Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1384&sort=award_amount
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=award_amount", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1405&sort=award_amount", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1385&sort=award_amount", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1383&sort=award_amount" }, "data": [ { "type": "Grant", "id": "6470", "attributes": { "award_id": "3U19AI077439-13S2", "title": "UCSF COVID-19 Immunophenotyping Clinical Study and Core Laboratories", "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": [ { "id": 21721, "first_name": "Gang", "last_name": "Dong", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-08", "end_date": "2022-03-31", "award_amount": 5742559, "principal_investigator": { "id": 21722, "first_name": "David J", "last_name": "Erle", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 768, "ror": "https://ror.org/043mz5j54", "name": "University of California, San Francisco", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "COVID-19, the pandemic illness caused by the novel virus SARS-CoV-2, is a serious respiratory illness that has high infectivity and a mortality rate that varies from <1% to up to 20% depending on underlying risk factors. Indeed, disease severity varies markedly based on recognized clinical risk factors (age and co-morbidities). The biological underpinnings of this clinical variability are unknown but likely relate to variation in both the virus and the host response. A detailed understanding of the risk factors for severe disease, including genetic and environmental factors and the nature of the host immunological response, is essential for the development of prognostic biomarkers and effective therapies. To meet this urgent need we propose to help develop and to participate in the IMPACC multi-center longitudinal clinical study of hospitalized patients with COVID-19 and to immunophenotype participants using shared immunological methods that will be designed an carried out by core laboratories at UCSF and at other participating institutions. Our specific aims are 1) to develop a prospective observational convenience cohort of adult subjects hospitalized with known or presumptive COVID-19, 2) to use this cohort to describe the relationship between specific immunologic assessments and clinical course of COVID-19 in hospitalized patients, and 3) to implement three core laboratories at UCSF to support immunophenotyping in this multicenter cohort. These core laboratories will perform bulk RNA sequencing of blood peripheral blood mononuclear cells (PBMC), bulk metagenomic next-generation sequencing (mNGS) on endotracheal aspirate samples, and serologic phage display assays (PhIP-Seq). Successful completion of these aims will yield critical information regarding the relationship between viral load, host immunological responses, and poor clinical outcomes that are urgently needed for biomarker development and rational therapeutic targeting. In addition, the cellular samples banked in this study may directly contribute to the development of neutralizing antibodies and vaccine strategies that will be our ultimate defense against recurrence of this extraordinary pandemic. A rapid and robust scientific and medical response of the type proposed by the NIAID and the academic community in this consortium is an essential element of a broad response required to protect the health and well-being of all individuals, our health care system, and the broader social structures that maintain global health and welfare.", "keywords": [ "2019-nCoV", "Adult", "Affect", "Age", "Aspirate substance", "Biological", "Biological Assay", "COVID-19", "COVID-19 pandemic", "Case Fatality Rates", "China", "Chronic", "Clinical", "Clinical Research", "Clinical Trials", "Communities", "Coronavirus", "DNA Sequencing Facility", "Development", "Diabetes Mellitus", "Disease", "Disease Outcome", "Elements", "Enrollment", "Environmental Risk Factor", "Family", "General Hospitals", "Genetic", "Genetic Risk", "Health", "Healthcare Systems", "Hypertension", "Immune System Diseases", "Immune response", "Immunologics", "Immunophenotyping", "Individual", "Infection", "Institution", "Intervention", "Investigation", "Laboratories", "Lung diseases", "Medical", "Medical center", "Metagenomics", "Methods", "Myocardial Ischemia", "National Institute of Allergy and Infectious Disease", "Nature", "Onset of illness", "Outcome", "Participant", "Pathogenicity", "Patients", "Peripheral Blood Mononuclear Cell", "Personal Satisfaction", "Phage Display", "Phage ImmunoPrecipitation Sequencing", "Pharmaceutical Preparations", "Pneumonia", "Prognostic Marker", "Recurrence", "Resources", "Risk Factors", "Sample Size", "Sampling", "San Francisco", "Serological", "Serum", "Severity of illness", "Site", "Therapeutic Agents", "Variant", "Viral Load result", "Virus", "base", "biomarker development", "clinical center", "clinical risk", "cohort", "comorbidity", "design", "effective therapy", "endotracheal", "global health", "health care availability", "improved", "inclusion criteria", "member", "mortality", "neutralizing antibody", "neutralizing vaccine", "next generation sequencing", "novel", "novel therapeutics", "novel virus", "pandemic disease", "pathogen", "peripheral blood", "prospective", "respiratory", "response", "social structure", "therapeutic target", "transcriptome sequencing", "trauma centers", "welfare" ], "approved": true } }, { "type": "Grant", "id": "15259", "attributes": { "award_id": "1U01IP001238-01", "title": "IP24-045, PREVENT: Preparedness through Respiratory Virus Epidemiology and Community Engagement", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Center for Immunization