Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/49025
Title: Advancing the adoption of oncology decision support tools in Europe: insights from CAN.HEAL
Authors: Frederickx, Nancy
FROYEN, Guy 
Kamal, Maud
Dupain, Celia
Pallocca, Matteo
Maetens, Julie
von Bubnoff, Nikolas
Ciliberto, Gennaro
De Wurstemberger, Pauline
Morel, Zeina Chamoun
Alessandrello, Rossana
McCrary, J. Matt
MAES, Brigitte 
De Maria, Ruggero
Nowak, Frederique
Castellano-Garcia, Jose Maria
Prats, Claudia
Giacomini, Patrizio
Hebrant, Aline
Toungouz, Gordana Raicevic
van den Bulcke, Marc
Van Valckenborgh, Els
Issue Date: 2026
Publisher: FRONTIERS MEDIA SA
Source: Frontiers in digital health, 8 (Art N° 1784519)
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.
Notes: Frederickx, N (corresponding author), Sciensano, Canc Ctr, Dept Epidemiol & Publ Hlth, Brussels, Belgium.
Nancy.frederickx@sciensano.be
Keywords: AI data-driven precision oncology;CAN.HEAL;clinical decision system;data integration;decision support tool (DST)digital framework;Molecular Tumour Board;personalised oncology
Document URI: http://hdl.handle.net/1942/49025
e-ISSN: 2673-253X
DOI: 10.3389/fdgth.2026.1784519
ISI #: 001744635600001
Rights: 2026 Frederickx, Froyen, Kamal,Dupain, Pallocca, Maetens, von Bubnoff,Ciliberto, De Wurstemberger, ChamounMorel, Alessandrello, McCrary, Maes, DeMaria, Nowak, Castellano-Garcia, Prats,Giacomini, Hebrant, Raicevic Toungouz,Van den Bulcke and Van Valckenborgh.This is an open-access article distributedunder the terms of the CreativeCommons Attribution License (CC BY).The use, distribution or reproduction inother forums is permitted, provided theoriginal author(s) and the copyrightowner(s) are credited and that theoriginal publication in this journal iscited, in accordance with acceptedacademic practice. No use, distributionor reproduction is permitted which doesnot comply with these terms.
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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