Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1419&sort=program_reference_codes
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=program_reference_codes", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=program_reference_codes", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1420&sort=program_reference_codes", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1418&sort=program_reference_codes" }, "data": [ { "type": "Grant", "id": "1663", "attributes": { "award_id": "2014713", "title": "SBIR Phase I: A smart wearable platform for remote respiratory monitoring: building better technologies for telemedicine in the age of COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8032" ], "program_officials": [ { "id": 4360, "first_name": "Alastair", "last_name": "Monk", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-01", "end_date": "2021-05-31", "award_amount": 224999, "principal_investigator": { "id": 4361, "first_name": "Jason", "last_name": "Kroh", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 642, "ror": "", "name": "Strados Labs, Inc.", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 642, "ror": "", "name": "Strados Labs, Inc.", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to create a smart wearable stethoscope platform as a new tool to remotely monitor patients affected by COVID-19. Many infected patients may not present with symptoms until it is too late. Remotely monitoring these patients for the development of cough and shortness of breath prior to presentation in respiratory distress is critical. Patients with existing cardiopulmonary disease are at increased risk of contracting viral or secondary bacterial pneumonia due to COVID-19, but it is challenging to continuously assess these patients’ lung sounds due to risks of healthcare worker exposure. There is a clear need for more effective ways to monitor patients’ respiratory health due to COVID-19 both in quarantined patients and those in acute care. This project allows for remote monitoring to help triage COVID-19 patients and reduce healthcare worker exposure.This Small Business Innovation Research (SBIR) Phase I project addresses the further development and optimization of an artificial intelligence-based wearable device that monitors and analyzes lung sounds in high ambient noise environments. Ambient noise affects the use of standard electronic stethoscopes. Many commercially available electronic stethoscopes address ambient noise by reducing dynamic range or by warning the user not to use the device in a high noise environment. These mitigation methods restrict the utility of these devices by limiting the information that can be obtained from the acoustic measurements. Additionally, susceptibility to ambient noise eliminates its potential use in the home environment. Ambient noise has been shown to degrade the effectiveness of machine learning algorithms trained in low-noise environments to accurately detect lung sounds. This project addresses issues with high ambient noise using novel and established techniques of passive noise cancellation, active noise cancellation, signal processing techniques, and machine learning algorithms. The optimal combination and integration of these solutions in a wearable respiratory monitoring platform will establish a useful tool for use in a variety of real-world environments. The success of this project will be measured by the improvement of the machine learning sensitivity metrics after system optimization.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": "1237", "attributes": { "award_id": "2027586", "title": "STTR Phase I: COVID-19: AI-based Development of Neutralizing Antibodies for SARS-CoV-2", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8032" ], "program_officials": [ { "id": 3180, "first_name": "Anna", "last_name": "Brady", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2020-11-30", "award_amount": 256000, "principal_investigator": { "id": 3182, "first_name": "Barry D", "last_name": "Olafson", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 561, "ror": "", "name": "Protabit LLC", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3181, "first_name": "Stephen L", "last_name": "Mayo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 561, "ror": "", "name": "Protabit LLC", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this STTR project will lead to the development of engineered antibodies for that can be used to provide passive immunity and treatment to patients infected with COVID-19. These neutralizing antibodies can also be administered as preventative measures for populations at high risk of contracting COVID-19. Such engineered antibodies present a wider range of potential solutions than those produced naturally in the human body, potentially allowing more effective solutions. The proposed combination of high-throughput screening, next-generation-sequencing and AI-based antibody design allows systematic exploration of vast ranges of antibody sequences. This platform technology will be highly responsive to future outbreaks of novel coronaviruses or mutated forms of existing coronaviruses. The technology will be a platform technology which is would be useful going forward for other therapeutics for different diseases beyond coronavirus. Solutions in this space are highly relevant due to the current ongoing COVID-19 pandemic.This STTR Phase I project proposes to greatly enable AI and