Real-time, smartphone-based processing of lateral flow assays for early failure detection and rapid testing workflows.

ABSTRACT: Despite their simplicity, lateral flow immunoassays (LFIAs) remain a crucial weapon in the diagnostic arsenal, particularly at the point-of-need. However, methods for analysing LFIAs still rely heavily on sub-optimal human readout and rudimentary end-point analysis. This negatively impacts both testing accuracy and testing times, ultimately lowering diagnostic throughput. Herein, we present an automated computational imaging method for processing and analysing multiple LFIAs in real-time and in parallel. This method relies on the automated detection of signal intensity at the test line, control line, and background, and employs statistical comparison of these values to predictively categorise tests as "positive", "negative", or "failed". We show that such a computational methodology can be

SUBMITTER: Colombo M 

PROVIDER: S-EPMC9850356 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature