Big Data for Complex Disease

Overview

Cancer and cardiovascular diseases are major killers worldwide. Despite progress in prevention and treatment, their impact continues to grow as populations age.  

To tackle this, the Big Data for Complex Disease Driver Programme aims to use large health datasets to improve early detection, diagnosis, and management of both conditions.  

By analyzing data from various sources, the program seeks to enhance patient care and reduce the burden of these diseases on individuals and communities.  

This initiative leverages comprehensive health information to inform policies and best practices, ultimately aiming to lower disease impact globally. 

Programme Co- Leads:

Professor Angela Wood 

Professor Mark Lawler 

Theme Leads:

Professor Eva Morris – Cancer Data 

Dr Gary Abel – Methods 

“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

How can this new knowledge be translated into real benefit for the public and patients and to influence national and international policy and best practice?

Activities

• Create streamlined data access processes across the 4 national Secure Data Environments (SDE) and ensure clear information is available regarding dataset contents and suitability for projects.  

• Improve dataset linkages, access to code and code lists, phenotype libraries and algorithms, including creating pipelines and common ‘code lists’ to help define disease phenotypes and their diagnoses.  

• Define the components of our risk prediction scaffold, including the data (disease phenotypes, variables), models and algorithms used, and the evaluation metrics and validations.  

• Establish networks with existing risk prediction research programmes, e.g., Cancer Data Driven Detection (CD3).  

• Identify and begin to measure biological effects and potential interactions of drugs for treatment of cardiovascular diseases, cancers on other conditions. 

• Health economic research on the impact of co-morbidities when related to treatment and survivorship of cardiovascular diseases and cancers.  

• Improve UK-wide standards in data definitions of characteristics of inequalities and develop projects to bring together health and related datasets to understand their impact on complex diseases.  

• Provide training and support to PhD students and fellows. 

Outputs

• Development of data curation tools to support health data research in cardiovascular, cancer, and other diseases within the NHS England Secure Data Environment. 
• Publication of data-led consensus statements on the financial impact of cancer treatments, including policy recommendations for health systems.  
• Publication of a position paper to influence UK government to adopt a national cancer plan.  

Cross-Driver Programme – Health Economics fellowship call

HDR UK and Queen’s University Belfast launched a cross-Driver funding call for a Health Economics Fellow to advance research at the intersection of health economics and data science. With funding of up to £250K over three years (April 2025–March 2028), this fellowship offered a unique opportunity for an early-career researcher to explore the societal and policy impacts of health data. Sitting in the Big Data for Complex Disease Programme, the Fellow will also collaborate across other Driver Programmes, using diverse datasets to address inequalities, improve care, and inform health policies across the UK.

For more information on this call, please follow the link here to the webpage.