and Respiratory Diseases (NCIRD)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2024-08-01", "end_date": "2029-07-31", "award_amount": 5753431, "principal_investigator": { "id": 23572, "first_name": "LOUISE CHANG", "last_name": "LAURENT", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 760, "ror": "https://ror.org/0168r3w48", "name": "University of California, San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Monitoring of the incidence, morbidity, and mortality of respiratory infections has largely been performed by collecting and analyzing data from hospitals and clinical laboratories. While these data sources provide valuable information on risk factors, incidence, therapeutic response, and outcomes of severe disease, they do not reflect the range of potential clinical presentations and courses of disease, factors that increase or decrease the risk of community transmission, and the impact of disease on education and employment. We therefore propose to create “PREVENT: Preparedness through Respiratory Virus Epidemiology and Community Engagement,” which will serve as one of the CDC Pandemic Preparedness Network Cohorts and the Network’s Data Hub. We will participate in Components A1, A2, B, and C, with a catchment that spans San Diego County in HHS Region 9 adjacent to the U.S./Mexico border. Our relevant experience includes establishment of innovative programs for large-scale COVID-19 clinical testing, environmental surveillance through monitoring of wastewater and surface swabs, viral genome sequencing, and monitoring of immunity using co-created community-based sample collection strategies that are highly accessible and culturally sensitive. Major PREVENT activities will include: Component A1: We will enroll and retain a diverse longitudinal cohort of 2,000 individuals for: weekly symptom screening; surveys on knowledge, attitudes, and behaviors related to preventative measures; extraction of outcome and vaccination data from electronic health records and immunization information systems; and collection of follow-up data from participants on use of preventative/therapeutic measures and healthcare resources, missed school/work, symptom type/duration, and long-term sequelae. Symptomatic swabs will be collected and tested for 20 high-priority respiratory pathogens. Viral genome sequencing will be performed on a subset of samples using targeted and metatranscriptomic methods. Samples will be banked for >5 years. Component A2: Serial blood samples will be collected, analyzed, and banked from 20% of participants in Component A1. Samples will be collected at enrollment, in the months flanking the respiratory infection season, before/after vaccinations, and after infection. Quantitative immunoassays for antigen-specific antibody (Ab) levels and neutralizing antibody (nAb) levels against contemporary circulating virus isolates will be performed. Component B: For >100 index cases from A1 per year, we will collect and test daily nasal swabs from >75% of household members for >2 weeks. A subset of swabs (including at least 1 per index case) will be analyzed by viral genome sequencing, and high-priority pathogens/variants will be cultured. For a subset of households, we will also explore the relationships between viral load (quantified by qPCR) and viral titer (by in vitro cell-based assay), and between viral culture positivity and transmission. Component C: We will serve as the Data Hub and Warehouse, and support protocol development across the network, provide data entry and management tools, analyze data; and develop dashboards/visualizations.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3238", "attributes": { "award_id": "1636645", "title": "ALPACA: Advanced Cryogenic L-band Phased Array Camera for the Arecibo Radio Telescope", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "MID-SCALE INSTRUMENTATION" ], "program_reference_codes": [], "program_officials": [ { "id": 10184, "first_name": "Nigel", "last_name": "Sharp", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2018-06-15", "end_date": "2023-05-31", "award_amount": 5820519, "principal_investigator": { "id": 10189, "first_name": "Brian", "last_name": "Jeffs", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 436, "ror": "https://ror.org/047rhhm47", "name": "Brigham Young University", "address": "", "city": "", "state": "UT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 10185, "first_name": "James M", "last_name": "Cordes", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 10186, "first_name": "Donald B", "last_name": "Campbell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 10187, "first_name": "Karl F", "last_name": "Warnick", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 10188, "first_name": "Robert F", "last_name": "Minchin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 436, "ror": "https://ror.org/047rhhm47", "name": "Brigham Young University", "address": "", "city": "", "state": "UT", "zip": "", "country": "United States", "approved": true }, "abstract": "The objective of the program is to develop and deploy an Advanced Cryogenic L-Band Phased Array Camera for Arecibo (ALPACA) for the Arecibo Observatory 305 m radio telescope. With 40 beams, ALPACA will supersede the successful ALFA 7-beam receiver installed at Arecibo in 2004, increasing the survey speed by a factor of five. Major scientific objectives of the program include discovery of new pulsars, especially millisecond pulsars (MSPs) with stable periods suitable for inclusion in the program to detect gravitation radiation (NANOGrav), the detection and study of Fast Radio Bursts (FRBs), a census of gas-bearing low mass dark matter haloes in the local universe to test the validity of the Lambda/CDM