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Going viral: Harnessing Deep Learning and Quantum Materials for Early Disease Diagnosis
The silent pandemic of antimicrobial resistance ranks among the top ten global health threats facing humanity, and could kill 10 million people annually by 2050, at a cost to the global economy of $100 trillion.
There is growing recognition of the critical role of diagnostics in guiding patient management and antibiotic usage, yet the development of fit-for-purpose tests for antimicrobial resistance and models for decentralised diagnostic delivery, remains a major challenge.
Gold-standard laboratory tests, such as culture or PCR, while highly accurate, typically require posting samples to centralised labs and waiting for test results, resulting in diagnosis delays and inappropriate prescribing. Low-cost lateral flow tests which give results within minutes, have come to the fore during the COVID-19 pandemic by widening access to testing in decentralised community settings (e.g. pharmacies, GPs, care homes, schools and at home).
However, lateral flow tests typically lack sensitivity to early infections, resulting in false negatives. Hence there is an urgent need for high-performance rapid tests to accurately diagnose early-stage infections and antimicrobial resistance in community settings.
Herein, with IET A F Harvey Engineering Research Prize funding, I seek to exploit my team’s recent breakthroughs in quantum nanodiamond diagnostics and deep learning of rapid tests to revolutionise the early diagnosis of antimicrobial resistance, focusing on drug resistant Tuberculosis as an exemplar.
If successful, this ground-breaking early-stage research could lay the foundations of next-stage translational funding and open-up applications to other communicable and non-communicable diseases.
Professor Rachel McKendry
Professor Rachel McKendry is Professor of Biomedical Nanoscience and holds a joint position between the London Centre for Nanotechnology and Division of Medicine, University College London.
She is Director of the i-sense EPSRC IRC, a large interdisciplinary research collaboration in Early Warning Sensing Systems for Infectious Diseases (2013-24) and the new EPSRC Digital Health Hub for AMR. Her research lies at the cutting edge of quantum technologies, deep learning and telecommunications for infectious diseases and public health.
Her recent breakthroughs span from ultra-sensitive quantum nanodiamond diagnostics for virus detection (Miller et al., Nature 2020), to mHealth and deep learning models for rapid testing in partnership with the Africa Health Research Institute in South Africa (Turbé et al., Nature Medicine 2021).
Professor McKendry has won several awards for her research including the Royal Society Rosalind Franklin Award, Royal Society Wolfson Research Merit Award, and the Institute of Physics Paterson Medal.
She co-chaired the Digital Medicine Theme of the Topol Review of the NHS, ‘Preparing the Healthcare Workforce to Deliver the Digital Future’, served on the cross-council Steering Group for Antimicrobial Resistance, chaired the National Bionanosurveillance Network Expert Advisory Group and currently serves on the International Pandemic Preparedness 100 Days Mission Diagnostic Scientific and Technical Advisory Group.
