Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1382&sort=-principal_investigator
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-principal_investigator", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=-principal_investigator", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1383&sort=-principal_investigator", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1381&sort=-principal_investigator" }, "data": [ { "type": "Grant", "id": "699", "attributes": { "award_id": "2035793", "title": "SBIR Phase I: Stress Pathway Inhibition Prevents COVID-19 Infection (COVID-19)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 1609, "first_name": "Kaitlin", "last_name": "Bratlie", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-15", "end_date": "2021-12-31", "award_amount": 255700, "principal_investigator": { "id": 1610, "first_name": "Donald J", "last_name": "Davidson", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 212, "ror": "", "name": "CREATIVE BIOTHERAPEUTICS LLC", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the pursuit of developing a first-in-class, non-toxic, inexpensive, and effective treatment for COVID-19 for vulnerable patients including the elderly and those at additional risk from cancer, high blood pressure, diabetes and obesity. These conditions produce high levels of stress on diseased cells compared to normal cells. This project leverages insights that COVID-19 uses the same pathway to enhance viral infection as cancer cells use for survival; this process causes immune system weakening which allows tumor cells and viruses to multiply. The proposed project will create innovative anti-viral therapies by exploring how this survival pathway increases COVID-19 infectivity, weakens the immune system and induces tumor cell resistance. Its use can be expanded to other new targets and therapies. This SBIR Phase I project leverages insights regarding similarities between tumors and viral infections. This project will advance translation of a novel inhibitor to a survival factor that continually keeps these wounds from healing by increasing tumor survival and enhancing viral infections. This novel inhibitor can potently block the binding of COVID-19 spike protein to this survival factor, which has been shown to be highly expressed on stressed lung cells as a result of cancer and other inflammatory diseases. The goals of this project are to 1) show that the proposed COVID-19 inhibitor can block COVID-19 infection of stressed lung cells; 2) reduce cytokine expression to lessen the cytokine storm associated with COVID-19 infection; 3) prevent immune weakening and 4) inhibit coagulopathy to lessen the “blood clot storm”. The project will use standard in vitro viral infectivity assays and in vivo immune competent tumor-bearing mice models infected with a lethal strain of COVID-19. Together, these studies will demonstrate that the proposed lead survival factor inhibitor can significantly reduce the attachment, entry and replication of COVID-19 virus as well as reduce the immune suppressive nature of infected lung alveolar epithelial cells in vitro and in vivo.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": "698", "attributes": { "award_id": "2042600", "title": "SCC-CIVIC-PG Track B: Co-creating Data for Disaster Resilience with Historically Marginalized Communities in Savannah.", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 1604, "first_name": "Sandip", "last_name": "Roy", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-15", "end_date": "2021-12-31", "award_amount": 49957, "principal_investigator": { "id": 1608, "first_name": "Allen", "last_name": "Hyde", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 294, "ror": "", "name": "Georgia Tech Research Corporation", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 1605, "first_name": "Yanni", "last_name": "Loukissas", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1606, "first_name": "Nisha D", "last_name": "Botchwey", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1607, "first_name": "Mildred", "last_name": "McClain", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 294, "ror": "", "name": "Georgia Tech Research Corporation", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "In coastal communities across the United States, environmental disasters such as flooding, hurricanes, and heatwaves have become increasingly common and costly, both in terms of human and economic impacts. The coronavirus pandemic is exacerbating these impacts and bringing inequalities to the fore. This project proposes to study the compounded effects of social and physical vulnerabilities to environmental disasters in Savannah, Georgia, as well as the local policies and practices that promote resilience and recovery. The proposed approach prioritizes social equity and justice by including residents and representatives of Hudson Hill, a lower-income black neighborhood in Savannah, as research partners. Together, the project will identify and co-create new sources of data on disaster vulnerability and resilience and foster broader stakeholder networks within the region. The team also