Overcoming data management challenges in oncology research: Lessons from an NHS, industry, technology start-up and academic collaboration
Effective management of multimodal data in oncology requires early planning, multi-stakeholder engagement (among National Health Service [NHS] Trusts, industry, start-up collaborators, and academic institutions), and robust governance. The data lake model demonstrated a scalable and compliant approach to enabling secure, collaborative research using genomic data, providing a template for future initiatives in precision oncology.
Authors
- Steven R. Brown (ORCID: https://orcid.org/0000-0002-0980-2793)
- Matthew Griffiths (ORCID: https://orcid.org/0000-0002-7325-9668)
- Alicia‐Marie Conway (ORCID: https://orcid.org/0000-0003-2635-8206)
- Natalie Cook (ORCID: https://orcid.org/0000-0003-2606-1082)
- Hanafizan Hussain
- C. R. Bridges (ORCID: https://orcid.org/0009-0005-6905-559X)
- Kelly Warrington
- Matthew J. Concannon
- Karen Lightning-Jones
- April Marland
- Barney Plummer
Institutions
- Manchester University NHS Foundation Trust (GB)
- Concern Worldwide UK (GB)
- Roche (United Kingdom) (GB)
- The Christie NHS Foundation Trust (GB)
Publication Details
- Journal
- European Journal of Cancer
- Published
- 2025-08-12
- DOI
- https://doi.org/10.1016/j.ejca.2025.115705
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Cancer Research UK
- National Institute for Health and Care Research
- Department of Health and Social Care
- Manchester Biomedical Research Centre
- Innovate UK