Lateral flow immunoassay (LFIA) is one of the most successful and widely commercialised Rapid Diagnostic Test (RDT) for point-of-care testing. In most cases, it provides a qualitative (“yes/no”) answer. Quantification of LFIAs depends on the dynamic range of the calibration curve, which is typically around 1.5-2 orders of magnitude. The dynamic range of LFIA at the higher end of the calibration curve is limited by “hook effect”, according to which test line signal intensities reduce with increasing antigen concentration beyond a threshold. The “hook effect” may lead to either false negative results or underestimation of the concentration of the antigen being detected.
To address this problem, researchers in the lab of Bhushan Toley in the Department of Chemical Engineering developed a model which provided a fundamental understanding of how the antigen concentration in an LFIA affects the dynamics of signal development at the test and control lines. The rate of signal development at test and control lines was different for each of the antigen concentrations, which is a fundamental concept of chemical kinetics. Using time-lapse imaging, they then captured the corresponding rates at test and control lines and developed a novel method for expanding the dynamic range of LFIAs. Two parameters, the final test line intensity ‘Iend’ and ‘b’ (obtained using time-lapse imaging), were utilized to differentiate a wide range of antigen concentration.
The dynamic range of off-the-shelf pre-existing LFIAs were expanded to up to three orders of magnitude without making any modifications to the test device. The developed strategy requires only a cell phone camera, a time-lapse imaging app, and a small custom-made imaging box.
Reference:
Sathishkumar, N. & Toley, B. J. Development of an experimental method to overcome the hook effect in sandwich-type lateral flow immunoassays guided by computational modelling. Sensors Actuators B Chem. 324, 128756 (2020).
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