Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1391&sort=-program_officials
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-program_officials", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1419&sort=-program_officials", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=-program_officials", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1390&sort=-program_officials" }, "data": [ { "type": "Grant", "id": "9231", "attributes": { "award_id": "75N93020C00054-0-9999-1", "title": "DEVELOPMENT OF THERAPEUTIC PRODUCTS FOR COVID-19", "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": "2020-09-01", "end_date": "2025-08-31", "award_amount": 14260074, "principal_investigator": { "id": 24970, "first_name": "JEFFREY", "last_name": "GLENN", "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": "To support the advanced development of a promising candidate therapeutic for NIAID Category A, B, and C Priority Pathogens or emerging infectious diseases. The research and development activities to be supported will allow the candidate therapeutic product to progress through the product development pathway, and include preclinical and IND enabling development activities, chemistry optimization/development, GMP manufacturing, and clinical safety and efficacy assessment.", "keywords": [ "2019-nCoV", "Advanced Development", "COVID-19", "Categories", "Chemistry", "Clinical", "Development", "Emerging Communicable Diseases", "National Institute of Allergy and Infectious Disease", "Pathway interactions", "Safety", "pre-clinical", "priority pathogen", "product development", "research and development", "therapeutic candidate", "therapeutic development" ], "approved": true } }, { "type": "Grant", "id": "9232", "attributes": { "award_id": "75N93020C00054-P00001-9999-1", "title": "DEVELOPMENT OF THERAPEUTIC PRODUCTS FOR COVID-19", "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": "2020-09-01", "end_date": "2025-08-31", "award_amount": 8955992, "principal_investigator": { "id": 24970, "first_name": "JEFFREY", "last_name": "GLENN", "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": "To support the advanced development of a promising candidate therapeutic for NIAID Category A, B, and C Priority Pathogens or emerging infectious diseases. The research and development activities to be supported will allow the candidate therapeutic product to progress through the product development pathway, and include preclinical and IND enabling development activities, chemistry optimization/development, GMP manufacturing, and clinical safety and efficacy assessment.", "keywords": [ "Advanced Development", "COVID-19", "COVID-19 therapeutics", "Categories", "Chemistry", "Clinical", "Development", "Emerging Communicable Diseases", "National Institute of Allergy and Infectious Disease", "Pathway interactions", "efficacy evaluation", "pre-clinical", "priority pathogen", "product development", "research and development", "safety assessment", "therapeutic candidate", "therapeutic development" ], "approved": true } }, { "type": "Grant", "id": "9233", "attributes": { "award_id": "75N91020C00036-0-9999-1", "title": "DIGITAL HEALTH SOLUTIONS FOR COVID-19: DIGITAL HEALTH PASS AND SMARTER CONTACT TRACING SOLUTIONS", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-09-14", "end_date": "2020-11-13", "award_amount": 792019, "principal_investigator": { "id": 24971, "first_name": "RON", "last_name": "GOETZEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of this project it to develop both a contact tracing and secure data exchange tools. The contact tracing solution securely combines data from a variety of sources (including manual self-report data, mobile device surveys, wearable devices, electronic health records) to enable tracing of contacts with individuals that have tested positive for COVID-19. The data exchange solution is a secure mechanism that empowers users to control the data they share in the course of their return to normal activities, including the ability to provide a verifiable health status claim. These tools are to be used by employers, government agencies, and others to evaluate the risk of allowing individuals to return to normal activities and also the ability to trace user contact with individuals diagnosed with or suspected of having contracted COVID-19. