Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=2&sort=awardee_organization
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=awardee_organization", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=awardee_organization", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=awardee_organization", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=awardee_organization" }, "data": [ { "type": "Grant", "id": "7666", "attributes": { "award_id": "1ZIAAT000036-03", "title": "Sociocultural & biobehavioral influences on pain expression and assessment", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Center for Complementary and Integrative Health (NCCIH)" ], "program_reference_codes": [], "program_officials": [], "start_date": null, "end_date": null, "award_amount": 143657, "principal_investigator": { "id": 23472, "first_name": "Lauren", "last_name": "Atlas", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "This protocol measures pain-related facial responses in a diverse population to measure whether nonverbal responses to pain vary as a function of biological and sociocultural factors. We will then measure whether individuals (both healthy volunteers and medical providers) pay attention to different features of pain or assess pain differently in in-group relative to out-group individuals, and whether we can develop interventions to reduce any biases in attention or pain assessment. This year, we continued data collection for our first sub-study on the protocol, and began to prepare stimuli for sub-studies 2 and 3. The first sub-study includes two visits for most participants. During the first visit, we assess eligibility via eligibility checklist, urine screen, nursing assessment, and a standard clinical interview diagnostic. During the second visit, we use video recording and facial electromyography to measure facial responses to painful stimuli. We administer three types of noxious stimuli: electric shock, thermal pain, and cold water. In FY20 we had 19 new participants complete at least one visit and 16 participants who completed all tasks (3 FY19 subjects completed in FY20). This places us at 87 total participants who have completed at least one visit and 64 participants who completed both visits. Data collection will be complete when we have 100 participants who have completed both visits. We are using specialized software to measure facial responses via video and to avoid implicit biases that could affect results if we used human coders. We will measure whether sex differences are observed in facial responses that are similar to sex differences in pain, as well as whether we see differences in facial responses or sex differences as a function of race, ethnicity, or identity centrality of race or sex. We have begun analyzing facial and autonomic data from the study to establish our data processing pipeline. Following completion, sub-study 1 participants are asked whether they want their images to be included in a database that will be shown to other participants. Images of participants who opt into this database will be used as stimuli for our subsequent sub-studies 2 and 3, which use eye tracking to measure how individuals (both naive participants and medical providers) view and judge pain in others that they perceive to be similar or different from them. Through this, we hope to gain insight on behavioral mediators of health disparities in pain. If we identify targets that contribute to differences in perceived pain, we will use these to develop interventions and see if individuals can improve accuracy in sub-study 3. We have begun making stimulus clips from participants who opted into the database and are in the process of designing sub-studies 2 and 3. Obviously the need to halt healthy volunteer research due to the COVID19 pandemic was a set-back for data collection progress on this protocol. However, we successfully shifted gears to focus on data analysis, as well as other experiments that involve online data collection. Fortunately we have received approval to resume healthy volunteer research. We are in the process of modifying this protocol to allow for screening and data collection through secure remote platforms prior to having participants visit NIH in person, which will reduce the duration of the face to face procedures and provide protection of both participants and laboratory staff. We have modified our experiment room so that participants and experimenters will be in different rooms and