includes researchers from Georgia Tech and Savannah State as well as officials from the City of Savannah Office of Sustainability and the Harambee House, an environmental justice organization. New forms of community-based data exploration, integration, and mapping are necessary to understand the impacts of compounded environmental disasters faced by residents of Savannah, Georgia, particularly marginalized communities. The project will use these new tools to identify what vulnerability and resilience mean in this context, and then reimagine the resilience networks that these communities need to bounce forward from future disasters. The plan of work includes: 1) socially distanced workshops with communities and organizations; 2) preliminary data collection and archival research on resilience and vulnerability in the area; 3) the development of community-level research protections that bring social justice to data stewardship; 4) the of design community-centered but socially distanced data exploration and mapping techniques; and 5) collaborative grant-writing for the full project proposal. The intellectual merit of the project is to improve our understanding of disaster resilience in marginalized coastal communities and to establish new community-centered methods of data exploration and mapping that prioritize data justice. The following broader impacts are anticipated: 1) to highlight and strengthen existing strategies of disaster resilience in marginalized coastal communities; 2) to model how university partnerships might prioritize social equity and justice as they co-create data and put them into action; 3) to chart and establish a resilience network that can leverage data as planning tools for collective recovery and regeneration; and 4) to model new forms of inclusive and equitable community engaged research under social distancing conditions of COVID-19.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": "697", "attributes": { "award_id": "2043988", "title": "SCC-CIVIC-PG Track B: Equitable Food-Security: Disaster-resilient supply chains for pandemics and extreme weather events", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 1598, "first_name": "Sandip", "last_name": "Roy", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-15", "end_date": "2022-06-30", "award_amount": 49994, "principal_investigator": { "id": 1603, "first_name": "Ioannis A", "last_name": "Kakadiaris", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 1599, "first_name": "Hiba", "last_name": "Baroud", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1600, "first_name": "Aron B", "last_name": "Laszka", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 231, "ror": "https://ror.org/048sx0r50", "name": "University of Houston", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, { "id": 1601, "first_name": "Bruce A", "last_name": "Race", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1602, "first_name": "Casey P", "last_name": "Durand", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 231, "ror": "https://ror.org/048sx0r50", "name": "University of Houston", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "Food insecurity is the lack of consistent and reliable access to nutritious food needed for an active, healthy life. It is a significant problem in Harris County, Texas, where over 14% of households and 23% of children were food insecure at the beginning of 2020. This problem has been further magnified during recent devastating events, including Hurricane Harvey and the coronavirus (COVID-19) pandemic. It is unclear how the nutritional needs of Houston's vulnerable populations will be addressed amidst multiple disasters, including hurricanes and flooding, COVID-19, economic disruptions, and systemic food insecurity. The Houston Food Bank (HFB) serves the Greater Houston area and collaborates with over 1,500 partners to address families' needs experiencing food insecurity. Disaster preparation and response decisions have been mainly based on incomplete data, human intuition, and pro-bono input from consulting firms. The COVID-19 pandemic has further induced stresses on the organization’s funding and personnel. While the HFB has absorbed and adapted to flooding events and other disasters in the past, it envisions organizational transformation to engage in resilience-building strategies that go beyond current practice. Thus, there is an urgent and critical need for HFB and other such regional food banks to develop and utilize decision support systems that intelligently aid in disaster preparation, response, and performance measurement. Unaddressed, emergency food security supply chains are unlikely to ensure efficient, equitable, and effective distribution of food and related resources.The project’s goal is to improve the resilience of nonprofit food banks’ supply chains by developing and deploying methods and technology systems that enable food banks to fully prepare for disasters, respond to the needs of the communities impacted, and evaluate their performance during disasters. This planning grant involves the preparation of a detailed plan for the deployment of a