Rapid, cost-effective, sensitive, and point-of-care disease sensors have become highly sought since the COVID-19 pandemic. We present an approach that achieves the sensitivity of nucleic acid amplification tests in less time. It combines an agglutination assay, lensfree microscopy, and machine learning. Antibody-coated beads sandwich virus particles and agglutinate depending on the viral concentration. By identifying particularly low levels of agglutination, we achieve a 1270 copies/mL limit of detection, comparable to polymerase chain reaction tests. Readout is performed in a cost-effective and compact device. This approach can be sped up further and used to identify other diseases in the future.
Here we present a point-of-care biosensor for the diagnosis and quantification of SARS-CoV-2 using a simple agglutination assay, portable lens-free holographic microscopy, and machine learning. We achieve a sensitivity near that of traditional PCR methods within 3 hours and with a simple 1- or 2-step assay. This sensor is capable of quantifying complex samples consisting of large viral particles and cell debris through its machine learning algorithm, implicating its use as an assay for similarly complex human samples.
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