interact through a video monitoring and intercom system, thereby allowing us to ensure safety and complete sub-study 1 without obscuring facial responses due to masks. In addition to the data collection and analysis mentioned above, we published one commentary that is relevant to this line of research, in which we argued that studies of facial responses must include a diverse sample, particularly at this time when artificial intelligence is being trained on facial databases (Dildine & Atlas, 2019). We also have been preparing a systematic review on the relationship between pain and discrimination, and conducting several IRB-exempt online studies that measure perception of pain in computer generated facial expressions which are also relevant for this line of work.", "keywords": [ "Address", "Affect", "Artificial Intelligence", "Atlases", "Attention", "Back", "Behavioral", "Biological", "Biological Process", "COVID-19 pandemic", "Clinical", "Clip", "Code", "Computer software", "Data", "Data Analyses", "Data Collection", "Databases", "Diagnostic", "Discrimination", "Disease", "Electromyography", "Eligibility Determination", "Ensure", "Ethnic Origin", "Face", "Facial Expression", "Feedback", "Foundations", "Health", "Health Personnel", "Human", "Image", "Individual", "Institutional Review Boards", "Instruction", "Intervention", "Interview", "Laboratories", "Link", "Masks", "Measures", "Mediator of activation protein", "Medical", "Minority", "Monitor", "Nursing Assessment", "Outcome", "Pain", "Pain Measurement", "Pain Research", "Pain Threshold", "Pain management", "Participant", "Patients", "Persons", "Physiological", "Population Heterogeneity", "Procedures", "Process", "Protocols documentation", "Provider", "Psychophysiology", "Published Comment", "Publishing", "Race", "Reporting", "Research", "Research Design", "Safety", "Sampling", "Secure", "Series", "Sex Differences", "Shapes", "Shock", "Social Processes", "Stimulus", "Symptoms", "System", "Testing", "Time", "Training", "United States National Institutes of Health", "Urine", "Video Recording", "Visit", "Visual attention", "Water", "Work", "adverse outcome", "biobehavior", "computer generated", "data analysis pipeline", "design", "directed attention", "disadvantaged population", "efficacy testing", "experience", "experimental study", "health disparity", "healthy volunteer", "implicit bias", "improved", "insight", "pain perception", "pain reduction", "programs", "psychosocial", "response", "screening", "sex", "social", "social culture", "social factors", "social neuroscience", "systematic review", "therapy design", "visual tracking", "volunteer" ], "approved": true } }, { "type": "Grant", "id": "8834", "attributes": { "award_id": "75N95021P00635-0-0-1", "title": "Acquisition of Smile CDR FHIR-based clinical data repository Software. FY21 procurement.", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Center for Advancing Translational Sciences (NCATS)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2021-09-27", "end_date": "2022-09-26", "award_amount": 174000, "principal_investigator": { "id": 24646, "first_name": "CLEMENT", "last_name": "NG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "The NCATS National COVID Cohort Collaborative (N3C) Data Enclave, a centralized and secure data platform featuring powerful analytics capabilities for online discovery, visualization and collaboration for researchers studying COVID-19. The data are robust in scale and scope and are transformed into a harmonized data set to help scientists study COVID 19, including potential risk factors, protective factors and long-term health consequences. The N3C Data Enclave is anticipated to be one of the largest collections of data on COVID-19 patients in the United States. Data analysis within the enclave is supported by both R and Python, the most widely used open-source platforms for statistical analysis and data science. Researchers requesting access to, or working within, the enclave are encouraged to assemble collaborative teams with diverse expertise in such areas as clinical research, statistical analysis and informatics to make the best use of the N3C Data Enclave. A core tenet of the enclave is that it is both accessible and secure, allowing researchers to pursue research in a safe environment conducive to collaborative discovery while also allowing for the deployment of a wide variety of open source tools and components.", "keywords": [ "Area", "COVID-19", "COVID-19 patient", "Clinical