cosmological model on small scales, and searches for extra-terrestrial intelligence (SETI). Broader impacts of the work include training of three graduate students in construction and commissioning of the instrument, and involvement of a potentially large number of undergraduates in planned large scale surveys (following the example of ALFA). These surveys will also be a vehicle for engaging interested citizen scientists in astronomy research. ALPACA will help maintain the Arecibo Observatory as a modern, cutting edge facility with numerous benefits for Puerto Rico, including advancing STEM training on the island. \n\nUnlike all other deployed phased array feed (PAF) receivers at other telescopes around the world, the ALPACA instrument will be cryogenically cooled. The design is based on the successful development at Cornell University, and testing on the Arecibo telescope, of a prototype 19 dual polarization dipole cryogenic PAF. Brigham Young University (BYU) participated in these tests by providing a narrowband digital beamformer back end and is developing a 150 MHz beamformer to be used with a 7-beam L-band PAF on the Green Bank 100m telescope.\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": "2599", "attributes": { "award_id": "2019609", "title": "RII Track-2 FEC: Leveraging Big Data to Improve Prediction of Tick-Borne Disease Patterns and Dynamics", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Office Of The Director", "EPSCoR Research Infrastructure" ], "program_reference_codes": [], "program_officials": [ { "id": 7542, "first_name": "Subrata", "last_name": "Acharya", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-09-01", "end_date": "2024-08-31", "award_amount": 5830709, "principal_investigator": { "id": 7546, "first_name": "Xiaogang", "last_name": "Ma", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 627, "ror": "", "name": "Regents of the University of Idaho", "address": "", "city": "", "state": "ID", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 7543, "first_name": "Frederick C Harris", "last_name": "Jr", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 7544, "first_name": "Xun", "last_name": "Shi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 7545, "first_name": "Barrie", "last_name": "Robison", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 627, "ror": "", "name": "Regents of the University of Idaho", "address": "", "city": "", "state": "ID", "zip": "", "country": "United States", "approved": true }, "abstract": "Tick-borne diseases (TDs) account for a staggering 94% of human illnesses due to vector-borne diseases in the U.S. The mission of this project is to assimilate disparate datasets with spatio-temporal, environmental and human predictors and to leverage cyberinfrastructure and data science to enhance forecasting of TDs in the western US. The core members of this project are from universities in three EPSCoR jurisdictions: University of Idaho, University of Nevada, Reno, and Dartmouth College (New Hampshire). The collaboration will build capacity across traditional boundaries of research and practice, with an aim to change the way people tackle TDs. Building upon the best practices and standards for open data, the findability and reusability of the assimilated datasets will be improved to enable new analyses and findings. Accordingly, the contributions of this project will have broad and sustained impacts on TD, a public health issue of national importance. With the early-career faculty mentoring activities, this project will increase the pool of academics and practitioners in a collaborative network for improved prediction and informed response to TDs in the western US. The digital games and demos released by the project will help improve the awareness of TDs among the general public. The efforts of this project will also support underserved and largely rural populations at high risk of TDs. All the training programs, including postdoc and graduate student positions, will give priority to women and underrepresented minority groups. Through the national Big Data innovation ecosystem, this project will add a new community of practice via shared deliverables, datasets and complementary knowledge to improve monitoring and forecasting of TDs across US and the world. \n\nThis project will contribute to NSF’s big ideas on Harnessing the Data Revolution and Growing Convergence Research through data-intensive research for improved prediction of TDs. The central scientific hypothesis is that, climate change will increase the prevalence of TDs throughout the western US, both through altering the geographic and seasonal distributions of ticks as well as interacting factors of environment, ecology, socioeconomics, and human behavior. The project team will collect and develop application-level datasets, knowledge graphs, tools, and innovative data science methods to advance the understanding of factors, patterns, and risks for TDs in the western US. The research includes three focused scientific objectives: (1) An advanced framework for TD research: Sparse data collection and FAIR framework, workflow provenance, and algorithms for a data life cycle; (2) Identify the changing patterns in tick importation routes, pathogens, and TD dynamics in the West; and (3) Develop spatio-temporal models of tick dynamics that link TDs to climate, environment and socioeconomic factors. The team will incorporate expertise in complementary disciplines to generate enriched open data, promote innovation and capacity in big data analytics, and develop training, education and outreach programs for sustained impact. Through the teamwork, the research will produce fresh understanding of the interacting factors in TD dynamics. Resources and mentoring to support early-career professionals will build towards sustained productivity. We will bring state-of-the-art knowledge and skills to postdocs, students and other practitioners to nurture a new workforce. This collaborative project will engage academic, state, federal and local partners to create a connected and smart network to tackle TDs.