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.", "keywords": [ "COVID-19", "Contact Tracing", "Contracts", "Data", "Data Reporting", "Diagnosis", "Electronic Health Record", "Goals", "Government Agencies", "Health", "Health Status", "Individual", "Manuals", "Patient Self-Report", "Risk", "Secure", "Source", "Surveys", "Testing", "United States National Institutes of Health", "data exchange", "data hub", "data sharing", "digital", "handheld mobile device", "tool", "wearable device" ], "approved": true } }, { "type": "Grant", "id": "9234", "attributes": { "award_id": "75N91020C00036-P00001-9999-1", "title": "DIGITAL HEALTH SOLUTIONS FOR COVID-19: DIGITAL HEALTH PASS AND SMARTER CONTACT TRACING SOLUTIONS", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-09-14", "end_date": "2021-09-13", "award_amount": 4135490, "principal_investigator": { "id": 24971, "first_name": "RON", "last_name": "GOETZEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1810, "ror": "", "name": "INTERNATIONAL BUSINESS MACHINES CORP", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of this project it to develop both a contact tracing and secure data exchange tools. The contact tracing solution securely combines data from a variety of sources (including manual self-report data, mobile device surveys, wearable devices, electronic health records) to enable tracing of contacts with individuals that have tested positive for COVID-19. The data exchange solution is a secure mechanism that empowers users to control the data they share in the course of their return to normal activities, including the ability to provide a verifiable health status claim. These tools are to be used by employers, government agencies, and others to evaluate the risk of allowing individuals to return to normal activities and also the ability to trace user contact with individuals diagnosed with or suspected of having contracted COVID-19. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.", "keywords": [ "COVID-19", "Contact Tracing", "Contracts", "Data", "Data Reporting", "Diagnosis", "Electronic Health Record", "Goals", "Government Agencies", "Health Status", "Individual", "Manuals", "Patient Self-Report", "Risk", "SARS-CoV-2 positive", "Secure", "Source", "Surveys", "Testing", "United States National Institutes of Health", "data exchange", "data hub", "data sharing", "digital health", "handheld mobile device", "tool", "wearable device" ], "approved": true } }, { "type": "Grant", "id": "9237", "attributes": { "award_id": "75N93020C00053-P00001-9999-1", "title": "Development of a COVID-19 Vaccine", "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": "2020-09-01", "end_date": "2022-10-31", "award_amount": 1549907, "principal_investigator": { "id": 24974, "first_name": "RAYMOND", "last_name": "GOODRICH", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 323, "ror": "https://ror.org/03k1gpj17", "name": "Colorado State University", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 323, "ror": "https://ror.org/03k1gpj17", "name": "Colorado State University", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "To support the advanced development of candidate products for use following the intentional release of or in response to naturally occurring outbreaks of infectious diseases caused by NIAID Category A, B, and C Priority Pathogens or emerging infectious diseases. This contract may support formulation and manufacture of the individual vaccine components, as well as stability testing, nonclinical immunogenicity and efficacy testing in animal models, IND enabling GLP toxicology, submission of an IND and clinical safety and efficacy evaluation.", "keywords": [ "Advanced Development", "Animal Model", "COVID-19 vaccine", "Categories", "Clinical", "Communicable Diseases", "Contracts", "Development", "Disease Outbreaks", "Emerging Communicable Diseases", "Formulation", "Individual", "National Institute of Allergy and Infectious Disease", "Safety", "Toxicology", "Vaccines", "efficacy evaluation", "efficacy testing", "immunogenicity", "priority pathogen", "response", "stability testing" ], "approved": true } }, { "type": "Grant", "id": "9238", "attributes": { "award_id": "75N93020C00053-0-9999-1", "title": "Development of a COVID-19 Vaccine", "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": "2020-09-01", "end_date": "2022-04-30", "award_amount": 3099031, "principal_investigator": { "id": 24974, "first_name": "RAYMOND", "last_name": "GOODRICH", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 323, "ror": "https://ror.org/03k1gpj17", "name": "Colorado State University", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 323, "ror": "https://ror.org/03k1gpj17", "name": "Colorado State University", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "To support the advanced development of candidate products for use following the intentional release of or in response to naturally occurring outbreaks of infectious diseases caused by NIAID Category A, B, and C Priority Pathogens or emerging infectious diseases. This contract may support formulation and manufacture of the individual vaccine components, as well as stability testing, nonclinical immunogenicity and efficacy testing in animal models, IND enabling GLP toxicology, submission of an IND and clinical safety and efficacy