Desktop Digital Biomarker Analysis System


The Desktop Digital Biomarker Analysis System is a point-of-care precision device for rapid diagnosis of up to 14 blood biomarkers and diseases.

Value Proposition

Current test methods (ELISA) are insufficient to continuously monitor acute conditions like sepsis, cardiac arrest, kidney and liver disease.  The Desktop Digital Biomarker Analysis System delivers simple, rapid testing for up to 14 biomarkers in as little as 30 minutes.  With its speed, power and precision, our system has the potential to usher in a new era of precision medicine for critical care. 

The initial target market for the Desktop Digital Biomarker Analysis System is researchers and clinicians in a human or animal lab setting looking to increase monitoring potential, discover better treatment outcomes, and/or reduce overall cost per test.

Associated Products

Military or healthcare facilities with limited lab resources would benefit from our Portable Disease Detection System, which trades the multiplex power of the Desktop system for a portable, battery-powered device.

Competitive Advantage

Point-of-care users simply deposit blood samples into the microfluidic chip, where it is processed and results are displayed onto any computer via customized software.

  • Lightweight, 14”x14”, local integration with existing computers near research or point-of-care

  • Lower the burden on in-house labs with speed and accuracy, cost-effective processing of samples in as little as 30 minutes

  • Utilizes an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting

  • Reduced errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations, moving away from plate-based (ELISA) sample processing

  • Enables longitudinal protein biomarker measurements for small animal studies (sample volume < 2 μL)

Unique Features

  • Real-time data for blood samples freshly collected from human patients or lab animals

  • Whole-blood assay; no spinning or processing of blood samples required

  • Spatial-spectral microfluidic encoding scheme

  • 14-plexed pro-inflammatory biomarker detection at concentrations of < 10pg/mL

  • Rapid, direct cytokine measurement

  • Single-molecule sensitivity

  • Autonomous Image Analysis

  • It utilizes powerful, generalized digital assay technology to test for up to 14 biomarkers simultaneously.

Principal Investigators
Katsuo Kurabayashi, PhD

Licensing Manager
Michelle Larkin

Intellectual Property
• Invention Disclosure # 2019-323, 2020-324
• Patent Application Submitted

Solution Sheet
Download Solution Sheet (PDF)

An image of the prototype without casing, attached to a computer to demonstrate data output

The device prototype without external casing

MARKET OPPORTUNITY
Digital protein assays have great potential to advance immunodiagnostics because of their single-molecule sensitivity, high precision, and robust measurements. The rapid, sensitive, and low-input volume biomarker quantification enabled by the System is broadly applicable to monitoring of acute disease, enabling timely, personalized treatment. The system also has broad applications for animal testing with its small sample volume requirements, and it can be a future competitor for industry leading technology such as Luminex.

The Desktop Digital Biomarker Analysis System is currently available for licensing. Please contact the Licensing Manager, Michelle Larkin, for more information.

Funding History

$1,233,561 in non-dilutive funding

  • 2019 $299,500 National Science Foundation

  • 2019 $200,000 Cancer Research Institute

  • 2020 $734,061 NIH

  • Substantial additional departmental, school and center based support

Completed Milestones:

  • Basic Research "The Idea"

  • Alpha Prototype/MVP

  • Initial Testing

  • Proof of Concept


Funding Organizations

Publications

Biosensors & Bioelectronics, 2021

MedRxIV, 2020

Blood, 2021

A digital protein microarray for COVID-19 cytokine storm monitoring. Lab on a Chip, 21(2), 331-343, (2021) Y. Song, Y. Ye, S.-H. Su, A. Stephens, T. Cai, M.-T. Chung, M. K. Han, M. W. Newstead, L. Yessayan, D. Frame, H.D. Humes, B.H. Singer, K. Kurabayashi

Media Coverage

None at this time