public Health", "Research", "Research Institute", "Research Personnel", "Research Training", "Resources", "Rural", "Science", "Secure", "South Carolina", "Support System", "Technology", "Terminology", "Text", "Training", "Training and Infrastructure", "Translating", "Translational Research", "Translations", "Universities", "Vision", "Work", "base", "biomedical informatics", "cohort", "coronavirus disease", "cost effective", "data access", "data enclave", "data interoperability", "data modeling", "data sharing", "digital", "expectation", "experience", "flexibility", "health disparity", "improved", "innovation", "innovative technologies", "interest", "knowledge base", "medically underserved", "member", "method development", "outreach", "parent grant", "patient population", "practice setting", "programs", "response", "rural underserved", "social health determinants", "success", "synergism", "telehealth", "tool", "translational pipeline", "web services" ], "approved": true } }, { "type": "Grant", "id": "15390", "attributes": { "award_id": "1U19AI181930-01", "title": "RP1: Antigen design and testing of arenavirus and nairovirus", "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": "2024-07-30", "end_date": "2027-06-30", "award_amount": 4640498, "principal_investigator": { "id": 31991, "first_name": "Robert W", "last_name": "Cross", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 851, "ror": "", "name": "UNIVERSITY OF TEXAS MED BR GALVESTON", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "– RP1 (Antigen Design and Testing Of Arenavirus And Nairovirus Vaccines) The viral order Bunyavirales contains several high priority human pathogens. Notably, Arenaviridae and Nairoviridae families contain viruses which cause severe hemorrhagic diseases in humans across the world with mortality rates up to 60% and some are associated with significant, long-term sequelae in survivors. Of these, rodent borne arenaviruses – Lassa (LASV), Lujo, Chapare, Guanarito, Junin and Machupo viruses and one tickborne Nairovirus-Crimean-Congo Hemorrhagic Fever Virus- are identified as NIAID Category A pathogens due to ease of dissemination or transmission person-to-person, production of significant morbidity and mortality, the potential for major public health impact, and due to the requirement for special action for public health preparedness. Threats to public health are further heightened by the lack of internationally approved vaccines to address threats of natural epidemics as well as the potential bio-weaponization of these viruses. To address this unmet need, PABVAX RP1 will leverage combined expertise in high-containment virology, immunology, and biological product development, to develop arenavirus and nairovirus research tools and vaccine approaches using prototype members of each viral group which can be adapted across each viral family using a “plug-and-play” approach. Much of the work developing vaccines for these viruses has relied on isolates derived over 40 years ago, recent advances in viral reverse for these viral families is making vaccine testing of emerging isolates more feasible by improving access. Vaccine development for most arenaviruses and nairoviruses has centered on the understanding of the critical role for viral glycoproteins (GP) and nucleoproteins (NP) to drive natural immunity. We have recently successfully engineered a recombinant, stabilized prefusion LASV GPe to act as an antigenic mimic of viral surface displayed GP and found this trimeric GPe alone, co- delivered with NP, or NP subunits alone, can protect guinea pigs against lethal challenge by LASV underscoring the value of these antigens as vaccine components. Subunit vaccines are prime candidates for alternative vaccination approaches like microneedle patches (MNP). MNP coupled antigens and adjuvants directly interact with the potently immunoresponsive cutaneous microenvironments using dissolvable MNPs to elicit robust and long-lasting protective immunity against the target pathogen. The importance of humoral immunity for affording potent protection or treatment against viral infections cannot be understated as evidenced by the recent success using monoclonal antibody therapies to treat Ebola virus disease or COVID-19, yet little is known for the potential for pre-exposure prophylactic (PREP) administration of antibody therapies and what kind of prophylactic windows are possible. In this proposal, we will develop protective protein-based subunit-MNP vaccines, PREP treatment strategies, and recombinant virus tools using prototyped arenaviruses and nairoviruses which will template development of countermeasures against other related Bunyaviridae members.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "11663", "attributes": { "award_id": "5U19AI167903-02", "title": "Systems biological assessment of B cell responses to vaccination", "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": "2022-03-07", "end_date": "2027-02-28", "award_amount": 409240, "principal_investigator": { "id": 23528, "first_name": "Scott Dexter", "last_name": "Boyd", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 266, "ror": "https://ror.org/00f54p054", "name": "Stanford University", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 266, "ror": "https://ror.org/00f54p054", "name": "Stanford University", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "– Project 3 The focus of Project 3 is to study antigen-specific B cell and plasma cell responses in the context of two timely and fundamental topics in vaccinology: (i) Immunology of COVID-19 vaccines, and (ii) the impact of the microbiota on immune responses to vaccination. The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 (CoV-2), and the vaccines developed to combat this pathogen, have underscored a need for greater understanding of primary antibody responses in humans. We will use a systematic panel of cutting- edge humoral immunity analyses to thoroughly characterize antibodies elicited by two CoV-2 vaccines, and the B cell and plasma cell clonal populations required for B cell memory and sustained antibody titers. Our focus will be on the serological, B cell and plasma cell responses elicited by a lipid nanoparticle mRNA vaccine (Pfizer-BioNTech), and a Matrix M-adjuvanted