machine learning antibody engineering approaches by providing the needed antibody sequence mutation binding data that will take AI-based antibody engineering to a new level. Currently available antibody datasets number in the thousands of datapoints and this project proposes to generate datasets that number in the tens of millions. The project will also be generating both positive and negative antibody binding data, leading to higher performing learned antibody binding models. This project allows testing the hypothesis that synthetic antibodies can be the equal of, or better than, naturally occurring antibodies for neutralizing SARS-CoV-2 infectivity. Nature has its own set of rules and limitations for generating antibodies and the propsoals' approach could potentially develop a much wider range of antibody variations. This work will be laser-focused on discovering a number of high-affinity antibodies targeting the receptor binding domain (RBD) of the SARS-CoV-2 spike protein through the combination of yeast-display, high-throughput FACS sorting and next-generation-sequencing. Combining these high-throughput data generation workflows with the latest deep neural networks will lead to a new methodology that can quickly and efficiently discover high performing antibodies, both for the current pandemic and others that may follow.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": "1247", "attributes": { "award_id": "2028008", "title": "SBIR Phase I: Accelerating Understanding of COVID-19 Biology and Treatment Via Scaled Medical Record and Biosimulation Analytics", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8032" ], "program_officials": [ { "id": 3206, "first_name": "Anna", "last_name": "Brady", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2020-11-30", "award_amount": 256000, "principal_investigator": { "id": 3207, "first_name": "Guha", "last_name": "Jayachandran", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 565, "ror": "", "name": "Onu Technology, Inc.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 565, "ror": "", "name": "Onu Technology, Inc.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to address information needs of the COVID-19 crisis by rapidly integrating research findings describing the chemistry of the virus and its treatment. The proposed project will deploy advanced computational methods at participating medical institutions to make patient records immediately available for study while maintaining institutional and patient privacy. While the initial focus is on ameliorating COVID-19, the proposed solution can be applied more generally to accelerate epidemiological studies, improving scientific knowledge and public health with faster timelines and lowered costs for personnel, computing capabilities, and data storage. This SBIR Phase I project proposes to rapidly expand and accelerate the accessibility of clinical and computational data to improve understanding of COVID-19. The proposed innovation will use cryptographic techniques, notably multiparty computation, to facilitate privacy-preserving cross-institutional querying of COVID-19 medical records. Improved access to petabytes of computational (simulation and model) data will speed research by allowing researchers around the world to probe the data. The effort will adapt and deploy decentralized computation techniques to enable distributed storage of many petabytes of virus molecular dynamics simulation data across computers around the world, in a verifiable manner that enables data analysis at the data location. The proposed dashboard will allow for secure queries of a combined dataset of participating institutions to quickly yield insight about the effect of various pre-existing conditions and medications on COVID-19. The effort will include verification and validation.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": "1504", "attributes": { "award_id": "2031813", "title": "SBIR Phase I: Secure blockchain communication for federal benefit assessments during COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8032", "8038", "8042" ], "program_officials": [ { "id": 3914, "first_name": "Alastair", "last_name": "Monk", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-09-01", "end_date": "2021-08-31", "award_amount": 256000, "principal_investigator": { "id": 3915, "first_name": "Aristotle M", "last_name": "Mannan", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 607, "ror": "", "name": "bosWell, Inc.", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 607, "ror": "", "name": "bosWell, Inc.", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to simplify how Americans in need of assistance during COVID-19 obtain government benefits in a secure, safe transaction. The platform will use new blockchain technologies for security. The platform will streamline eligibility screening, facilitate enrollment and expedite review timelines. Furthermore, it will enable rapid access to disadvantaged populations.This Small Business Innovation Research (SBIR) Phase I project proposes to develop an end-to-end platform using distributed ledger technology (DLT) to facilitate transactions with the federal government in a secure fashion. Subsequently, the platform will consolidate redundancies into a uniform system. The proposed work will identify technical requirements and implement DLT.