\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": "9419", "attributes": { "award_id": "4U24LM013755-02", "title": "RADx-Rad Discoveries & Data: Consortium Coordination Center Program Organization", "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": 10715, "first_name": "YANLI", "last_name": "WANG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-21", "end_date": "2024-11-30", "award_amount": 5848902, "principal_investigator": { "id": 25146, "first_name": "Eliah S", "last_name": "Aronoff-Spencer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 760, "ror": "https://ror.org/0168r3w48", "name": "University of California, San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 23731, "first_name": "LUCILA", "last_name": "OHNO-MACHADO", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 25147, "first_name": "HUA", "last_name": "XU", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 760, "ror": "https://ror.org/0168r3w48", "name": "University of California, San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "ABSTRACT Preparing SARS-CoV-2 testing data for reuse requires making the data syntactically and semantically equivalent. Standardization of terminologies and a common data model accomplish the former, while the latter is accomplished through understanding the data and making it comparable across RADx-rad awardees by benchmarking against known gold standards. The standardization of samples is as important as standardizing the data, particularly in the highly innovative RADx-rad program, where new technologies will be developed or optimized for deployment in various settings. Highly motivated RADx-rad awardees will receive advice on how their diagnostics compare to FDA-approved ones, with each other, how their diagnostic performs in independent testing, as well as how to ensure the tests are usable in real world settings. In collaboration with University of Texas Health Science Center at Houston, University of California San Diego researchers in informatics/data science and infectious diseases with ample experience in leading large consortia have designed a unique RADx- rad Consortium Data and Coordination Center (radCDCC). This center is based on three pillars: (1) effective administration and coordination among awardees, NIH, and other programs;; (2) innovative approaches and tools to collect and standardize data and metadata to promote findability, accessibility, interoperability and reuse (FAIR) for data sharing;; and (3) principled preparation of standardized samples with known quantities of viral loads, and standardized procedures for testing new diagnostics to allow comparison across tests and calibration of new technologies. Backed by sophisticated HIPAA-compliant cloud services, user friendly web-tools, and extensive support from UCSD’s facilities for computation and for clinical research, the radCDCC will interface with other RADx programs and other COVID-19 focused programs at NIH to ensure alignment of awardees, NIH and the public in the pursuit of effective, affordable, and deployable new technologies for testing.", "keywords": [ "Agreement", "Antibodies", "Area", "Award", "Back", "Benchmarking", "Biological Assay", "COVID-19", "COVID-19 diagnostic", "COVID-19 pandemic", "COVID-19 testing", "Calibration", "California", "Clinical Pathology", "Clinical Research", "Cloud Computing", "Cloud Service", "Collaborations", "Communicable Diseases", "Communication", "Communities", "Computer software", "Consultations", "Data", "Data Collection", "Data Coordinating Center", "Data Discovery", "Data Science", "Data Scientist", "Data Sources", "Development", "Diagnostic", "Diagnostic tests", "Ensure", "Evaluation", "FAIR principles", "FDA approved", "Funding", "Goals", "Gold", "Health Insurance Portability and Accountability Act", "Health Sciences", "Informatics", "Internet", "Knowledge", "Laboratories", "Logistics", "Metadata", "Methods", "Online Systems", "Persons", "Positioning Attribute", "Preparation", "Privacy", "Procedures", "Process", "Protocols documentation", "Quality Control", "RADx", "RADx Radical", "Reporting", "Research Personnel", "Resources", "Risk", "Role", "SARS-CoV-2 infection", "Sampling", "Science", "Secure", "Security", "Semantics", "Signal Transduction", "Specialist", "Specimen", "Standardization", "Structure", "Technology", "Terminology", "Testing", "Texas", "Time", "United States National Institutes of Health", "Universities", "Update", "Validation", "Viral", "Viral Load result", "Virus", "Work", "base", "dashboard", "data access", "data centers", "data exchange", "data management", "data modeling", "data reuse", "data sharing", "data standards", "design", "diagnostic technologies", "distributed data", "expectation", "experience", "help-seeking behavior", "indexing", "innovation", "meetings", "member", "new technology", "news", "novel diagnostics", "programs", "quality assurance", "repository", "search engine", "syntax", "testing services", "tool", "transmission process", "user centered design", "user-friendly", "virology" ], "approved": true } }, { "type": "Grant", "id": "10844", "attributes": { "award_id": "7U24LM013755-03", "title": "RADx-Rad Discoveries & Data: Consortium Coordination Center Program Organization", "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": 10715, "first_name": "YANLI", "last_name": "WANG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-01-01", "end_date": "2024-11-30", "award_amount": 