research-centered socio-technical project to develop and implement decision-making tools that will facilitate integrated disaster planning between HFB and nonprofit agencies involved in food distribution. The specific objectives are to (1) Design organizational resilience indicators and mapping of food equity needs using different census data at low levels of aggregation (e.g., the CDC Social Vulnerability Index) and HFB’s client network, (2) Design a multilayer, complex network for HFB, consisting of interdependencies both upstream and downstream, (3) Design decision-making tools for disaster management using computational game theory and deep reinforcement learning, and (4) Design the collection of same-day privacy-preserving data from underserved and vulnerable populations over a potentially disrupted communication infrastructure.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": "696", "attributes": { "award_id": "2110109", "title": "RAPID: Curtailing Nosocomial Amplification of COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 1594, "first_name": "Katharina", "last_name": "Dittmar", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-02-01", "end_date": "2023-01-31", "award_amount": 195381, "principal_investigator": { "id": 1597, "first_name": "Eric", "last_name": "Lofgren", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 306, "ror": "https://ror.org/05dk0ce17", "name": "Washington State University", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 1595, "first_name": "Assefaw H", "last_name": "Gebremedhin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1596, "first_name": "Kasey", "last_name": "Jones", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 306, "ror": "https://ror.org/05dk0ce17", "name": "Washington State University", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true }, "abstract": "One of the populations hardest hit during an emerging epidemic are frontline healthcare workers. Infections in healthcare workers and in healthcare settings produce two separate but related challenges. The first, and most obvious, is that sick or dying healthcare workers cannot care for patients, causing labor shortages right at the moment when demand on a healthcare system is likely increasing due to the epidemic. The second problem is that, because of how difficult it is to control infections within hospitals, the epidemic itself can accelerate once it reaches the healthcare system, causing a rapid increase in the number of cases. Examples of this phenomena, which we call “nosocomial amplification”, are common, including both previous major coronavirus epidemics before COVID-19 (SARS and MERS) as well as Ebola. This project will seek to model and understand what factors within a hospital can prevent this from happening, to increase the resilience of healthcare systems. Outcomes from this effort will be informing behavioral guidelines for healthcare systems. Other broader impacts from this project include training and professional development opportunities for students.\tThe researchers will adapt an existing model of within-hospital infection transmission to COVID-19 and combine this model with a spatially explicit agent-based model of the healthcare facilities in the state of North Carolina. This approach allows for the representation both of the healthcare environment, as well as the community where initial cases are seeded, where healthcare workers can infect – and be infected by – their community, etc. It also allows for the modeling of facility-level impacts of state-level decisions and allows us to address the question of how to best protect the health of both patients and healthcare workers in an environment where both are at significant risk of infection and critical supplies such as PPE are not necessarily unlimited. Simultaneously, they will collect data from hospitals in the SHEA Research Network on the changes brought on to staffing and clinical practice from COVID-19, such as whether or not the ratio of nurses to patients has changed, as well as ascertaining to what extent modeling has been used in hospital decision making, and whether or not it has been useful in that role. This project will thus have both a robust and sophisticated model for the interaction between hospitals at a granular level and the surrounding community, as well as timely parameter estimates from a diverse array of hospitals on how COVID-19 has changed their practices, as well as how modeling might be better tailored to inform the control of both COVID-19 and future epidemics.