The programme, funded by Cancer Research UK and partners, will create new tools using AI and state-of-the-art analytics to advance cancer early detection and prevention.
Over the next five years, the Cancer Data Driven Detection programme (CD3) will access and link data from sources such as health records, genomics, family history, demographics, and behavioural data, to develop advanced statistical models to accurately predict who is most likely to get cancer. The programme aims to increase the number of people diagnosed with cancer at its earliest stages, when it is most treatable.
Queen Mary’s Wolfson Institute of Population Health are hosting one of the three funded projects, a research programme focused on multicancer risk prediction. Co-led by Dr Garth Funston and Professor Julia Hippisley-Cox, the project will apply a range of methods, including AI approaches, to data from tens of millions of UK patients in order to develop models which provide the risk of an individual developing 12 types of cancer.
The models will support informed decision making by patients on prevention and screening activities, and at the national level will target preventive interventions and tailor future multicancer detection screening programmes to maximise benefits and minimise harms. The research team will also examine the potential impact of using these models to select patients for cancer prevention and screening interventions.
The research at Queen Mary will focus on multicancer risk prediction, examining the potential impact of using the models developed to select patients for cancer prevention and screening interventions. The team will also assess the clinical utility of all models to support prevention, screening, and improved referrals for investigations, and integrate the strengths of the different approaches for risk factor discovery and cancer risk modelling.
Dr Garth Funston, Clinical Senior Lecturer in Primary Care Cancer Research, said: “This is a unique opportunity to improve understanding of cancer risk and develop clinically useful models to support doctors and patients in making informed, individualised decisions about cancer prevention and testing options.”
Professor Julia Hippisley-Cox, Professor of Clinical Epidemiology and Predictive Medicine in the Wolfson Institute of Population Health, said: “As a new Professor joining Queen Mary University of London, I am delighted to be part of this major investment in research lead by CRUK, to drive forward improvements in cancer detection and early diagnosis. The UK lags behind most other parts of the developed world in these areas and now we have a fantastic opportunity to address that and make a step change to drive improvements for patients and the NHS. The UK has some of the world’s richest data assets so this is also a golden opportunity to build lasting data infrastructure to accelerate new cancer research.”
Science Minister, Lord Vallance, said: “There are huge opportunities in AI to improve UK healthcare, from scans detecting illnesses earlier to bringing NHS waiting lists down by planning appointments more efficiently, and these will continue to develop.
“This investment in harnessing the potential of data to spot those at risk of cancer represents the sort of innovation the Government’s new AI Opportunities Action Plan sets out to realise, so this technology improves lives, while transforming public services and boosting growth.”
The Cancer Data Driven Detection programme is jointly supported by Cancer Research UK, the National Institute for Health & Care Research, the Engineering & Physical Sciences Research Council, Health Data Research UK, and Administrative Data Research UK.