5853027, "principal_investigator": { "id": 25146, "first_name": "Eliah S", "last_name": "Aronoff-Spencer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 760, "ror": "https://ror.org/0168r3w48", "name": "University of California, San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 23731, "first_name": "LUCILA", "last_name": "OHNO-MACHADO", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 25147, "first_name": "HUA", "last_name": "XU", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "ABSTRACT Preparing SARS-CoV-2 testing data for reuse requires making the data syntactically and semantically equivalent. Standardization of terminologies and a common data model accomplish the former, while the latter is accomplished through understanding the data and making it comparable across RADx-rad awardees by benchmarking against known gold standards. The standardization of samples is as important as standardizing the data, particularly in the highly innovative RADx-rad program, where new technologies will be developed or optimized for deployment in various settings. Highly motivated RADx-rad awardees will receive advice on how their diagnostics compare to FDA-approved ones, with each other, how their diagnostic performs in independent testing, as well as how to ensure the tests are usable in real world settings. In collaboration with University of Texas Health Science Center at Houston, University of California San Diego researchers in informatics/data science and infectious diseases with ample experience in leading large consortia have designed a unique RADx- rad Consortium Data and Coordination Center (radCDCC). This center is based on three pillars: (1) effective administration and coordination among awardees, NIH, and other programs;; (2) innovative approaches and tools to collect and standardize data and metadata to promote findability, accessibility, interoperability and reuse (FAIR) for data sharing;; and (3) principled preparation of standardized samples with known quantities of viral loads, and standardized procedures for testing new diagnostics to allow comparison across tests and calibration of new technologies. Backed by sophisticated HIPAA-compliant cloud services, user friendly web-tools, and extensive support from UCSD’s facilities for computation and for clinical research, the radCDCC will interface with other RADx programs and other COVID-19 focused programs at NIH to ensure alignment of awardees, NIH and the public in the pursuit of effective, affordable, and deployable new technologies for testing.", "keywords": [ "Agreement", "Antibodies", "Area", "Award", "Back", "Benchmarking", "Biological Assay", "COVID-19 diagnostic", "COVID-19 testing", "Calibration", "California", "Clinical Pathology", "Clinical Research", "Cloud Computing", "Cloud Service", "Collaborations", "Communicable Diseases", "Communication", "Communities", "Computer software", "Consultations", "Creativeness", "Data", "Data Collection", "Data Discovery", "Data Science", "Data Scientist", "Data Sources", "Development", "Diagnostic", "Diagnostic tests", "Ensure", "Evaluation", "FAIR principles", "FDA approved", "Funding", "Goals", "Gold", "Health Insurance Portability and Accountability Act", "Health Sciences", "Infection", "Informatics", "Infusion procedures", "Internet", "Knowledge", "Laboratories", "Logistics", "Metadata", "Methods", "Online Systems", "Persons", "Positioning Attribute", "Preparation", "Privacy", "Procedures", "Process", "Protocols documentation", "Quality Control", "RADx", "RADx Radical", "Reporting", "Research Personnel", "Resources", "Risk", "Role", "Sampling", "Science", "Secure", "Security", "Semantics", "Signal Transduction", "Specialist", "Specimen", "Standardization", "Structure", "Technology", "Terminology", "Testing", "Texas", "United States National Institutes of Health", "Universities", "Update", "Validation", "Viral", "Viral Load result", "Virus", "Visualization", "Work", "coronavirus disease", "dashboard", "data access", "data centers", "data exchange", "data management", "data modeling", "data reuse", "data sharing", "data standards", "design", "detection method", "diagnostic technologies", "distributed data", "expectation", "experience", "help-seeking behavior", "indexing", "innovation", "interoperability", "meetings", "member", "new technology", "news", "novel diagnostics", "pandemic disease", "programs", "quality assurance", "repository", "search engine", "syntax", "testing services", "tool", "transmission process", "usability", "user centered design", "user-friendly", "virology" ], "approved": true } }, { "type": "Grant", "id": "6190", "attributes": { "award_id": "3OT2OD030195-01S3", "title": "Establish a Public Private Partnership for COVID19 Research", "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": 20992, "first_name": "Felicia M", "last_name": "Qashu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-02", "end_date": "2021-12-31", "award_amount": 5898134, "principal_investigator": { "id": 20993, "first_name": "David N.", "last_name": "Wholley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1433, "ror": "", "name": "FOUNDATION FOR THE NIH", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1433, "ror": "", "name": "FOUNDATION FOR THE NIH", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The Foundation for the National Institutes of Health (FNIH) (www.fnih.org) was chartered by the Congress of the United States in 1990 as a not-for-profit 501(c)(3) charitable organization and has been working to facilitate groundbreaking research at the National Institutes of Health (NIH) and worldwide since 1996, creating and managing numerous biomedical public-private research partnerships