What is ED&D?

Scientific Officer working in lab

The Early Diagnosis and Detection (ED&D) Centre at The Royal Marsden and the Institute of Cancer Research (ICR) relates to discovery and translation of novel early cancer diagnosis, detection and prevention. 

ED&D proposes a two-step diagnostic strategy to detect cancer at its earliest, most curable stage. This approach consists of using screening technologies as a first step, identifying individuals who are likely to have higher risk of cancer or more aggressive cancer (using biomarker tests in blood, urine, saliva, etc.), followed by cutting-edge diagnostics such as imaging or liquid biopsy technologies to diagnose cancers. We are one of the leading centres to combine this with use of Artificial Intelligence (AI) for earlier diagnosis, detection, and prevention.

To support our integrated research strategy, our key focus areas are :

  • Risk Stratification / Targeted Early Diagnosis
  • Molecular Detection / Liquid Biopsy Technologies
  • Convergence Science e.g. Point of care tests
  • Artificial Intelligence & Computational approaches
  • Population Studies: Epidemiology & Behavioural factors
  • Delivering patient facing early diagnosis studies locally and nationally
  • Driving new innovative models of early diagnosis care, based on our research, through NHS England

How are we different from other early diagnosis and detection centres?

Early Diagnosis and Detection centre will focus on risk stratified early diagnosis. Our expertise will be utilisied to achieve this through cancer genetics as well as our patient community presenting with variety of different conditions. This can help us to develop cutting edge liquid biopsy biomarkers and AI early detection tools.

Our facilities are likely to expand further with the new Oak Cancer Centre based at The Royal Marsden, as we continue to harness future partnerships with key stakeholders.

Read more about the importance of early diagnosis in cancer.

Early Diagnosis and Detection Centre research overview diagram


Please note this diagram should not be used or replicated without permission.

Artificial Intelligence (AI) in early diagnosis of cancer

AI uses computer systems to perform complex decision-making processes normally carried out by humans. This can be used to learn important features in imaging (‘machine learning’) or reading of medical text (‘natural language processing’). AI allows us to develop new tools that navigate large scale ‘big data’ and support or perhaps improve upon ‘decision-making’ required for early cancer diagnosis. It does this by finding patterns in clinical scans and records that identify patients who might be at increased risk of cancer, or by automating triaging of test results to alert clinicians sooner. AI can also be applied to identify pre-cancer states, cancer sub-types and predict clinical behaviour including risk of relapse.

Sometimes, scan findings are labelled as ‘indeterminate’ and require repeating to watch for change or concerning behaviour that might indicate cancer or other disease. This can be stressful and worrisome for patients during a period of ‘watchful waiting’, however, AI may enable earlier diagnosis and reduce such anxieties for patients. It may also help reduce the number of scans and appointments needed, freeing up valuable healthcare resources which can then be re-diverted to support other clinical needs, or explore newer avenues of research.

We hope that patients will help us to develop the best approach to clinical research that use trustworthy AI tools. Through patient-clinician solidarity, we hope to find the most ethical and valuable approaches whereby AI can lead to ‘learning’ healthcare systems. If earlier diagnosis of cancer is one of our core strengths in this area. We hope our pioneering studies will provide a springboard to share such research on a wider scale, to benefit all patients, including those who aren’t able to access hospital care at the Royal Marsden directly.

AI in healthcare is a rapidly expanding forum for innovation and we welcome interested investors and collaborators who wish to join us in this exciting dynamic new research frontier.