BRIEF RESEARCH REPORT article

Front. Digit. Health

Sec. Health Informatics

Advancing the adoption of oncology Decision Support Tools in Europe: Insights from CAN.HEAL

  • 1. Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium

  • 2. Laboratory for Molecular Diagnostics, Jessa Hospital, Hasselt, Belgium

  • 3. Faculty of Medicine and Life Sciences, LCRC, University of Hasselt, Hasselt, Belgium

  • 4. Department of Drug Development & Innovation (D3i), Institute Curie (IC), Paris, France

  • 5. IHU PRISM National Precision Medicine Centre in Oncology, Gustave Roussy, Villejuif, France

  • 6. Institute of Endotypes in Oncology Metabolism and Immunology "G. Salvatore" (IEOMI-CNR), on behalf of DIGICORE, Naples, Italy

  • 7. Universitatsklinikum Schleswig-Holstein Campus Lubeck, Lübeck, Germany

  • 8. Department of Hematology and Oncology, University Medical Center Schleswig-Holstein (UKSH) and University Cancer Center Schleswig-Holstein (UCCSH), Campus Lübeck, Lübeck, Germany

  • 9. IRCCS National Cancer Institute Regina Elena (on behalf of Digicore), Rome, Italy

  • 10. Advanced Training Office, Institute Curie (IC), Paris, France

  • 11. Innovation & Strategic Futures Area, Agency for Health Quality and Assessment of Catalonia (AQuAS), Barcelona, Spain

  • 12. Department of Human Genetics, Hannover Medical School, Hannover, Germany

  • 13. Institute of Clinical Genetics and Genomic Medicine, University Hospital of Würzburg & University of Würzburg, Würzburg, Germany

  • 14. Laboratory for Molecular Diagnostics, Jessa Hospital,, Hasselt, Belgium

  • 15. Alleanza Contro il Cancro, Roma, Italy

  • 16. Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy; Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy

  • 17. Health Technologies Institute, Inserm, Paris, France

  • 18. UOSD Medicina di Precisione in Senologia, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy

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Abstract

Effective cancer care increasingly depends on digital decision support tools (DSTs) to interpret complex clinical, molecular, and genomic data and guide personalised treatment decisions. However, the oncology DST (oncDST) landscape remains fragmented, with limited interoperability, inconsistent standards, and uneven clinical adoption across healthcare systems. This fragmentation hinders routine clinical use and impedes the demonstration of robust clinical benefit. To address these challenges, the CAN.HEAL consortium proposes the EU-oncDST digital framework, a conceptual, harmonised, interoperable, and modular architecture designed to integrate existing oncDSTs across Europe. Developed through consortium-wide consultations, an EU-level survey and comprehensive mapping of both public and private solutions, the framework provides a practical pathway for implementing interoperable oncDSTs while fostering stakeholder collaboration and innovation. It also promotes the improvement of data-driven precision oncology, highlighting the integration of artificial intelligence, enabling continuous patient follow-up, and supporting the development of a learning cancer system. At its core, the framework empowers Molecular Tumour Boards (MTBs) to operate efficiently at institutional, national, and European levels. By offering a harmonised, interoperable, and modular architecture designed to integrate clinical, molecular and genomic data, the framework strengthens evidence-based and personalised treatment recommendations. A phased action plan links MTB deployment to the implementation of oncDSTs. Early phases focus on piloting and validating oncDST use within MTBs, optimising patient-centred consultations, harmonising variant annotation, and enhancing clinical trial matching. Overall, the EU-oncDST digital framework aims to provide a practical and collaborative pathway to strengthen oncology decision-making and accelerate the translation of precision medicine into clinical benefit across Europe.

Summary

Keywords

AI Data-Driven Precision Oncology, CAN.HEAL, Clinical decision system, data integration, Decision support tool (DST), digital framework, MolecularTumour Board, precision oncology

Received

09 January 2026

Accepted

18 February 2026

Copyright

© 2026 Frederickx, Froyen, Kamal, Dupain, Pallocca, Maetens, Von Bubnoff Von Bubnoff, Ciliberto, De Wurstemberger, Chamoun Morel, Alessandrello, McCrary, Maes, De Maria, Nowak, Castellano Gracia, Prats, Giacomini, Hebrant, Raicevic Toungouz, Van Den Bulcke and Van Valckenborgh. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Nancy Frederickx

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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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