Research", "Collaborations", "Data", "Data Analyses", "Data Collection", "Data Science", "Data Set", "Environment", "Fast Healthcare Interoperability Resources", "Health", "Informatics", "Pythons", "Research", "Research Personnel", "Risk Factors", "Scientist", "Secure", "Smiling", "Statistical Data Interpretation", "United States", "Visualization", "base", "clinical data repository", "cohort", "coronavirus disease", "data enclave", "data harmonization", "open source", "open source tool", "protective factors", "software repository" ], "approved": true } }, { "type": "Grant", "id": "6681", "attributes": { "award_id": "75N92021C00018-P00002-9999-1", "title": "RADX TECH 2375 - POINT OF NEED, SALIVA-BASED, COVID-19 TESTING PLATFORMS", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2021-07-01", "end_date": "2022-06-30", "award_amount": 12970000, "principal_investigator": { "id": 22379, "first_name": "DAVE", "last_name": "BEEBE", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "The key conceptual insight underpinning this proposal is that detecting individuals who are most likely to transmit SARS-CoV-2 is essential to mitigating the pandemic and reopening America. Our approach consciously contrasts with most existing nucleic acid testing platforms, which begin from the premise that maximizing detection sensitivity is the goal. We argue that striving for maximum sensitivity is at odds with the current needs for broad population based testing and that in a public health emergency, nucleic acid testing should be designed to maximize the number of people who can be tested for high viral loads consistent with shedding of live virus, in the greatest number of settings, at the lowest possible cost. To achieve this we couple a proven, ultrafast nucleic acid extraction method with rapid detection of amplified nucleic acids in an assay that can be both massively scaled in centralized reference labs and also used by point-of-care testing providers. The key enabling technology is a new, but proven, nucleic acid extraction method that reliably, quickly, and easily extracts, purifies, and concentrates viral RNA from a variety of sample types including nasal swabs and saliva in a highly parallel format. RNA prepared using this extraction method can be reliably amplified and detected using a simple colorimetric assay following isothermal amplification. These two technologies combined provide a testing platform that can enable millions of tests a week, at low cost, in both centralized laboratories and at point-of-care using technicians with no specialized training to support test/isolate/trace.", "keywords": [ "Americas", "Biological Assay", "COVID-19 testing", "Conscious", "Goals", "Individual", "Laboratories", "Methods", "Nucleic Acid Amplification Tests", "Nucleic Acids", "Persons", "Provider", "RADx Tech", "RNA", "SARS-CoV-2 transmission", "Saliva", "Sampling", "Technology", "Testing", "Training", "Viral Load result", "Virus", "amplification detection", "base", "cost", "design", "detection sensitivity", "insight", "isothermal amplification", "nasal swab", "pandemic disease", "point of care", "point of care testing", "population based", "public health emergency", "rapid detection", "viral RNA" ], "approved": true } }, { "type": "Grant", "id": "14008", "attributes": { "award_id": "75N91021F00056-P00005-0-1", "title": "Laboratory to Perform Assays of Coagulopathy Biomarkers for the National Cancer Institute’s COVID-19 in Cancer Patients Study (NCCAPS)", "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": "2023-03-01", "end_date": "2024-02-28", "award_amount": 155897, "principal_investigator": { "id": 24006, "first_name": "EDWARD", "last_name": "WONG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "Lab will conduct coagulopathy assays for NCI to analyze as part of a correlative science objective in NCI COVID-19 in Cancer Patients Study (NCCAPS): A Longitudinal Natural History Study, ClinicalTrials.gov Identifier: NCT04387656 https://clinicaltrials.gov/ct2/show/NCT04387656", "keywords": [ "Biological Assay", "Biological Markers", "Blood Coagulation Disorders", "COVID-19", "Cancer Patient", "Laboratories", "National Cancer Institute", "Natural History", "Science" ], "approved": true } }, { "type": "Grant", "id": "4102", "attributes": { "award_id": "NNX16AK48G", "title": "ASTEROID 2008 TC3 WAS TRACKED AND STUDIED IN SPACE FOR ~19 HOURS BEFORE IT IMPACTED EARTH'S ATMOSPHERE AND SHATTERED OVER NORTHERN SUDAN ON OCTOBER 7, 2008.WE