evaluation.", "keywords": [ "Advanced Development", "Animal Model", "COVID-19", "COVID-19 vaccine", "Categories", "Clinical", "Communicable Diseases", "Contracts", "Development", "Disease Outbreaks", "Emerging Communicable Diseases", "Formulation", "Individual", "National Institute of Allergy and Infectious Disease", "Safety", "Toxicology", "Vaccines", "efficacy evaluation", "efficacy testing", "immunogenicity", "priority pathogen", "response", "stability testing" ], "approved": true } }, { "type": "Grant", "id": "9252", "attributes": { "award_id": "75N91019D00024-P00001-759102000025-3", "title": "International study on COVID-19 Vaccine to assess Immunogenicity, Reactogenicity and Efficacy (InVITE)", "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": "2020-09-28", "end_date": "2025-09-27", "award_amount": 8758469, "principal_investigator": { "id": 24984, "first_name": "SALLY", "last_name": "HUNSBERGER", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1610, "ror": "", "name": "LEIDOS BIOMEDICAL RESEARCH, INC.", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1610, "ror": "", "name": "LEIDOS BIOMEDICAL RESEARCH, INC.", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "This funding supports a multicenter study of COVID-19 vaccine immunogenicity and durability, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections in people who receive a COVID-19 vaccine through their country’s national vaccination programs. The study will be conducted in international sites including those that participate in the Division of Clinical Research Special Projects. This study is unique in that it examines the immunogenicity of multiple different vaccination regimens (both initial and booster) across several countries.", "keywords": [ "2019-nCoV", "Age", "Antibody Response", "Body mass index", "COVID-19 vaccine", "Clinical Research", "Country", "Data", "Funding", "HIV Infections", "Immunization Programs", "Infection", "International", "Measures", "Multicenter Studies", "Participant", "Regimen", "SARS-CoV-2 infection", "Site", "Subgroup", "Vaccination", "Vaccines", "Virus", "comorbidity", "immunogenicity", "study population", "viral genomics" ], "approved": true } }, { "type": "Grant", "id": "9254", "attributes": { "award_id": "75N91020C00038-P00004-9999-1", "title": "DIGITAL HEALTH SOLUTIONS FOR COVID-19: COVID COMMUNITY ACTION AND RESEARCH ENGAGEMENT (COVID-CARE)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-09-14", "end_date": "2021-09-13", "award_amount": 2927659, "principal_investigator": { "id": 24986, "first_name": "PRADUMAN", "last_name": "JAIN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1812, "ror": "", "name": "VIGNET, INC.", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1812, "ror": "", "name": "VIGNET, INC.", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of this project is to develop mobile applications, data integrations, and validated machine learning algorithms to identify COVID-19 and differentiate it from the flu, and to perform contact tracing using Wi-Fi technologies. Vibrent Health will accomplish this goal by enhancing their Vibrent Digital Health Solutions Platform (DHSP) implementation to large-scale pilot populations among diverse user groups. The project will focus on validating the technology’s performance, usability, and reliability in refinement of analytics to generate predictive algorithms for infection. The platform is intended to support individual, organizational, community, and societal-level decision-making in the COVID-19 pandemic response. The first objective involves innovation to develop a technology that can differentiate between COVID-19 and flu (or other respiratory illness). The second objective involves the development and testing of a Wi-Fi-based contact tracing tool using George Mason University’s enterprise Wi-Fi system. The third objective involves the development of a full technical integration approach and strategy to support data exchange. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.", "keywords": [ "Action Research", "COVID-19", "COVID-19 pandemic", "Caring", "Communities", "Community Actions", "Contact Tracing", "Data", "Decision Making", "Development", "Differential Diagnosis", "Goals", "Health", "Individual", "Infection", "Performance", "Population", "Secure", "System", "Technology", "Testing", "United States National Institutes of Health", "Universities", "base", "coronavirus disease", "data exchange", "data hub", "data integration", "digital health", "flu", "innovation", "machine learning algorithm", "mobile application", "prediction algorithm", "respiratory", "response", "tool", "usability", "wireless fidelity" ], "approved": true } }, { "type": "Grant", "id": "9255", "attributes": { "award_id": "75N91020C00038-0-9999-1", "title": "DIGITAL HEALTH SOLUTIONS FOR COVID-19: COVID