that support the NIH’s mission. The FNIH therefore has extensive experience working with both NIH and the biopharmaceutical industry and deep familiarity with NIH’s people, science, practices, and policies. The FNIH has been asked by Dr. Francis S. Collins, Director of the NIH, to assist the agency in its response to the COVID-19 crisis. The aim of this collaboration is to accelerate NIH research urgently required to respond to this public health threat and to save lives by leveraging private-sector scientific expertise, in-kind assets and financial resources to augment federal efforts. Dr. Collins’ request that the FNIH help create a COVID-19 public-private partnership (PPP) to accelerate the development of therapeutics and vaccines under the Accelerating Medicines Partnership (AMP) is consistent with the FNIH’s own mission and the Congressional statute by which the FNIH was established to support the NIH in its mission and to advance collaboration with biomedical researchers from universities, industry, nonprofit organizations and other federal agencies, including the US Food and Drug Administration (FDA). AMP is a nimble and powerful public-private partnership that includes the NIH, FNIH, FDA and multiple biopharmaceutical companies and not-for-profit organizations. Managed by the FNIH, AMP programs bring together the resources of the NIH and industry to improve our understanding of disease pathways and facilitate better selection of targets for treatment. Multimillion dollar collaborations supported by the private sector through the FNIH have been established in four major disease areas: Alzheimer's disease, Type 2 diabetes, Rheumatoid Arthritis (RA)/Lupus and Parkinson's disease. The FNIH is also preparing to launch an AMP in Schizophrenia in partnership with the National Institute on Mental Health (NIMH). The overarching goal of the FNIH in this new AMP is to support the NIH in designing and implementing a strategic and coordinated cross-sector approach to end the current COVID-19 pandemic and to manage future such threats. This PPP is now known as ACTIV, the Accelerated COVID-19 Therapeutic Intervention and Vaccine partnership. Notably, most AMP projects start with a Design Phase that takes approximately 9 months to complete in which the FNIH identifies key partners, establishes scientific working and sub-groups, puts in place governance structures, executes contracts and agreements, deploys and trains appropriate staff, and identifies potential sources of funding. The result of the Design Phase is a detailed scientific and business plan for the PPP, which is called the Implementation Plan (sometimes referred to as the White Paper). The resulting Implementation Phase is a multiyear effort in which the PPP, through management by the FNIH, operationalizes the scientific plan and coordinates this work with critical support provided by NIH using its grants and contracts mechanisms. However, given the acute public health threat that has resulted in tens of thousands of COVID-19 deaths, the FNIH responded immediately to NIH’s call to action, redirecting staff from active, fully funded donor-supported programs to begin work on the Design Phase for the proposed PPP even though no financing for the FNIH’s work has yet been secured. In fact, for the past four weeks, the FNIH staff has been working non-stop on ACTIV, including nights and weekends, and has already achieved in record time what under normal circumstances would have taken months. This redeployment of staff is not sustainable, and the resulting costs and lost revenue are imposing an unacceptable burden on the FNIH’s finances. This request for support under NIH’s Other Transaction Authority (OTA) is, in fact, a do-or-die matter for the FNIH. While other funding sources have been explored and fundraising continues, none have or are likely to be forthcoming in a manner that is sufficiently timely to support the FNIH’s efforts. Quite simply, without immediate funding the FNIH will not be able to continue working on ACTIV and hence will be unable to support the NIH and its mission in this devastating COVID-19 health crisis. As requested in the Request for Negotiation to Establish a Public Private Partnership for COVID19 Research submitted by the NIH, the FNIH provides herein information concerning the work the FNIH has and will undertake until July 31, 2020 and the costs to underwrite that work. While much of this activity concerns the Design Phase, given the urgent need to make progress now, several critical implementation activities are anticipated to commence before July 31, 2020. Please note that this request also includes a separate request for support of the Deloitte Consulting, LLC (Deloitte) contract with the FNIH. Deloitte was contacted to expand and support the FNIH capabilities given the speed and volume of work required for ACTIV.", "keywords": [ "Acute", "Agreement", "Alzheimer&apos", "s Disease", "Area", "Biological Products", "Businesses", "COVID-19", "COVID-19 mortality", "COVID-19 pandemic", "COVID-19 therapeutics", "Collaborations", "Congresses", "Consult", "Contracts", "Disease", "Disease Pathway", "Familiarity", "Foundations", "Funding", "Funding Agency", "Future", "Goals", "Grant", "Industry", "Institutes", "Lupus", "Mediation", "Medicine", "Mental Health", "Mission", "Non-Insulin-Dependent Diabetes Mellitus", "Nonprofit Organizations", "Paper", "Parkinson Disease", "Phase", "Policies", "Private Sector", "Privatization", "Public Health", "Research", "Research Personnel", "Resources", "Rheumatoid Arthritis", "Schizophrenia", "Science", "Secure", "Speed", "Structure", "Subgroup", "Therapeutic Intervention", "Time", "Training", "Transact", "United States", "United States Food and Drug