Since their inception in the latter part of the 20th Century, lateral flow assays have evolved from being single target qualitative tests into producing multiplexed quantitative results often incorporating lateral flow reader technology.
Lateral flow readers use predefined algorithms and calibration curves to translate the colour intensity of the lateral flow test line into a quantitative result. The application and the setting of the analysis of the test will determine what data is produced and what it represents.
Utilising reader technology means LFDs can be either semi-quantitative or fully-quantitative. With some assays the data produced will be based on approximate thresholds and will only display a level such as low, medium or high, thus being a semi-quantitative result. In the case of fully quantitative assays, readers produce exact numerical data based on the density of the test line. An example of a fully quantitative assay is Seralite®– FLC.
Quantitative lateral flow test development is a considerable step forward from developing a qualitative test. Translating a test line(s) into numerical data requires expert development capabilities and experience in a variety of disciplines.
There are several important elements to consider when developing a quantitative lateral flow assay. In a recent interview, our Assay Development Manager explained some of the key considerations, such as calibration curve selection, the suitability of raw materials and the quality of available lateral flow reader technology.
Abingdon Health has a dedicated team of assay and reader development scientists who have experience in producing semi-quantitative and fully-quantitative assays. Abingdon Health develops and manufactures lateral flow immunoassays for multiple industry sectors, under ISO 9001:2015 and ISO 13485:2016 certification and GMP compliance.
Contact us on +44 (0) 1904 406082 or email@example.com to see how Abingdon Health can help you achieve your quantitative ambitions for your lateral flow assay.
Published 2nd October 2018
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