Quantitative Smartphone Reader Application for use with Lateral Flow Assays

Lateral flow assays (LFAs) are diagnostic tests where a liquid sample is applied to a small paper strip pre-patterned with reagents for detection of particular proteins, cells, chemical molecules or microorganisms. They are used for numerous applications including human health (e.g. infectious disease), animal health, agricultural and food monitoring and environmental.

Many existing tests are based on achieving a qualitative result i.e. the presence or absence of coloured lines thus a positive or a negative test result. But there are many other uses when determining how much of the analyte is present. For example, in human health testing of cardiac markers, in animal health, the use of antibiotics, in agriculture, mycotoxins in food.

There is a clear market need for a reader system that allows quantification with very high sensitivity. In addition, readers offer the potential to remove the subjectivity of reading qualitative tests visually. Whilst the current reader market is significant ($1.2bn; Source MarketsandMarkets LFA Market 2017-22) the opportunity to use readers is restricted by their cost and lack of portability.

A robust, precise, easy-to-use smartphone reader has the potential to take a significant share of the existing $1.2bn market by matching or bettering technical performance of desk-top readers whilst offering the benefits of being cheaper, more portable and with less environmental footprint. In addition, there is an opportunity to significantly expand the LFA reader market through enabling decentralised testing of LFAs that would previously have been performed in the laboratory.

We believe our smartphone reader technology ("AppDx") has the potential to lead this transformation of the LFA testing market and increase the democratisation and decentralisation of testing, through the use of this enabling technology. In this way digital technology has the potential to enhance the precision, personalisation and efficient delivery of care.

Such a system would also be applied to multiple sectors, including military and defence, animal health, environmental and agri-food.

Our project objective is to further develop and optimise the performance of our AppDx product to allow the launch of a fully quantitative best-in-class application into the LFA market. Our technology is based on a patent-filed neural network algorithm which has the potential to provide the level of precision and performance required to enable a significant increase in the adoption of this technology worldwide.

This project will fund the development of our fully quantitative AppDx product to allow commercial launch in three years.