Scientists at Cambridge University are leading a £10 million project that could enable doctors the ability to predict individual chances of getting cancer and provide personalised detection and prevention measures. The Cancer Data-Driven Detection programme is being led by Antonis Antoniou, professor of Cancer Risk Prediction at the University of Cambridge.

The program intends to access and connect data from multiple sources such as health records, family history, demographics and behavioural data, to generate statistical models that support scientists in determining who is most likely to get cancer. The programme will also develop new tools that use AI to interpret the data and calculate an individual’s potential risk of cancer within their lifetime.

Professor Antoniou explains that determining people at the highest risk of developing cancer, is a significant challenge. The UK’s ability in population-focused data resources, along with advanced analytical solutions like AI, provide considerable opportunities to connect disparate data and create ideas that could result in earlier detection, diagnosis and prevention of cancers.

Over the next few years, the funding will generate the infrastructure needed to access and assess the algorithms and AI tools to enable accurate and clinically valid information about potential cancer risks. The scientific programme will be supported by partnerships with cancer patients, the public, clinical professionals and industry while tackling ethical and legal factors to ensure that models and tools work effectively in practice.

Professor Antoniou highlighted that the Cancer Data Driven Detection programme could support public health policy and empower people and healthcare providers to deliver informed decisions. By recognising individual cancer risks, people can take the necessary steps to stop cancer before it gets worse or potentially before it even begins.

The generated models delivered from the research could be used to support people at a higher risk of cancer in various ways. For example, the NHS could provide regular cancer screening sessions or screening to those at a higher risk. 

Early diagnosis of cancer saves lives, but studies of NHS data by Cancer Research UK, suggest only 54% of cancers in England are diagnosed at either stages one or two, when treatment is more likely to be effective. NHS England has announced a target to diagnose 75% of cancers at stages one and two by 2028, and this is only possible with research and embracing new technologies. 

Recently, the UK Government confirmed support for the power of big data and AI, which can help more people, including those with cancer. Science Minister Lord Vallance explains that there are significant opportunities in AI to strengthen UK healthcare, ranging from scans to detect illnesses to reducing waiting lists by efficient planning.

This investment is strengthening the potential of data to identify those at risk of cancer highlighting the innovation of the Government’s new AI Opportunities Action Plan, so this technology enhances lives while transforming public services and accelerating growth.

Andrew Gwynne, the Minister for Public Health and Prevention, explains that applying the latest technology could transform how the health industry diagnoses and treats individuals. As part of the Government’s Plan for Change, we can shift the health service towards digital, and projects like this represent how to achieve this. 

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 support the Cancer Data Driven Detection programme.

Dr David Crosby, the Head of Prevention and Early Detection Research at Cancer Research UK believes the most important thing we can do to beat cancer is find it earlier, when treatment is more likely to succeed. With approximately half a million cancer cases per year predicted in the UK by 2040, we require a significant transformation towards more accurate diagnosis and detection of early cancer. 

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