COMMUNITY ACTION AND RESEARCH ENGAGEMENT (COVID-CARE)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-09-14", "end_date": "2021-01-13", "award_amount": 1098256, "principal_investigator": { "id": 24986, "first_name": "PRADUMAN", "last_name": "JAIN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1812, "ror": "", "name": "VIGNET, INC.", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1812, "ror": "", "name": "VIGNET, INC.", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of this project is to develop mobile applications, data integrations, and validated machine learning algorithms to identify COVID-19 and differentiate it from the flu, and to perform contact tracing using Wi-Fi technologies. Vibrent Health will accomplish this goal by enhancing their Vibrent Digital Health Solutions Platform (DHSP) implementation to large-scale pilot populations among diverse user groups. The project will focus on validating the technology’s performance, usability, and reliability in refinement of analytics to generate predictive algorithms for infection. The platform is intended to support individual, organizational, community, and societal-level decision-making in the COVID-19 pandemic response. The first objective involves innovation to develop a technology that can differentiate between COVID-19 and flu (or other respiratory illness). The second objective involves the development and testing of a Wi-Fi-based contact tracing tool using George Mason University’s enterprise Wi-Fi system. The third objective involves the development of a full technical integration approach and strategy to support data exchange. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.", "keywords": [ "Action Research", "COVID-19", "COVID-19 pandemic", "Caring", "Communities", "Community Actions", "Contact Tracing", "Data", "Decision Making", "Development", "Goals", "Health", "Individual", "Infection", "Performance", "Population", "Secure", "System", "Technology", "Testing", "United States National Institutes of Health", "Universities", "base", "coronavirus disease", "data exchange", "data hub", "data integration", "digital", "flu", "innovation", "machine learning algorithm", "mobile application", "prediction algorithm", "respiratory", "response", "tool", "usability", "wireless fidelity" ], "approved": true } }, { "type": "Grant", "id": "9262", "attributes": { "award_id": "75N91020C00040-0-9999-1", "title": "DIGITAL HEALTH SOLUTIONS FOR COVID-19: PERSONALIZED ANALYTICS WEARABLE BIOSENSOR PLATFORM FOR EARLY DETECTION OF COVID-19 DECOMPENSATION", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-09-14", "end_date": "2021-01-22", "award_amount": 2305814, "principal_investigator": { "id": 25003, "first_name": "KAREN", "last_name": "LARIMER", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1814, "ror": "", "name": "VGBIO, INC.", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1814, "ror": "", "name": "VGBIO, INC.", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of this project is to develop an artificial intelligence-based data analytics and cloud computing platform, paired with U.S. Food and Drug Administration (FDA)-cleared wearable devices, to create a personalized baseline index that could indicate a change in health status for patients who have tested COVID-19 positive. The project involves the development and validation of a COVID-19 Decompensation Index (CDI) that builds off physIQ’s existing wearable biosensor-derived analytics platform. Data will be collected from 400 human subjects that are both pre-hospitalization subjects (found to be positive for COVID-19) and subjects that have been hospitalized and treated for COVID and then discharged. This combined population will consist of COVID-19 decompensation cases (event cases) and cases for which COVID-19 did not result in any kind of decompensation (non-event cases). The 400-patient dataset will be partitioned into a training subset and a testing subset. Performance will be assessed using receiver operator characteristics (ROC) area under the curve (AUC) as the metric of performance. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.", "keywords": [ "Area Under Curve", "Artificial Intelligence", "Biosensor", "COVID-19", "Cloud Computing", "Data", "Data Analytics", "Data Set", "Development", "Early Diagnosis", "Event", "Goals", "Health", "Health Status", "Hospitalization", "Patients", "Performance", "Population", "Receiver Operating Characteristics", "Secure", "Testing", "Training", "United States Food and Drug Administration", "United States National Institutes of Health", "Validation", "base", "computational platform", "coronavirus disease", "data hub", "digital", "human subject", "indexing", "wearable device" ], "approved": true } } ], "meta": { "pagination": { "page": 1391, "pages": 1419, "count": 14184 } } }