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Award details
- Awarding agency
- National Science Foundation
- Branch
- Not reported
- Recipient company
- Oraliva, Inc.
- Proposal award date
- 2025-08-15
- Contract end date
- 2027-07-31
- UEI
- LMZ2DG9M4RH6
- Solicitation number
- NSF 24-580
- Topic code
- BM
Research abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is to optimize an accurate and efficient early stage, point of care cancer diagnostic for commercialization and market entry. In 2020, the total cost of cancer care was nearly $210 billion dollars and current cancer diagnostics only allow for diagnosis during late stage disease, resulting in a large economic burden to patients, families, and healthcare providers. Commercialization of the company’s project allows for accurate early-stage cancer detection, enabling healthcare providers to give patients the most appropriate treatment to increase the chances of survival at a lower overall cost. The company’s project will also help increase the cancer diagnostics market size, adding to, for example, the cervical cancer diagnostic market, which was 4.5B USD in 2022, and is expected to increase with a projected compound annual growth rate of 5.7% by 2030. The company’s beachhead market includes dentists, gastroenterologists, and gynecologists. Further, the company has developed a strong partnership with Delta Dental and built relationships with researchers at the University of Miami, University of North Carolina Chapel Hill, and New York University Langone to expand the project to other indications and promote collaboration between academia and industry.
This Small Business Technology Transfer (STTR) Phase II project will advance the company’s project as an artificial intelligence (AI)-linked, point of care technology for the early detection of epithelial cancers. Current diagnostic tools including magnetic resonance imaging and computed tomography scans, as well as tissue biopsies/histology are expensive techniques most relevant for late-disease detection and are limited by low accuracy. The company offers a solution for early-stage epithelial cancer intervention through the project technology, which leverages a microfluidic engine and microscope/imaging capabilities. In the proposed objectives, the company will target the development of a next-generation AI-linked cytopathology technology that can detect epithelial cancers by first defining design specifications for an initial prototype of the project instrument, and by developing: cost-effective modular clinical decision screening apps to improve early detection/management of epithelial cancers, a generalized cytopathology interface tool with analytics, and deep learning capabilities for enhanced biomarker recognition. These objectives will promote the optimization of the project to accurately classify cell phenotypes, which is crucial for diagnosing and understanding the progression of disease. Ultimately, this work will yield an improved and commercial ready diagnostic tool for early cancer detection in US medical/dental markets.
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.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
Research funding history
4 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $3,097,868. Reported amounts are not federal obligations.
Phases: Phase II, Phase I
Agencies: Department of Health and Human Services, National Science Foundation
Agency intelligence
National Science Foundation
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