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": "1229", "attributes": { "award_id": "2027721", "title": "SBIR Phase I: MouthLab - A Medical Tricorder Optimized for Real-time, Rapid Assessment of COVID-19 Patients And Those At Risk", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8034" ], "program_officials": [ { "id": 3155, "first_name": "Anna", "last_name": "Brady", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2020-11-30", "award_amount": 256000, "principal_investigator": { "id": 3156, "first_name": "Sathya", "last_name": "Elumalai", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 558, "ror": "", "name": "MULTISENSOR DIAGNOSTICS, LLC", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 558, "ror": "", "name": "MULTISENSOR DIAGNOSTICS, LLC", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to advance the development of a novel, rapid COVID-19 symptoms assessment and real-time monitoring tool for individuals as well as infected patients and their care providers. The ability to detect all the early/progressive COVID-19 symptoms are invaluable to limit the rapid spread of disease and reduce the overwhelming demand for healthcare facilities, medical supplies, and front-line personnel. Currently, clinical care for COVID-19 is limited to hospitals and traditional healthcare facilities. Unfortunately, physicians still use temperature or subjective symptom data as the sole predictor of infection/disease status. This project will demonstrate a hand-held device to measure 10+ vital health parameters relevant to COVID-19 in just 30 seconds, and a cloud-based triage platform that leverages AI and machine learning algorithms to create a unique remote-monitoring solution for people who are infected or susceptible to life-threatening complications due to COVID-19. This SBIR Phase I project proposes to customize a device and platform for remote detection and management of COVID-19. This project will advance the development of a device design for remote use and modify the communication protocol to allow the platform to function reliably, even in areas with low cellular network connectivity. Secondly, the project will design a user interface to include a health status indicator via a weighting system optimized for specific parameters (e.g. breathing rate, SpO2, spirometry, temperature). This will enable even general users to understand their health/disease trends based on underlying data and analytics. The proposed project aims to build secure APIs for integrating with existing EMRs to provide data to health systems and federal agencies. Finally, the project will develop an integrated COVID-19 surveillance/triage dashboard for providers and military medics to receive real-time biometric data across populations and geographies to ensure timely intervention and treatment modification.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": "1705", "attributes": { "award_id": "2027693", "title": "STTR Phase I: Autonomous Disinfecting Robot for Crowded Spaces", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8034" ], "program_officials": [ { "id": 4466, "first_name": "Anna", "last_name": "Brady", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2021-05-31", "award_amount": 256000, "principal_investigator": { "id": 4467, "first_name": "Chinmay", "last_name": "Soman", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 668, "ror": "", "name": "EarthSense, Inc.", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 668, "ror": "", "name": "EarthSense, Inc.", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is to respond to the COVID-19 pandemic. The proposed work will rapidly create new autonomous robots for sanitization in hospitals and other high-traffic areas with high risk of surface-borne pathogen transmission. The autonomous sanitizing system produced by this effort would fill a crucial void in ensuring hospital spaces are kept sanitized as the health care system scrambles to respond to the evolving COVID-19 crisis. In addition, the solution will be widely applicable in controlling Hospital Acquired Infections, affecting over 2 million people in the US annually, with an overall economic impact of $45 B. The proposed autonomous high-dexterity robots are projected to successfully keep the high-touch areas in about 10,000 square feet of commercial space reliably sanitized and could be applicable to the over 50 billion square feet of public commercial space (office, industrial, healthcare, hospitality, retail, etc.) in the US. Faster, more efficient, and targeted santization has potential to dramatically reduce downtime of these spaces and the labor required for sanitization. This STTR Phase I project, in response to the ongoing COVID-19 crisis, will rapidly develop new robotic systems and algorithms for robots capable of precisely navigating surfaces in crowded environments. This new system will be capable of selective sanitization in the proximity of humans, removing the key limitation of existing full-room single-source UV radiation based robots requiring the room to be unoccupied. UV light technology has tremendous promise in improving sanitization at hospitals and reducing costs by minimizing chemical use, but the technology has had limited application due to ill effects on mammalian cells. The selective exposure capability with the use of the robotic arm and focused lighting will alleviate that limitation, opening up further uses of UV lighting in hospital sanitization. Toward this goal, this project will advance key areas of robotics, including Simultaneous Localization and Mapping (SLAM) algorithms in the presence of dynamic obstacles, and the control of arms over surfaces with varied objects and in the vicinity of humans. These efforts will advance the science and practice of robotics for applications in healthcare and other industries.