Administration", "United States National Institutes of Health", "Universities", "Vaccines", "Work", "authority", "cost", "design", "experience", "improved", "programs", "public-private partnership", "response", "therapeutic development", "therapeutic vaccine" ], "approved": true } }, { "type": "Grant", "id": "9121", "attributes": { "award_id": "3UM1AI148575-01S2", "title": "Vaccine and Treatment Evaluation Units (VTEU)", "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": [ { "id": 7539, "first_name": "Marina", "last_name": "Lee", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-13", "end_date": "2022-11-30", "award_amount": 5921655, "principal_investigator": { "id": 9706, "first_name": "HANA M", "last_name": "EL SAHLY", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 566, "ror": "https://ror.org/02pttbw34", "name": "Baylor College of Medicine", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 566, "ror": "https://ror.org/02pttbw34", "name": "Baylor College of Medicine", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This supplement request is for a Phase 3, randomized, stratified, observer-blind, placebo- controlled study to evaluate the efficacy, safety and immunogenicity, of mRNA-1273 vaccine compared to placebo in adults 18 years of age and older who have no known history of SARS- CoV-2 infection but whose locations or circumstances put them at appreciable risk of acquiring COVID-19 and/or SARS-CoV-2 infection. This request also relates to other COVID 19 activities.", "keywords": [ "18 year old", "2019-nCoV", "Adult", "COVID-19", "Evaluation", "Infection", "Location", "Messenger RNA", "Phase", "Placebos", "Randomized", "Recording of previous events", "Risk", "Safety", "Vaccine Clinical Trial", "Vaccines", "blind", "immunogenicity", "placebo controlled study" ], "approved": true } }, { "type": "Grant", "id": "15659", "attributes": { "award_id": "2416898", "title": "BPC-AE: STARS Computing Corps: Extending a National Community of Practice for Developing BPC Change Leaders", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "CISE Education and Workforce" ], "program_reference_codes": [], "program_officials": [ { "id": 7542, "first_name": "Subrata", "last_name": "Acharya", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-01-01", "end_date": null, "award_amount": 5924905, "principal_investigator": { "id": 3184, "first_name": "Jamie", "last_name": "Payton", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 277, "ror": "https://ror.org/00kx1jb78", "name": "Temple University", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 15557, "first_name": "Tiffany M", "last_name": "Barnes", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 29210, "first_name": "Susan", "last_name": "Fisk", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 29675, "first_name": "Clarissa A", "last_name": "Thompson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 32167, "first_name": "Veronica M", "last_name": "Catete", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 228, "ror": "https://ror.org/05e74xb87", "name": "New Jersey Institute of Technology", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true }, "abstract": "The New Jersey Institute of Technology will extend STARS Computing Corps BPC Alliance. STARS aims to address the challenge of increasing the number and representation of Black, Hispanic, and women students who graduate with computing degrees and who remain in the field of computing after graduation. STARS serves as a national resource for transforming computer science and artificial intelligence education. Through this extension, STARS will continue its national community of practice and associated resource center to build capacity in college computing departments for developing more inclusive computing and AI educational experiences. This work builds upon a multi-year study, which provided evidence that the STARS Computing Corps approach is effective for broadening participation in computing goals, and indicates the value of a community of practice that engages college computing and AI faculty and students with a shared commitment. Ultimately, the work of STARS has the potential to increase student persistence in computing and AI research, degree programs, and careers. STARS creates significant knowledge, institutional, and human resources that can increase the reach of BPC research to a larger audience of researchers, educators, and K-20 students, and builds capacity to dramatically increase the number of people taking action in efforts to broaden participation in computing. STARS conferences, programs, and networks propagate evidence-based BPC approaches and advance peer-reviewed BPC scholarship. The key indicator for STARS impact is increased persistence for Black, Hispanic, and women students (and intersections thereof) in computing degree programs in institutions of higher education.This extension will 1) include new members and partnerships that expand the reach of STARS and that emphasize participation of Black and Hispanic students and faculty; 2) build capacity for evidence-based BPC practices for K12-university partnerships; 3) establish connections to STARS Alumni in industry to support professional networking and mentoring for current STARS students and to promote the persistence of STARS Alumni in the computing workforce. The project will also research: 4) how the STARS system of BPC interventions have longitudinal impacts on persistence in computing degree programs and the computing workforce with sample sizes that uniquely enable analyses of differential impacts at intersections of race, ethnicity, and gender, 5) how to adapt interventions to consider the changing landscape of needs for BPC, including changing university