Sensyne launches MagnifEye smartphone app to help lateral flow diagnostic tests


Sensyne Health plc, the Oxford-based Clinical AI technology company, has launched MagnifEye, a new smartphone software application that uses deep machine learning AI to automate the accurate reading, beyond the human visible spectrum, and Big Data analysis of lateral flow diagnostic tests.

MagnifEye draws on research & development at Sensyne over the past two years in applying deep learning AI to the analysis of medical images and Big Data analysis of clinical results across large patient populations.  The MagnifEye application was then built in response to the demand generated by the COVID-19 pandemic for the accurate and standardised reading of lateral flow tests used for disease surveillance across large populations and the Big Data analysis of results in real time. The IP underlying MagnifEye is the subject of a number of patent applications filed by the Company. 

MagnifEye is marketed as a busines-to-business commercial product now being offered to lateral flow test manufacturers and healthcare providers that use lateral flow tests for disease surveillance across large populations, including in international markets.  MagnifEye can be quickly trained to read and analyse individual lateral flow tests and has applications in human and animal health, including cancer, infectious disease and fertility, as well as plant pathogen and environmental testing.  It can be used as a standalone smartphone application or incorporated into third party web or native software applications.

Lord (Paul) Drayson PhD FREng, CEO, said: “Applying Clinical AI to medical imaging has been an important R&D focus for Sensyne since formation and the Company has developed world-class deep learning AI capabilities in this area and has a collaboration with Bayer in the field of machine vision. Diagnostic testing has seen rapid progress over the past year, accelerated by responses to the COVID-19 pandemic. We have been working on developing a general capability to automate the reading of lateral flow tests in response to demand from commercial test manufacturers and healthcare providers. We look forward to working with these potential partners to apply this technology as rapidly as possible.”