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": "1683", "attributes": { "award_id": "2014753", "title": "STTR Phase I: Development and Commercialization of the SafeLight Family of Antimicrobial Materials for Combatting the COVID-19 Pandemic and Hospital Acquired Infections", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8038" ], "program_officials": [ { "id": 4409, "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": "2020-06-01", "end_date": "2021-12-31", "award_amount": 225000, "principal_investigator": { "id": 4411, "first_name": "Robert J", "last_name": "Sheehan", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 654, "ror": "", "name": "PHOTOCIDE PROTECTION, INC.", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4410, "first_name": "Reza A", "last_name": "Ghiladi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 654, "ror": "", "name": "PHOTOCIDE PROTECTION, INC.", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Technology Transfer (STTR) Phase I project is the development of new antimicrobial materials to reduce the spread of harmful bacteria and viruses in a variety of settings, particularly for self-disinfecting personal protection equipment against SARS-CoV-2 to combat the COVID-19 pandemic. While primarily intended for use in hospitals, these antimicrobial materials can also impact bio-defense; military facilities; food processing, packaging, and service industries; wastewater treatment facilities; daycare and long-term care facilities; and even personal households. Beyond the current pandemic, this technology can address hospital-acquired infections, which add an estimated $30-45 billion to health care costs every year; and the food service industry, where norovirus foodborne infections alone account for an economic loss of about $5.8 B annually in the United States. The proposed technology offers significant benefit for the current COVID-19 challenge and beyond. The proposed project will develop light-activated surface-disinfecting materials based on photodynamic inactivation that generates singlet oxygen – a highly reactive yet environmentally benign species – to cause non-specific damage to microbes, rendering them inactive. The technical challenges are: 1) the development of chemical species capable of producing singlet oxygen upon exposure to light, but stable at the high temperatures of manufacturing processes, for which we will start with a known class of compounds; 2) the development of a method for the production and embedding of the newly-developed photoreactive compounds within relevant materials, particularly for the manufacture of personal protection equipment; and 3) evaluation of process efficacy for virucidal (against coronaviruses), antibacterial, antimycotic and sporicidal 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": "1996", "attributes": { "award_id": "2029745", "title": "SBIR Phase I: Development and assessment of a diagnostic platform for rapid identification of COVID-19 patients without using custom reagents", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8038" ], "program_officials": [ { "id": 5334, "first_name": "Henry", "last_name": "Ahn", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-01", "end_date": "2020-12-31", "award_amount": 256000, "principal_investigator": { "id": 5335, "first_name": "Rajesh", "last_name": "Krishnamurthy", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 712, "ror": "", "name": "3I Diagnostics, Inc.", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 712, "ror": "", "name": "3I Diagnostics, Inc.", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to deploy a diagnostic to rapidly and inexpensively detect COVID-19 infections. Beyond the short-term goal of identifying COVID-19 patients, the technology will lend strong support for real-time infection tracking nationally. The same hardware components of the diagnostic can be used to identify a wide variety of pathogens without custom reagents. The system will work with a cloud-based database and monitoring system to rapidly identify hotspots of increased pathogen activity, enabling faster response to new pathogens since no hardware-related development, manufacturing, and distribution are needed. Once a new pathogen’s fingerprint is obtained, it can be easily distributed to deployed instruments to enable immediately tracking of the new pathogen. This Small Business Innovation Research (SBIR) Phase I project aims to develop a rapid diagnostic capable of detecting SARS-nCoV2 directly from sample matrices without the use of custom reagents (like DNA) or a cold supply chain. The approach isolates intact virus directly from the specimen with the help of a disposable cartridge and a syringe pump. The isolated virus is then identified using Fourier-Transform Infrared Spectrometry (FTIR). The proposed work leverages the differential response to mechanical stress between the virus and the components of a sample matrix. This differential response is used to selectively lyse only the sample matrix components, not the virus. The debris is subsequently separated from the virus by size-based separation methods such as filtration, enabling rapid isolation of a broad range of pathogens directly from the sample. FTIR is used to identify the isolated virus since pathogens exhibit unique spectral fingerprints in the infrared region. The proposed Phase I effort will develop the protocol for isolating and identifying intact virus and will demonstrate the performance with nasopharyngeal swab samples. The results will be compared against results from RT-PCR methods to assess comparability.