Peptide-based point-of-care serodiagnosis of Lyme disease enabled by deep-learning

Artem Goncharov; Hyou-Arm Joung; Rajesh Ghosh; Kevin Ngo; Barath Palanisamy; Elizabeth J. Horn; Paul M. Arnaboldi; Raymond J. Dattwyler; Omai Garner; Dino Di Carlo; Aydogan Ozcan; Katarina Pejcinovic; Nicole Krockenberger

doi:10.1117/12.3002004

13 March 2024 Peptide-based point-of-care serodiagnosis of Lyme disease enabled by deep-learning

Artem Goncharov, Hyou-Arm Joung, Rajesh Ghosh, Kevin Ngo, Barath Palanisamy, Elizabeth J. Horn, Paul M. Arnaboldi, Raymond J. Dattwyler, Omai Garner, Dino Di Carlo, Aydogan Ozcan, Katarina Pejcinovic, Nicole Krockenberger

Author Affiliations +

Proceedings Volume PC12832, Optics and Biophotonics in Low-Resource Settings X; PC128320I (2024) https://doi.org/10.1117/12.3002004
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

Lyme disease (LD) is a tick-borne illness and can lead to severe health complications if left undiagnosed/untreated. This study introduces a novel approach to point-of-care testing for LD, utilizing deep-learning-enabled peptide-based serodiagnosis. 82 unique patient serum samples were used for validation, obtained from the Bay Area Lyme Disease Biobank and the CDC Lyme Serum Repository. Blinded test results demonstrated outstanding diagnostic performance, with 84.0% sensitivity and 96.3% specificity. By integrating deep learning techniques with a peptide-based sensing panel, this serodiagnosis offers a rapid (< 15 minutes) and cost-effective (< $0.5/test) platform for LD diagnostics, while minimizing cross-reactivity.

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Artem Goncharov, Hyou-Arm Joung, Rajesh Ghosh, Kevin Ngo, Barath Palanisamy, Elizabeth J. Horn, Paul M. Arnaboldi, Raymond J. Dattwyler, Omai Garner, Dino Di Carlo, Aydogan Ozcan, Katarina Pejcinovic, and Nicole Krockenberger "Peptide-based point-of-care serodiagnosis of Lyme disease enabled by deep-learning", Proc. SPIE PC12832, Optics and Biophotonics in Low-Resource Settings X, PC128320I (13 March 2024); https://doi.org/10.1117/12.3002004

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