We’re facilitating focused, collaborative spaces where community members can connect with others, share expertise, explore new methods, tackle emerging challenges and support skill development across a large network of UK-wide academic and research institutions.
The community is organised around eight interest groups, each representing a priority area in data science and addressing key challenges and opportunities across the research landscape.
Each group is supported by expert academic advisors who help guide its direction and ensure activities reflect both scientific needs and our wider priorities.
Focuses on the computational foundations needed for modern cancer research, including high‑performance computing, cloud infrastructure, workflow optimisation and the development and application of AI and machine‑learning tools.
Group advisor: Andrew Blake, Cancer Research UK Oxford Centre
Aims to maximise the value of existing datasets and biological samples by improving accessibility, harmonisation, interoperability and best practices in data governance, sharing and reproducibility.
Group advisors: Frances Pearl, University of Sussex and Mieke Van Hemelrijck, Kings College London
Explores the use of real‑world clinical data, electronic health records, imaging and AI‑enabled clinical decision tools to support diagnosis, prognosis, treatment planning and improved patient outcomes.
Group advisors: Iliada Eleftheriou, Cancer Research UK Manchester Centre, Gareth Price, Cancer Research UK Manchester Centre and Georgios Lyratzopoulos, University College London
Ensures data‑driven cancer research reflects diverse populations and is informed by meaningful patient and public involvement. Promotes equity, representation and inclusive research practices.
Group advisor: Harriet Unsworth, Cancer Research UK National Biomarker Centre
Supports the development of skills and career pathways for researchers working at the intersection of data science and cancer research, including training, mentorship and capacity building.
Group advisor: Colin McLean, Cancer Research UK Scotland Centre
Focuses on data emerging from spatial transcriptomics, proteomics and imaging technologies, developing approaches for the analysis, integration and biological interpretation of spatially resolved tumour ecosystems.
Addresses the environmental footprint of data‑intensive research by promoting efficient computing, sustainable data practices and awareness of the resource and energy implications of large‑scale analytics.
Concentrates on data science approaches tailored to children’s and young people’s cancers, including handling rare disease datasets, cross‑centre data integration and age‑specific research challenges.
Exploring issues in cancer science, how that science shapes our understanding of the disease and the challenges the community face conducting this research.
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This forum brings together expertise from NHS England, researchers, third sector organisations and people affected by cancer to improve access, quality and timeliness of cancer health system data.