recombinant protein vaccine (Novavax). Combining these analyses with studies of innate immunity (Project 1) and T cell (Project 2) responses to these vaccines should highlight cellular mechanisms correlated with the strength and durability of antibody responses. Rare serious anaphylactoid adverse reactions have been reported for mRNA vaccines, particularly in individuals with a history of food allergy, and those with IgG antibodies specific for polyethylene glycol (PEG). We will examine potential B cell contributions to these anaphylactoid reactions, using specimens from affected individuals who received SARS-COV-2 mRNA vaccines. Finally, we will address the role of the microbiome on humoral immunity to vaccination, with a similar strategy of serological, memory B cell and plasma cell analyses in participants with or without temporarily ablated microbiota following antibiotic treatment. Of particular importance in the aforementioned studies, we will not only analyze peripheral blood B cells and plasmablasts, but also monitor lymph node germinal center reactions by fine-needle aspiration, and sample bone marrow plasma cells in the same participants, to comprehensively study humoral immunity to vaccination in humans. The combined impact of these investigations will likely be clinically significant in guiding the development of future vaccination strategies by uncovering the B cell and plasma cell specificities, differentiation pathways, and longevity stimulated by new SARS-CoV-2 vaccine platforms, and in clarifying the role of the microbiome in vaccine responses to novel antigens.", "keywords": [ "2019-nCoV", "Ablation", "Acute", "Address", "Adjuvant", "Adverse reactions", "Affect", "Affinity", "Allergic", "Antibiotic Therapy", "Antibiotics", "Antibodies", "Antibody Response", "Antibody titer measurement", "Antigens", "Avidity", "B-Cell Antigen Receptor", "B-Lymphocytes", "B-cell receptor repertoire sequencing", "Basophils", "Binding", "Biological Assay", "Blood", "Bone Marrow", "COVID-19", "COVID-19 pandemic", "COVID-19 vaccine", "Cells", "Clinical", "Clone Cells", "Collaborations", "DNA", "Data Analyses", "Development", "Ensure", "Epitopes", "Fine needle aspiration biopsy", "Food Hypersensitivity", "Future", "Glycoproteins", "Human", "Humoral Immunities", "Immune response", "Immunity", "Immunoglobulin G", "Immunoglobulin M", "Immunology", "Individual", "Infection", "Investigation", "Label", "Longevity", "Measures", "Memory B-Lymphocyte", "Methods", "Monitor", "Monoclonal Antibodies", "Natural Immunity", "Participant", "Pathogenicity", "Pathway interactions", "Phenotype", "Plasma Cells", "Plasmablast", "Polyethylene Glycols", "Population", "RNA vaccination", "RNA vaccine", "Rabies", "Rabies Vaccines", "Reaction", "Recombinant Proteins", "Recording of previous events", "Reporting", "Role", "SARS-CoV-2 antigen", "Sampling", "Serology", "Shapes", "Specificity", "Specimen", "Structure of germinal center of lymph node", "T-Lymphocyte", "Vaccination", "Vaccinee", "Vaccines", "Variant", "Viral", "Virus", "Virus Diseases", "adaptive immunity", "biological systems", "clinically significant", "combat", "coronavirus disease", "data management", "in vitro Assay", "lipid nanoparticle", "lymph nodes", "microbiome", "microbiota", "monoclonal antibody production", "multiplex assay", "novel", "novel coronavirus", "pathogen", "peripheral blood", "recruit", "response", "transcriptome", "vaccination strategy", "vaccine development", "vaccine platform", "vaccine response", "vaccinology", "variants of concern" ], "approved": true } }, { "type": "Grant", "id": "15185", "attributes": { "award_id": "1U19AI181103-01", "title": "Project 2", "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": "2024-09-04", "end_date": "2029-06-30", "award_amount": 699043, "principal_investigator": { "id": 9495, "first_name": "Michael S", "last_name": "Diamond", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2516, "ror": "", "name": "WASHINGTON UNIVERSITY", "address": "", "city": "", "state": "MO", "zip": "", "country": "United States", "approved": true }, "abstract": "– PROJECT 2 SARS-CoV-2 and influenza A viruses are human pathogens with broad geographic range that cause pandemics and jeopardize human health. While the rapid deployment of vaccines against COVID-19 and annual campaigns with seasonally-matched inactivated, intramuscularly-delivered influenza vaccines have saved millions of human lives, it has become increasingly apparent that intramuscularly-delivered vaccines do not effectively induce mucosal immunity in the respiratory tract, which in theory, could better limit virus infection or transmission at the portal of entry or egress. Although vaccination of antigen-naïve populations provides benefit against SARS-CoV- 2 infection, the impacts of intramuscular boosting on protection from infection by recent circulating strains has been less impressive, in part due to the effects of immune imprinting. In Project 2 of this CCHI, we hypothesize that viral infection in the context of prior recent vaccination induces mucosal immune responses that functionally differ from those after infection or vaccination alone in the levels and types of cross-neutralizing and Fc effector functions of antibodies (Abs), and cross-reactive T cell responses. Project 2 will address key knowledge gaps as to the functional quality of infection- and vaccine-induced systemic and mucosal immunity. To achieve these goals, we will utilize ongoing human natural history cohorts of infected and vaccinated adults with unique clinical samples to study how vaccination impacts qualitative and quantitative systemic and mucosal antibody, B and T cell responses, and Fc effector functions seen after SARS-CoV-2 or IAV infection. We also will utilize samples from a unique influenza A virus human challenge cohort to assess how recent immunization with a quadrivalent influenza vaccine (Flucelvax®) modulates induction of mucosal immunity and control of infection. Our innovative studies on SARS-CoV-2 and influenza infection and vaccination will provide new information on human immune responses and inform evaluation of new mucosal vaccines targeting the human respiratory tract.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 2, "pages": 1392, "count": 13920 } } }