Cancer and cardiovascular diseases (CVD) are the two leading causes of death in the UK and around the world. Despite substantial advances in the prevention, diagnosis and treatment of these two major groups of diseases, their impact on public health has continued to rise as the world’s population ages. Addressing this requires approaches that recognise and exploit the power of whole, large population-scale health-relevant data to catalyse health data science and its translation to improved patient care.

We also need to break down traditionally siloed disease and expertise-specific domains, rising to the challenge of jointly addressing cancer, CVD and other complex diseases. Crucially, we need to use the intelligence gained to translate into real benefits for patients, as well as influence policy and best practice.

The Big Data for Complex Disease (BDCD) Driver Programme will address challenges that focus on deploying whole population, national linked health data.

“This is an unprecedented opportunity to bring together the best minds in the UK to address the two Big ‘C’s’ of human health, cancer and cardiovascular disease, which collectively kill over 320,000 people in the UK each year. We will deploy a new approach, underpinned by the smart use of data, to provide a better insight into the key drivers of these diseases and use these insights to transform the lives of our patients and citizens.”

Professor Mark Lawler, Associate Director of Health Data Research Wales-Northern Ireland and Scientific Director of DATA-CAN

“Through uniting expertise, data and research infrastructure across the UK, our ambition is to create an enduring foundation that will enable health data research into cardiovascular disease, cancer and many other diseases for decades to come. Patients and the public will be at the core of our work, shaping everything we do to promote trust and ensure that what we uncover can improve peoples’ lives.”

Professor Cathie Sudlow, Chief Scientist and Deputy Director of HDR UK, and Director of the BHF Data Science Centre

    • To better predict development of cancer and CVD and to stratify risk for better early detection, early diagnosis and prevention.
    • To improve understanding of the inter-relationship between these complex diseases to ensure that data-driven insights fully inform strategies for the prevention, early diagnosis and management of both treatment sequelae and long-term risk.
    • To examine and better understand the impact of inequalities to influence and mitigate the negative impacts on incidence and outcomes associated with age, gender, ethnicity, geography and deprivation.