demographics, legislation that impacts BPC initiatives in higher education, the impacts of COVID on college student and faculty engagement, and the need to advance AI education, and 6) how to provide inclusive computing education experiences in the context of HBCUs, eHSIs, and community colleges. Finally, this extension will enable further research on broadening participation in computing, by providing early research opportunities for undergraduate students from underrepresented groups in computing and advancing dissemination of BPC research through the RESPECT and STARS Celebration conferences. This 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": "9418", "attributes": { "award_id": "1U24LM013755-01", "title": "RADx-Rad Discoveries & Data: Consortium Coordination Center Program Organization", "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": 10715, "first_name": "YANLI", "last_name": "WANG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-21", "end_date": "2022-11-30", "award_amount": 5954423, "principal_investigator": { "id": 25146, "first_name": "Eliah S", "last_name": "Aronoff-Spencer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 760, "ror": "https://ror.org/0168r3w48", "name": "University of California, San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 23731, "first_name": "LUCILA", "last_name": "OHNO-MACHADO", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 25147, "first_name": "HUA", "last_name": "XU", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 760, "ror": "https://ror.org/0168r3w48", "name": "University of California, San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "ABSTRACT Preparing SARS-CoV-2 testing data for reuse requires making the data syntactically and semantically equivalent. Standardization of terminologies and a common data model accomplish the former, while the latter is accomplished through understanding the data and making it comparable across RADx-rad awardees by benchmarking against known gold standards. The standardization of samples is as important as standardizing the data, particularly in the highly innovative RADx-rad program, where new technologies will be developed or optimized for deployment in various settings. Highly motivated RADx-rad awardees will receive advice on how their diagnostics compare to FDA-approved ones, with each other, how their diagnostic performs in independent testing, as well as how to ensure the tests are usable in real world settings. In collaboration with University of Texas Health Science Center at Houston, University of California San Diego researchers in informatics/data science and infectious diseases with ample experience in leading large consortia have designed a unique RADx- rad Consortium Data and Coordination Center (radCDCC). This center is based on three pillars: (1) effective administration and coordination among awardees, NIH, and other programs;; (2) innovative approaches and tools to collect and standardize data and metadata to promote findability, accessibility, interoperability and reuse (FAIR) for data sharing;; and (3) principled preparation of standardized samples with known quantities of viral loads, and standardized procedures for testing new diagnostics to allow comparison across tests and calibration of new technologies. Backed by sophisticated HIPAA-compliant cloud services, user friendly web-tools, and extensive support from UCSD’s facilities for computation and for clinical research, the radCDCC will interface with other RADx programs and other COVID-19 focused programs at NIH to ensure alignment of awardees, NIH and the public in the pursuit of effective, affordable, and deployable new technologies for testing.", "keywords": [ "Agreement", "Antibodies", "Area", "Award", "Back", "Benchmarking", "Biological Assay", "COVID-19", "COVID-19 diagnostic", "COVID-19 pandemic", "COVID-19 testing", "Calibration", "California", "Clinical Pathology", "Clinical Research", "Cloud Computing", "Cloud Service", "Collaborations", "Communicable Diseases", "Communication", "Communities", "Computer software", "Consultations", "Data", "Data Collection", "Data Coordinating Center", "Data Discovery", "Data Science", "Data Scientist", "Data Sources", "Development", "Diagnostic", "Diagnostic tests", "Ensure", "Evaluation", "FAIR principles", "FDA approved", "Funding", "Goals", "Gold", "Health Insurance Portability and Accountability Act", "Health Sciences", "Informatics", "Internet", "Knowledge", "Laboratories", "Logistics", "Metadata", "Methods", "Online Systems", "Persons", "Positioning Attribute", "Preparation", "Privacy", "Procedures", "Process", "Protocols documentation", "Quality Control", "RADx", "RADx Radical", "Reporting", "Research Personnel", "Resources", "Risk", "Role", "SARS-CoV-2 infection", "Sampling", "Science", "Secure", "Security", "Semantics", "Signal Transduction", "Specialist", "Specimen", "Standardization", "Structure", "Technology", "Terminology", "Testing", "Texas", "Time", "United States National Institutes of Health", "Universities", "Update", "Validation", "Viral", "Viral Load result", "Virus", "Work", "base", "dashboard", "data access", "data centers", "data exchange", "data management", "data modeling", "data reuse", "data sharing", "data standards", "design", "diagnostic technologies", "distributed data", "expectation", "experience", "help-seeking behavior", "indexing", "innovation", "meetings", "member", "new technology", "news", "novel diagnostics", "programs", "quality assurance", "repository", "search engine", "syntax", "testing services", "tool", "transmission process", "user centered design", "user-friendly", "virology" ], "approved": true } } ], "meta": { "pagination": { "page": 1384, "pages": 1405, "count": 14046 } } }