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": "695", "attributes": { "award_id": "2041345", "title": "Collaborative Research: Ultrasensitive Nucleic Acid Sensing Tools Based on Cas Assays and Solid-State Nanopores", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 1592, "first_name": "Aleksandr", "last_name": "Simonian", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2024-02-29", "award_amount": 299574, "principal_investigator": { "id": 1593, "first_name": "Hsin-Chih", "last_name": "Yeh", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 156, "ror": "", "name": "University of Texas at Austin", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 156, "ror": "", "name": "University of Texas at Austin", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The urgent need for rapid, inexpensive, and convenient methods to detect viruses has been clearly evidenced by the onset of Covid-19, which caused the death of over 2 million prople worldwide from mid November 2019 to mid January 2021, and continues to take its toll on human life. The 2020 Nobel Prize winning CRISPR/Cas technology, which can be used to rapidly detect DNA sequences in any living organism, offers a promising approach. This approach has been pursued by many companies, but none to date has been able to match the sensitivity of the “gold standard” test (real-time polymerase chain reaction (RT-PCR)), which requires 4-6 hours for completion and costs ~$100 per test. Thus the goal of this project is to develop a method for SARS-CoV-2 (the virus responsible for the COVID-19) detection that is faster, cheaper, more sensitive, and more convenient than the methods presently used for SARS-CoV-2 detection. The project’s goals will be achieved by integrating CRISPR/Cas assays with cutting-edge technologies. Limitations of existing systems will be addressed using a number of advanced analysis tools, advanced devices, artifical inteligence, and novel nanomaterial probes to design an integrated nanopore-microfluidic device for use in point-of-care (POC) settings that is ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable to end users). Succesful development of this sensor platform will offer a wide range of other uses, as the principles behind it may be applied to other applications that are not related to SARS-CoV-2. The project creates excellent opportunities for interdisciplinary research, as it combines biochemistry, nanoengineering, photonics, and medicine. Outreach programs related to this exciting project will be offered to K-12 schools, attracting young minds and inspiring them to pursue science, technology, engineering and mathematics (STEM) degrees. The goal of this project is to develop a highly sensitive and reliable nucleic acid sensing tool based on CRISPR/Cas assays for SARS-CoV-2 detection. The research will reveal the cleavage activities of Cas enzymes on a variety of composite nanomaterial reporter designs. Solid-state nanopores will be optimized for reading the cleavage patterns of nanomaterial reporters in the Cas assays using a deep neural network to classify the cleavage signatures. Solid-state nanopore readout provides single-molecule quantification and also identifies molecular signatures within the translocating molecules, which has significant advantages over the standard readout methods of today (fluorescence, paper-strip, colorimetric, and electrochemical readout). Once the cleavage activities are understood, a variety of reporters whose cleavage patterns correspond to specific target sequences will be designed. Identification of the cleavage products will enable the development of an integrated nanopore-microfluidic device for use in POC settings that will demonstrate simultaneous nanopore and fluorescence readings of cleavage products in multiplexed CRISPR/Cas assays.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": "10752", "attributes": { "award_id": "2235455", "title": "DREAM Sentinels: Selection of aptamers that target viral variants with high specificity", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "BIOSENS-Biosensing" ], "program_reference_codes": [], "program_officials": [ { "id": 961, "first_name": "Aleksandr", "last_name": "Simonian", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-01-01", "end_date": "2025-12-31", "award_amount": 640000, "principal_investigator": { "id": 1593, "first_name": "Hsin-Chih", "last_name": "Yeh", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 156, "ror": "", "name": "University of Texas at Austin", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 26813, "first_name": "Yi", "last_name": "Lu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 156, "ror": "", "name": "University of Texas at Austin", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "To combat infectious diseases, this project will develop a versatile platform that has a much shorter turn-around time in generating a new capture molecule that specifically binds a new viral variant with high affinity. The investigators will further convert the captured molecule into a sensor for virus detection, and also turn it into a blocking molecule to neutralize the virus. The current selection process is time-consuming and labor intensive. The goal of this project is to develop a streamlined process that can rapidly target emerging viral variants with high affinity and specificity. The proposed work will advance our knowledge in virus sensing and therapeutics, establishing a quick-responsive biosensing/actuating All-In-One platform that can be easily adapted to address future infectious diseases. To increase impact, the investigators will work with local K-12 students in several outreach programs, with the goal of training the students to develop novel tools and encouraging them into a career path in science, technology, engineering and mathematics.