WILL CONDUCT PETROLOGIC STUDIES, OXYGEN ISOTOPE ANALYSES, AR-AR DATING, AND SPECTROSCOPIC MEASUR", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2016-05-23", "end_date": "2017-05-22", "award_amount": 0, "principal_investigator": { "id": 13774, "first_name": "CYRENA", "last_name": "GOODRICH", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "ASTEROID 2008 TC3 WAS TRACKED AND STUDIED IN SPACE FOR ~19 HOURS BEFORE IT IMPACTED EARTH'S ATMOSPHERE AND SHATTERED OVER NORTHERN SUDAN ON OCTOBER 7, 2008.WE WILL CONDUCT PETROLOGIC STUDIES, OXYGEN ISOTOPE ANALYSES, AR-AR DATING, AND SPECTROSCOPIC MEASUR", "keywords": [], "approved": true } }, { "type": "Grant", "id": "9115", "attributes": { "award_id": "75N92020C00010-P00001-9999-1", "title": "RADX TECH - TALIS BIOMEDICAL HIGHLY SCALABLE SARS-COV-2 RNA DETECTION IN MINUTES", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-07-30", "end_date": "2021-07-29", "award_amount": 9750000, "principal_investigator": { "id": 24901, "first_name": "JENNIFER", "last_name": "BALDWIN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "With over $100M investment by the top biotech Venture Capital funds, NIH, CARB-X, and DARPA, Talis has developed ultrafast, sensitive, scalable technology uniquely suitable for COVID-19 testing. The Talis technology performs rapid (as fast as 6 minutes) purification of SARS-CoV-2 RNA from large volumes of human specimens including swabs and saliva and detects SARS-CoV-2 RNA in under 5 minutes for high positives and under 10 minutes near the limit of detection (~10 copies/reaction). Talis will deploy this technology in a high-throughput format for laboratories (Talis HT) and at the point-of-care (POC) for minimally trained users (Talis One). With RADx support, Talis will scale this technology in three stages: (1) In June, to accelerate throughput of the currently installed diagnostic equipment, Talis will deliver reagent kits for rapid SARS-CoV-2 detection in 96-well format. (2) In July, to further increase testing throughput, Talis will launch automation solutions for common diagnostic laboratory platforms, making kits for 4 million tests available. (3) In September, Talis will launch its rapid COVID-19 Talis One POC test on a multiplexed cartridge, expandable to include influenza. Operated by a compact Talis One instrument, this cartridge enables fully automated, sensitive SARS-CoV-2 RNA detection in under 20 minutes. Talis HT and Talis One will be adaptable to mobile testing for rapid response contact tracing, worker screening, and outbreak response. Talis is requesting RADx support to scale up and accelerate manufacturing of tests and will commit significant funds for cost-sharing.", "keywords": [ "2019-nCoV", "Automation", "Biotechnology", "COVID-19", "COVID-19 detection", "COVID-19 testing", "Capital Financing", "Contact Tracing", "Cost Sharing", "Detection", "Diagnostic", "Diagnostic Equipment", "Disease Outbreaks", "Funding", "Human", "Influenza", "Investments", "Laboratories", "RADx", "RADx Tech", "RNA", "Reaction", "Reagent", "Saliva", "Specimen", "Swab", "Technology", "Testing", "Training", "United States National Institutes of Health", "detection limit", "instrument", "point of care", "point of care testing", "rapid testing", "response", "scale up", "screening" ], "approved": true } }, { "type": "Grant", "id": "5334", "attributes": { "award_id": "NNX08AX76G", "title": "\"THE XMM-LSS SURVEY: RE-OBSERVATION OF A05 POINTINGS AFFECTED BY RADIATION\" We propose to re-observe 19 XMM-LSS AOS fields significantly affected by radiation during A05 operations. They are part of the XMM Large Programme dedicated to full coverage of th", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2008-07-23", "end_date": "2010-09-29", "award_amount": 0, "principal_investigator": { "id": 18724, "first_name": "CAROL", "last_name": "LONSDALE", "orcid": null, "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "\"THE XMM-LSS SURVEY: RE-OBSERVATION OF A05 POINTINGS AFFECTED BY RADIATION\" We propose to re-observe 19 XMM-LSS AOS fields significantly affected by radiation during A05 operations. They are part of the XMM Large Programme dedicated to full coverage of th", "keywords": [], "approved": true } }, { "type": "Grant", "id": "8122", "attributes": { "award_id": "75N92021C00009-0-9999-1", "title": "RADX TECH XTRAVA, INC. - SPERA COVID-19 AG TESTRAPID ACCELERATION OF DIAGNOSTICS (RADX) PROGRAM: TECH PROJECT #5834 