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Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, and data processing, coupled with deep learning, can help improve POCT. To demonstrate the performance of our approach, we present a rapid and cost-effective paper-based high-sensitivity vertical flow assay (hs-VFA) for quantitative measurement of cardiac troponin I (cTnI), a biomarker widely used for measuring acute cardiac damage and assessing cardiovascular risk. The hs-VFA includes a colorimetric paper-based sensor, a portable reader with time-lapse imaging, and computational algorithms for digital assay validation and outlier detection. Operating at the level of a rapid at-home test, the hs-VFA enabled the accurate quantification of cTnI using 50 μL of serum within 15 min per test and achieved a detection limit of 0.2 pg/mL, enabled by gold ion amplification chemistry and time-lapse imaging. It also achieved high precision with a coefficient of variation of <7% and a very large dynamic range, covering cTnI concentrations over 6 orders of magnitude, up to 100 ng/mL, satisfying clinical requirements. In blinded testing, this computational hs-VFA platform accurately quantified cTnI levels in patient samples and showed a strong correlation with the ground truth values obtained by a benchtop clinical analyzer. This nanoparticle amplification-based computational hs-VFA platform can democratize access to high-sensitivity point-of-care diagnostics and provide a cost-effective alternative to laboratory-based biomarker testing.

As a global shift continues to occur in high burden diseases toward developing countries, the importance of medical diagnostics based on point-of-care testing (POCT) is rapidly increasing. However, most diagnostic tests that meet clinical standards rely on high-end analyzers in central hospitals. Here, we report the development of a simple, low-cost, mass-producible, highly sensitive/quantitative, automated, and robust paper/soluble polymer hybrid-based lateral flow biosensing platform, paired with a smartphone-based reader, for high-performance POCT. The testing architecture incorporates a polymeric barrier that programs/automates sequential reactions via a polymer dissolving mechanism. The smartphone-based reader with simple opto-mechanical parts offers a stable framework for accurate quantification. Analytical performance of this platform was evaluated by testing human cardiac troponin I (cTnI), a preferred biomarker for the diagnosis of myocardial infarction, in serum/plasma samples. Coupled with catalytic/colorimetric gold-ion amplification, this platform produced results within 20 min with a detection limit of 0.92 pg mL -1 and a coefficient of variation <10%, which is equivalent to the performance of a high-sensitivity standard analyzer, and operated within acceptable levels stipulated by clinical guidelines. Moreover, cTnI clinical sample tests indicate a high correlation ( r = 0.981) with the contemporary analyzers, demonstrating the clinical utility of this platform in high-performance POCT.

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest in developing COVID-19 serology tests to monitor population-level immunity. To address this critical need, we designed a paper-based multiplexed vertical flow assay (xVFA) using five structural proteins of SARS-CoV-2, detecting IgG and IgM antibodies to monitor changes in COVID-19 immunity levels. Our platform not only tracked longitudinal immunity levels but also categorized COVID-19 immunity into three groups: protected, unprotected, and infected, based on the levels of IgG and IgM antibodies. We operated two xVFAs in parallel to detect IgG and IgM antibodies using a total of 40 μL of human serum sample in