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": "1245", "attributes": { "award_id": "2028187", "title": "SBIR Phase I: HaloFilm as a virucide against COVID-19 infection", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8038" ], "program_officials": [ { "id": 3202, "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": "2020-06-01", "end_date": "2021-02-28", "award_amount": 256000, "principal_investigator": { "id": 3203, "first_name": "Mingyu", "last_name": "Qiao", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 544, "ror": "", "name": "HALOMINE INC.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop an antiviral surface coating with unique application and efficacy features. Evidence suggests that the COVID-19 virus strain can remain live on stainless steel and plastic for as long as three days, a potentially harmful situation in environments with high traffic, such as subway turnstiles, buses, and high-touch surfaces in hospitals. Furthermore, even in hospitals, cleaning and disinfecting can be insufficiently comprehensive than desired, with surfaces that may easily be recontaminated until disinfectants are reapplied. The proposed technology enables chlorine-based disinfectants to be effective for as long as 4 weeks. The coating keeps chlorine in a physical and chemical state that is active against viruses, but remains safe and does not cause skin irritation upon contact. The coating can turn any surface into an antimicrobial, and antiviral, surface. The proposed SBIR Phase I project will assess the utility, efficacy and safety of a spray-on surface coating that is rechargeable and can be reapplied, such that it can be used as an antimicrobial surface coating, particularly to prevent transmission of coronaviruses. The state-of-the-art is to regularly use liquid spray disinfectants to kill viruses on surfaces. However, typical active ingredients, such as chlorine, quaternary ammonium compounds, alcohol, peracetic acid or hydrogen peroxide, are active against viruses for a matter of minutes and certainly less than an hour, leaving a surface that can potentially be recontaminated. The technical aims of the proposal focus on 1) assessing the virucidal activities of the coating at specific times after application; 2) determining the half-life of coronaviruses on the coating for comparison to other materials.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": "1246", "attributes": { "award_id": "2027985", "title": "SBIR Phase I: Large Scale Production of Antiviral Interferons for the Treatment of COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "8038" ], "program_officials": [ { "id": 3204, "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": "2020-06-01", "end_date": "2021-08-31", "award_amount": 256000, "principal_investigator": { "id": 3205, "first_name": "Ryan W", "last_name": "Shepherd", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 564, "ror": "", "name": "PhylloTech Inc.", "address": "", "city": "", "state": "WI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 564, "ror": "", "name": "PhylloTech Inc.", "address": "", "city": "", "state": "WI", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to advance the development of production for COVID-19 treatments. The COVID-19 pandemic is placing great strain on the supply chain for protein and antibody therapeutics and research products. Interferons represent a specific class of protein released in response to viral infections; they are currently being tested as important therapies to combat COVID-19 infections and to regulate the immune system. This project will develop a new system to produce and purify interferons using a new platform based on a plant system. No plant system has been utilized commercially to produce human interferons, due to product loss during purification from plant tissue. This system overcomes this challenge by secreting the proteins to leaf surfaces where they will easily be recovered. The rapid scalability of this plant-based system can allow fast production of COVID-19 therapeutics at high levels and lower cost than current protein expression systems. The proposed Phase I project will develop a photosynthetic platform for the production of COVID-19 therapeutics, as current production strategies are expensive to scale and limited in production capacity. Plants will be generated that produce and secrete interferons for the purposes of large-scale production. Further research efforts will be performed to determine if newly-identified trichome-specific promoters, intron-mediated expression elements, and unique protein secretion signals that are cleaved during protein maturation can optimize and enhance the system for interferon production. Plant-made interferons will be tested for activity and compared against interferons generated in other biomanufacturing systems.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": 1419, "pages": 1424, "count": 14236 } } }