BRIEF RESEARCH REPORT article
Front. Digit. Health
Sec. Health Informatics
Advancing the adoption of oncology Decision Support Tools in Europe: Insights from CAN.HEAL
Nancy Frederickx 1
Guy Froyen 2,3
Maud Kamal 4,5
Célia Dupain 4
Matteo Pallocca 6
Julie Maetens 1
Nikolas Von Bubnoff Von Bubnoff 7,8
Gennaro Ciliberto 9
Pauline De Wurstemberger 1
Zeina Chamoun Morel 10
Rossana Alessandrello 11
J.Matt McCrary 12,13
Brigitte Maes 14,3
Ruggero De Maria 15,16
Frédérique Nowak 17
Jose Maria Castellano Gracia 11
Claudia Prats 11
Patrizio Giacomini 18
Aline Hebrant 1
Gordana Raicevic Toungouz 1
Marc Van Den Bulcke 1
Els Van Valckenborgh 1
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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