Secure eResearch Platform (SeRP), based in Population Data Science at Swansea University, is part of a £10 million partnership to revolutionise cancer early detection and prevention using cutting-edge AI and advanced analytics. The Cancer Data-Driven Detection (CD3) programme will harness population-scale data to predict cancer risk and enable earlier diagnosis and prevention.
Doctors may soon predict your individual cancer risk and offer personalised detection and prevention strategies, thanks to a transformative new initiative. The Cancer Data-Driven Detection (CD3) programme is backed by a £10 million investment from Cancer Research UK, the National Institute for Health and Care Research (NIHR), and the Engineering and Physical Sciences Research Council (EPSRC).
The programme aims to access and link data from different sources – including health records, genomics, family history, demographics, and behavioural data – to develop advanced statistical models that help scientists accurately predict who is most likely to get cancer. Alongside this, the programme will develop powerful new tools which use AI to analyse the data and calculate an individual’s risk of cancer throughout their lifetime.
CD3, led by the University of Cambridge, unites experts and infrastructure across the UK, including a dedicated team from SeRP.
The Secure eResearch Platform (SeRP) will play a key role in securely managing and analysing the data, and provide CD3 with a SeRP Hub to sit within the SAIL Databank Trusted Research Environment (TRE). SeRP Hubs reduce the operational barriers to establishing a robust TRE. This SeRP Hub is a hosted TRE that benefits from SAIL Databank’s accredited, privacy-protecting ‘5-safes’ environment. The CD3 programme will utilise the SAIL Databank and other trusted research environments (TREs) to link and analyse data from multiple sources, including health records, genomics, and behavioural data. A team of three researchers based at Swansea University will support the integration and use of data across the UK, contributing to the development of predictive AI tools.
Professor Simon Thompson, Co-Applicant and Co-Director of SeRP and SAIL, said “By connecting diverse data sources and using AI-driven insights, we have the potential to change how we detect and prevent cancer. SAIL Databank and SeRP, along with our expertise in Population Data Science, play an important role in this collaboration, ensuring that data is used securely and effectively to improve lives. This programme reflects our commitment to contributing to cutting-edge, data-driven research for public benefit.”
Professor Ashley Akbari, Co-Applicant and CD3 Data Lab co-lead, said “This exciting and important programme will look to harness the potential of population-scale linked data across the UK, integrating data from a diverse range of sources such as electronic health records (EHRs), administrative records, and other multi-modal data sources. Utilising these data, the CD3 data lab team will drive the development of reproducible data-driven intelligence across the UK to enable the CD3 programme and collaboration. Building upon our expertise at Swansea University from the SAIL Databank and SeRP, we cannot wait to start working further across this CD3 collaboration and associated networks to drive impactful research which will improve people’s lives and the services they use.”
Over the next five years, the team at Population Data Science will collaborate closely with partners to establish the infrastructure needed to link datasets, develop algorithms for cancer risk prediction, and evaluate their clinical application.
As part of the programme, ADR UKis providing funding to support the linking of administrative and health data in Wales, which is key to understanding cancer incidence across the Wales. The ADR Wales team based in Population Data Science at Swansea University has been leading feasibility studies that link cancer data with administrative records. These findings will be shared ahead of the CD3 programme’s launch in early 2025, ensuring a strong foundation for this transformative initiative.
Director of the Cancer Data Driven Detection programme and Professor of Cancer Risk Prediction at the University of Cambridge, Professor Antonis Antoniou, said:
“Finding people at the highest risk of developing cancer, including those with vague symptoms, is a major challenge. The UK’s strengths in population-scale data resources, combined with advanced analytical tools like AI, offer tremendous opportunities to link disparate datasets and uncover clues that could lead to earlier detection, diagnosis, and prevention of more cancers.
The Cancer Data Driven Detection programme will build the partnerships and infrastructure needed to make data-driven cancer early detection, diagnosis and prevention a routine part of frontline healthcare. Ultimately, it could inform public health policy and empower individuals and their healthcare providers to make shared decisions. By understanding individual cancer risks, people can take proactive steps to stop cancer before it gets worse or even begins in the first place.”
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.
