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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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