SBIR/STTR Research Award

Development and Validation of Efficient Algorithms for Real-Time Glucose Monitoring on a Multi-Sensor Integrated Platform

Award identifier 4d74775893519b7f2901fcbbf6f8f805551801298b96514e02bce5c8429ebbd1Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$284,999

Program and phase

SBIR · Phase I

Award year

2025

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Integrated Medical Sensors
Proposal award date
2025-09-01
Contract end date
2026-05-31
UEI
HJ46NHNMRF13
Solicitation number
PAR24-131
Topic code
NIDDK

Research abstract

The long-term goal of this project is to develop a scalable, user-friendly, and affordable continuous glucose monitoring (CGM) system to improve diabetes management. IMS has created the world’s smallest electrochemical analyte sensing platform using an application-specific integrated circuit (ASIC) based on Complementary Metal-Oxide Semiconductor (CMOS) technology. This design offers several advantages, including extreme miniaturization, enhanced signal-to-noise ratio (SNR), multi-sensor redundancy for better accuracy, and on-chip temperature calibration for improved reliability. The system leverages scalable semiconductor and flexible hybrid electronics manufacturing methods, increasing lot sizes by over 1000x compared to current CGMs, potentially simplifying factory calibration and reducing costs. It also provides superior performance, such as improved hypoglycemia accuracy, and usability benefits with a 5x smaller and 50% lighter transmitter compared to the Libre 3 CGM, allowing for a gentler skin adhesive that reduces irritation. IMS has demonstrated the core platform's functionality in humans through a First-In-Human (FIH) feasibility study presented at ADA 2023 and a second human study at ATTD 2024, and ADA 2025 showcasing multi-day sensor operation. This shows the significance of the platform for further NIH support. Currently, retrospective data processing is used to generate glucose readings from the device data. The Objective of this grant is to optimize these data processing algorithms to generate glucose readings from the IMS CGM while eliminating noise (de-noising) and combining multi-sensor data (fusion). IMS has shown that this is feasible. Upon demonstrating in vitro feasibility in Phase I, these algorithms will be tested in pre-clinical and clinical studies in Phase II. The project team includes the original inventors from the California Institute of Technology (Dr. Nazari, Dr. Rahman, and Mr. Sencan), along with seasoned researchers and industry experts such as Bill Van Antwerp (former CSO of Medtronic MiniMed), quality and IP expert John Heithaus, commercialization expert Paul Strasma (former CEO of Capillary Biomedical), clinical expert Dr. Anne Peters (Head of USC Diabetes Clinics), and biosensor expert Dr. Natalie Wisniewski (former CTO of Profusa, Inc.). The team will mentor Ms. Narges Honarvar Nazari in her transition from academic research into medical devices industry and entrepreneurship.

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

11 SBIR/STTR records share this UEI (2016–2025). Reported award amounts total $4,976,700. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

Department of Health and Human Services

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.