\n\nDevelopment of aptamer sensors and therapeutics is hampered by the bottleneck in the workflow of current gold standard SELEX (systematic evolution of ligands by exponential enrichment), especially the counterselection process, which aims to eliminate the candidates that bind structurally similar relatives of the target. While the counterselection is key to selecting highly specific aptamers against a specific target, it is a time-consuming, labor-intensive process that often fails. To address this issue, this project will combine SELEX workflow with a complementary high-throughput chip selection approach that can fully characterize the binding affinity, kinetics and specificity of each aptamer variant in the library against a number of structurally similar viral targets. This total-analysis approach not only bypasses the need to perform counterselections but also allows selection of aptamers that can differentiate structurally similar viral targets. The virus-binding aptamers will then be integrated with novel fluorogenic aptamer design to create new sensors that light up upon binding the target viruses and can be turned into virus inhibitors that bind and block the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein from interacting with the angiotensin-converting enzyme 2 (ACE2) receptors on human host cells. The proposed research thus has both biosensing and bioactuation components that address new biological threats.\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": "694", "attributes": { "award_id": "2041340", "title": "Collaborative Research: Ultrasensitive Nucleic Acid Sensing Tools Based on Cas Assays and Solid-State Nanopores", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 1590, "first_name": "Aleksandr", "last_name": "Simonian", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2024-02-29", "award_amount": 279403, "principal_investigator": { "id": 1591, "first_name": "MinJun", "last_name": "Kim", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 370, "ror": "https://ror.org/042tdr378", "name": "Southern Methodist University", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 370, "ror": "https://ror.org/042tdr378", "name": "Southern Methodist University", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The urgent need for rapid, inexpensive, and convenient methods to detect viruses has been clearly evidenced by the onset of Covid-19, which caused the death of over 2 million prople worldwide from mid November 2019 to mid January 2021, and continues to take its toll on human life. The 2020 Nobel Prize winning CRISPR/Cas technology, which can be used to rapidly detect DNA sequences in any living organism, offers a promising approach. This approach has been pursued by many companies, but none to date has been able to match the sensitivity of the “gold standard” test (real-time polymerase chain reaction (RT-PCR)), which requires 4-6 hours for completion and costs ~$100 per test. Thus the goal of this project is to develop a method for SARS-CoV-2 (the virus responsible for COVID-19) detection that is faster, cheaper, more sensitive, and more convenient than the methods presently used for SARS-CoV-2 detection. The project’s goals will be achieved by integrating CRISPR/Cas assays with cutting-edge technologies. Limitations of existing systems will be addressed using a number of advanced analysis tools, advanced devices, artifical inteligence, and novel nanomaterial probes to design an integrated nanopore-microfluidic device for use in point-of-care (POC) settings that is ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable to end users). Succesful development of this sensor platform will offer a wide range of other uses, as the principles behind it may be applied to other applications that are not related to SARS-CoV-2. The project creates excellent opportunities for interdisciplinary research, as it combines biochemistry, nanoengineering, photonics, and medicine. Outreach programs related to this exciting project will be offered to K-12 schools, attracting young minds and inspiring them to pursue science, technology, engineering and mathematics (STEM) degrees. The goal of this project is to develop a highly sensitive and reliable nucleic acid sensing tool based on CRISPR/Cas assays for SARS-CoV-2 detection. The research will reveal the cleavage activities of Cas enzymes on a variety of composite nanomaterial reporter designs. Solid-state nanopores will be optimized for reading the cleavage patterns of nanomaterial reporters in the Cas assays using a deep neural network to classify the cleavage signatures. Solid-state nanopore readout provides single-molecule quantification and also identifies molecular signatures within the translocating molecules, which has significant advantages over the standard readout methods of today (fluorescence, paper-strip, colorimetric, and electrochemical readout). Once the cleavage activities are understood, a variety of reporters whose cleavage patterns correspond to specific target sequences will be designed. Identification of the cleavage products will enable the development of an integrated nanopore-microfluidic device for use in POC settings that will demonstrate simultaneous nanopore and fluorescence readings of cleavage products in multiplexed CRISPR/Cas assays.