Automated, Deep Learning‐Enabled Immunoassay Microfluidic Cartridge for Viral Pathogen Detection

Enzyme-linked immunosorbent assays (ELISA) are recognized for their accuracy and versatility in disease diagnostics. However, conventional ELISA protocols rely on laboratory equipment, trained personnel, and established infrastructure, restricting their use to complex clinical environments, making them impractical for at-home diagnostics. Here, VISTA, a disposable, electricity-free microfluidic chip designed for immunoassay-based point-of-care diagnostic applications is reported. VISTA enables a bubbling immunoassay-based assay to be completed, sample-to-result, in under 45 min in non-laboratory settings. Using pressure-driven microfluidics, the device manipulates antibody-conjugated magnetic beads and platinum nanoparticles to execute a streamlined semiautomated immunoassay process with minimal user input. VISTA consolidates all steps, including sample processing and reagent addition, into a single, low-cost cartridge with user-friendly features to ensure proper operation. It pairs with an AI-enabled smartphone application, utilizing an adversarial neural network, that automatically interprets assay results from a smartphone image, eliminating the need for specialized expertise. The device's capability is demonstrated through the bubbling immunoassay to detect SARS-CoV-2 N antigen and HCV core antigen directly from 52 patient samples. VISTA's sensitivity is on par with lab-based ELISAs and surpasses conventional point-of-care technologies, detecting viral loads less than 10<sup>4</sup> copies mL<sup>-1</sup>. This solution provides sensitive and cost-effective diagnostics, ideal for use in low-resource settings.

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Publication Details

Journal
Advanced Materials Technologies
Published
2025-05-19
DOI
https://doi.org/10.1002/admt.202500025
Citations
2
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
1.35

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Automated, Deep Learning‐Enabled Immunoassay Microfluidic Cartridge for Viral Pathogen Detection

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2 citations
Advanced Materials Technologies
Biosensors and Analytical Detection
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article

Automated, Deep Learning‐Enabled Immunoassay Microfluidic Cartridge for Viral Pathogen Detection

Zhimin Yin, Raymond T. Chung, Manoj Kumar Kanakasabapathy, Joseph Hardie, Ahmed Shokr, Hadi Shafiee, Daniel R. Kuritzkes, E. Weinmann, Juhyeon Chun, Prudhvi Thirumalaraju, Sungwan Kim, Jane J. Kim, G.T. Gallagher, Aditya Vardhan Reddy Katkuri, J. Z. Li, Jorge Mera, Manasvi Alam, Harshitha Mariadoss Yuvaraj, Jack Minahan, Teertha Ayanji
article en
2 citations

Abstract

Enzyme-linked immunosorbent assays (ELISA) are recognized for their accuracy and versatility in disease diagnostics. However, conventional ELISA protocols rely on laboratory equipment, trained personnel, and established infrastructure, restricting their use to complex clinical environments, making them impractical for at-home diagnostics. Here, VISTA, a disposable, electricity-free microfluidic chip designed for immunoassay-based point-of-care diagnostic applications is reported. VISTA enables a bubbling immunoassay-based assay to be completed, sample-to-result, in under 45 min in non-laboratory settings. Using pressure-driven microfluidics, the device manipulates antibody-conjugated magnetic beads and platinum nanoparticles to execute a streamlined semiautomated immunoassay process with minimal user input. VISTA consolidates all steps, including sample processing and reagent addition, into a single, low-cost cartridge with user-friendly features to ensure proper operation. It pairs with an AI-enabled smartphone application, utilizing an adversarial neural network, that automatically interprets assay results from a smartphone image, eliminating the need for specialized expertise. The device's capability is demonstrated through the bubbling immunoassay to detect SARS-CoV-2 N antigen and HCV core antigen directly from 52 patient samples. VISTA's sensitivity is on par with lab-based ELISAs and surpasses conventional point-of-care technologies, detecting viral loads less than 10<sup>4</sup> copies mL<sup>-1</sup>. This solution provides sensitive and cost-effective diagnostics, ideal for use in low-resource settings.

Advanced Materials TechnologiesVol. 10(16)
Brigham and Women's Hospital (US), Harvard University (US), University of New Mexico (US), Cherokee Nation (US), Massachusetts General Hospital (US)
National Institutes of Health
Openalex Percentile: Top 20%
Biosensors and Analytical Detection
1.35
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