XTRAVA, INC.", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2021-03-04", "end_date": "2022-03-03", "award_amount": 6207000, "principal_investigator": { "id": 23997, "first_name": "SAMEH", "last_name": "SARHAN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "Mitigating the economic and health challenges of COVID-19 is hindered by the absence of mass population testing. Available platforms are designed for lab-use and rely on sophisticated technologies and readers. They are slow, expensive, hard to manufacture and overload healthcare professionals with time consuming manual workflows; presenting massive obstacles to high throughput testing. We introduce a novel platform to diagnose COVID-19, which includes a digital test that combines fluorescent lateral flow assays with our patent-pending cost-optimized lateral flow test platform which was initially developed to detect H1N1. We have formed the essential alliances with key partners to rapidly scale up manufacturing and distribution to the points-of-need. Nasal swabs (and soon saliva samples) are tested in under 15 minutes. The digital results are wirelessly communicated to the participants’ mobile devices and the cloud thereby providing healthcare providers with test status and sharing real-time analytics and monitoring capabilities with health authorities. In the first stage, the test will be deployed into CLIA-waived point-of-care clinics, walk-in facilities and drive-thru testing centers for less than $35 for the digital test and with an effective cost of less than $10 per disposable test. After full validation, we will immediately extend deployment to at-home use by leveraging machine vision-guided self-testing. By combining IoT technologies that are proven to enable large-scale production with rapid diagnostic testing we believe we are uniquely positioned to increase testing throughput by 10X-100X. RADx re-enforcement will propel the launch of the system in highly condensed timeframes to meet the enormous need.", "keywords": [ "Acceleration", "COVID-19", "COVID-19 diagnosis", "Clinic", "Consumption", "Diagnostic", "Diagnostic tests", "Economics", "Health", "Health Personnel", "Health Professional", "Home", "Influenza A Virus H1N1 Subtype", "Legal patent", "Manuals", "Monitor", "Population", "Positioning Attribute", "RADx", "RADx Tech", "Rapid diagnostics", "Reader", "System", "Technology", "Testing", "Time", "Validation", "Walking", "Wireless Technology", "authority", "cost", "design", "digital", "handheld mobile device", "large scale production", "lateral flow assay", "machine vision", "manufacturing scale-up", "nasal swab", "novel", "point of care", "programs", "saliva sample", "self testing" ], "approved": true } }, { "type": "Grant", "id": "9483", "attributes": { "award_id": "316201200036W-P00009-27200001-4", "title": "COVID 19 Supplement: The Immunology Databse and Analysis Portal (ImmPort)", "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": "2019-09-30", "end_date": "2021-09-29", "award_amount": 286956, "principal_investigator": { "id": 25195, "first_name": "JEANETTE", "last_name": "FRANK", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "To develop a COVID-19 Data Compendium which will greatly support the COVID-19 research community by enabling secondary data reuse, large-scale meta-analysis, and interoperability across other COVID-19 data repositories.", "keywords": [ "COVID-19", "Collaborations", "Communities", "Data", "Data Set", "Immunology", "Meta-Analysis", "Metadata", "Research", "Resources", "Retrieval", "Visualization", "coronavirus disease", "data acquisition", "data and analysis portal", "data harmonization", "data modeling", "data repository", "data resource", "data reuse", "data standards", "interoperability" ], "approved": true } }, { "type": "Grant", "id": "11681", "attributes": { "award_id": "1U01DA057849-01", "title": "Supported employment to create a community culture of SARS-CoV-2 rapid testing among people who inject drugs: PeerConnect2Test", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": null, "end_date": null, "award_amount": null, "principal_investigator": { "id": 26966, "first_name": "Camille C", "last_name": "Cioffi", "orcid": "https://orcid.org/0000-0003-2424-7473", "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "['psi.uoregon.edu']", "desired_collaboration": "", "comments": "", "affiliations": [] }, "other_investigators": [], "awardee_organization": null, "abstract": "", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 2, "pages": 1392, "count": 13920 } } }