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": "693", "attributes": { "award_id": "2032023", "title": "STTR Phase I: Formulation of a COVID-19 mRNA Vaccine by Inverse Flash NanoPrecipitation", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 1587, "first_name": "Kaitlin", "last_name": "Bratlie", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-15", "end_date": "2022-02-28", "award_amount": 256000, "principal_investigator": { "id": 1589, "first_name": "Robert", "last_name": "Pagels", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 369, "ror": "", "name": "Optimeos Life Sciences, Inc.", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 1588, "first_name": "Rodney D", "last_name": "Priestley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 369, "ror": "", "name": "Optimeos Life Sciences, Inc.", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this this Small Business Technology Transfer (STTR) Phase I project is the development of a novel messenger ribonucleic acid (mRNA)-based vaccine for COVID-19. The fastest-to-clinic vaccine for COVID-19 was mRNA-based; however, there are no mRNA-based vaccines on the market currently. This is, in part, because this class of vaccines is difficult to optimize and manufacture at a large scale. If clinical trials are successful, hundreds of millions of doses will be needed in the U.S. alone. This STTR project aims to pioneer a novel technique to manufacture mRNA-based vaccines initially for COVID-19. This technology is highly modular, allowing for the better understanding and optimization of this class of vaccines. Importantly, this new technique can be scaled to manufacture the doses needed both for the current COVID-19 pandemic and in the case of future outbreaks. The flexibility and scalability of this platform technology provide a durable competitive advantage. Following demonstration of preclinical efficacy, the company will work with an established pharmaceutical partner for testing and manufacturing. Capturing 5% of the U.S. COVID-19 vaccine market would bring an estimated $125 million in revenue. This is a beachhead market, and, once successful, the company will expand into other mRNA-based vaccine and therapeutic markets.This Small Business Technology Transfer (STTR) Phase I project aims to develop an mRNA-based nanoparticle vaccine for COVID-19 without the use of cationic materials. Current formulation methods require cationic lipids or polymers to form charge-based complexes with the anionic mRNA. Charge-based assembly limits the accessible nanoparticle surface chemistries, a feature crucial to directing which cell types will be transfected and the resulting immune response. Additionally, mRNA is only a minor component of the resulting formulations. The proposed formulation method decouples the mRNA encapsulation from the nanoparticle surface in a two-step process. The method does not require cationic materials, allowing for mRNA loadings up to 5-times higher than those achievable through other routes. However, mRNA transfection has not previously been demonstrated without the use of cationic materials. This will be achieved by completing three key milestones: (1) optimize mRNA encapsulation, (2) vary surface coatings to enhance dendritic cell uptake, and (3) demonstrate efficient cell transfection. A highly loaded nanoparticle formulation that can efficiently target and transfect dendritic cells is desired. Following the completion of this Phase I work, this formulation may be applied to a SARS-CoV-2 spike protein-coding mRNA to produce a COVID-19 vaccine.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": "692", "attributes": { "award_id": "2035981", "title": "SBIR Phase I: Development of a Novel Biosensor to Accelerate Investigations of COVID-19 and the Gut Microbiome.", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 1585, "first_name": "Erik", "last_name": "Pierstorff", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-15", "end_date": "2021-06-30", "award_amount": 255658, "principal_investigator": { "id": 1586, "first_name": "Dylan", "last_name": "Nichols", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 368, "ror": "", "name": "BIOMESENSE, INC.", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 368, "ror": "", "name": "BIOMESENSE, INC.", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be advanced understanding of the interaction between SARS-CoV-2, COVID-19, and the human gut microbiome, potentially resulting in new treatment approaches for COVID-19 patients. This project will develop a novel biosensor to enable low-cost, highly standardized studies of links between the human gut microbiome and COVID-19 to help evaluate the performance of different therapeutic approaches, drugs, vaccines, and other clinical interventions. Finally, once this project is successfully completed, there is a longer-term opportunity to add detection capability to the technology, enabling real-time, at-home tracking of SARS-CoV-2 prevalence in stool samples of high-risk patients and their caretakers. This would enable the technology to become a continuous viral detection tool.The proposed project will advance a sensor to allow isolation and preservation of microbial RNA from stool samples. Existing technique preserve microbial DNA but are not sensitive enough to preserve the far less stable RNA. The project will evaluate candidate extraction and fixative reagents based on technical performance, length of RNA stability, reagent cost, and storage requirements. Simultaneously, the project will develop an advanced systems architecture enabling a scalable solution for widespread use.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": "691", "attributes": { "award_id": "2054858", "title": "RAPID: Modeling COVID-19 Coronavirus Vaccine and Nursing Homes", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 1583, "first_name": "Katharina", "last_name": "Dittmar", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-15", "end_date": "2022-12-31", "award_amount": 200000, "principal_investigator": { "id": 1584, "first_name": "Bruce Y", "last_name": "Lee", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 367, "ror": "https://ror.org/01d03cj21", "name": "Research Foundation of The City University of New York", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 367, "ror": "https://ror.org/01d03cj21", "name": "Research Foundation of The City University of New York", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Nursing Homes (NHs) have been hit particularly hard by the COVID-19 coronavirus pandemic, with NH residents accounting for nearly a quarter of all COVID-19 deaths. This project will help answer key questions about NHs, which are particularly vulnerable to COVID-19 coronavirus infections and may be key to slowing the pandemic, and COVID-19 coronavirus vaccines. NH residents may be at a higher risk for COVID-19 coronavirus infections due to their health status, frequent interactions, and close, community-like living quarters. Once infected, residents are also at risk of serious health outcomes as a result of age-related illnesses, advanced chronic conditions, and frailty. Moreover, previous work has shown how NHs are highly interconnected with other healthcare facilities in a region and how an infectious disease outbreak in one nursing home can quickly spread throughout a region. Thus, NHs could further fuel the overall pandemic. COVID-19 coronavirus vaccines are one potential intervention in NHs and this proposed project would help address important questions about COVID-19 coronavirus vaccines. There is a need to better delineate the vaccine characteristics (e.g., efficacy/effectiveness, duration of protection, cost) that vaccine developers should aim for and how best to use different types of vaccines should they reach the market. It will also be helpful to understand the impact of varying prioritization of different populations, coverage, and compliance. A broader impact of this project is a better understanding of how COVID-19 coronavirus spreads in NHs and the impact of vaccination and other interventions. This will help decision makers determine what prevention and control measures should be implemented in NHs and how to implement these measures. This project will entail the development of computational models of selected nursing homes (NHs) and their residents and personnel (including health professionals and staff). The models would represent the layouts of the NH, the specific residents and personnel, their characteristics, and their interactions. Simulations will consider an infected person in the NH transmitting the virus to others through direct contact or potentially through aerosol transmission or surface contamination. Simulation experiments would consider introduction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into the nursing home in different ways. This work will explore the effects and value of introducing different types of COVID-19 coronavirus vaccines to the NHs. For example, varying the efficacy, duration of protection, and other characteristics of the vaccine. Additionally, the models could explore the effects of varying vaccination coverage and compliance among different nursing home residents and personnel (e.g., what would happen if different types of residents received the vaccine at different times, which residents and personnel should be prioritized if vaccines are limited). Simulation experiments could also explore the effects of layering on different selected policies and interventions (e.g., wearing face masks, testing, and different types of social distancing) with and without COVID-19 coronavirus vaccines. Developing and attaching a COVID-19 clinical outcomes and costing model to each of the residents and personnel then can help calculate the economic impact and value of different vaccines, policies, and interventions.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 } } ], "meta": { "pagination": { "page": 1382, "pages": 1424, "count": 14236 } } }