Governing artificial intelligence in cancer care: Perspectives and recommendations from patient organizations and the MULTIR consortium
Abstract
BACKGROUND: Artificial intelligence (AI) has the potential to improve cancer care. Its implementation must align with patients' needs, values, and lived experiences. This study aimed to explore perspectives from patient advocates representing patient organizations, including individuals with experience of melanoma, bladder and lung cancer, and to co-develop recommendations to support the ethical, patient-centered, and practical integration of AI in oncology. METHODS: Semi‑structured interviews were conducted with 18 patient advocates from patient organizations within the MULTIR network to explore current challenges in cancer care, perceptions of the benefits and risks of AI, and conditions for its trustworthy, sustainable and equitable adoption. Findings were reviewed and refined through a series of webinars, enabling participants to validate and strengthen the resulting recommendations. RESULTS: Participants identified key benefits and risks associated with AI and formulated six main recommendations targeting developers, policymakers, regulators, and researchers. These include: ensuring clear, accessible, and transparent communication about AI; strengthening training and capacity-building for healthcare professionals and patient organizations; demonstrating tangible clinical and patient-level benefits; developing secure, robust, and interoperable data infrastructures; reinforcing ethical and regulatory frameworks; and ensuring the sustained and meaningful involvement of patient organizations throughout AI development, implementation, and evaluation processes. CONCLUSION: These recommendations provide actionable, patient-informed directions for advancing the integration of AI in cancer care. Although grounded in insights from specific cancer communities, they are broadly applicable across oncology. Progress will require the structured integration of patient organizations and experiential knowledge into governance, research, and implementation processes, in order to support more equitable, trustworthy, and patient-centered AI-enabled health systems. POLICY SUMMARY: The recommendations have implications for European policies on healthcare regulation, digital health infrastructure, and data governance. They highlight the importance of capacity building, stakeholder engagement, and embedding principles of equitable access, responsible implementation, and patient‑centered governance of AI‑enabled health services.
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BibTeX
@article{budinljosne2026governing,
title = {{Governing artificial intelligence in cancer care: Perspectives and recommendations from patient organizations and the MULTIR consortium}},
author = {Isabelle Budin-Ljøsne and Alessandro Boni and Lise Boussemart and Ann-Katrin Fattal and Maria Frantzi and Laurent Gemenick and Filippos Koinis and Athanasios Kotsakis and Fredrik Östman and Thomas Roret and Merete Schmiegelow and Kalliopi Thanopoulou and Catherine Tourette-Turgis and Robert White},
journal = {Journal of Cancer Policy},
year = {2026},
month = sep,
doi = {10.1016/j.jcpo.2026.100803},
url = {https://inserm.hal.science/inserm-05740391v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Governing artificial intelligence in cancer care: Perspectives and recommendations from patient organizations and the MULTIR consortium
AU - Isabelle Budin-Ljøsne
AU - Alessandro Boni
AU - Lise Boussemart
AU - Ann-Katrin Fattal
AU - Maria Frantzi
AU - Laurent Gemenick
AU - Filippos Koinis
AU - Athanasios Kotsakis
AU - Fredrik Östman
AU - Thomas Roret
AU - Merete Schmiegelow
AU - Kalliopi Thanopoulou
AU - Catherine Tourette-Turgis
AU - Robert White
PY - 2026
DA - 2026/09/07
JO - Journal of Cancer Policy
DO - 10.1016/j.jcpo.2026.100803
UR - https://inserm.hal.science/inserm-05740391v1
AB - BACKGROUND: Artificial intelligence (AI) has the potential to improve cancer care. Its implementation must align with patients' needs, values, and lived experiences. This study aimed to explore perspectives from patient advocates representing patient organizations, including individuals with experience of melanoma, bladder and lung cancer, and to co-develop recommendations to support the ethical, patient-centered, and practical integration of AI in oncology. METHODS: Semi‑structured interviews were conducted with 18 patient advocates from patient organizations within the MULTIR network to explore current challenges in cancer care, perceptions of the benefits and risks of AI, and conditions for its trustworthy, sustainable and equitable adoption. Findings were reviewed and refined through a series of webinars, enabling participants to validate and strengthen the resulting recommendations. RESULTS: Participants identified key benefits and risks associated with AI and formulated six main recommendations targeting developers, policymakers, regulators, and researchers. These include: ensuring clear, accessible, and transparent communication about AI; strengthening training and capacity-building for healthcare professionals and patient organizations; demonstrating tangible clinical and patient-level benefits; developing secure, robust, and interoperable data infrastructures; reinforcing ethical and regulatory frameworks; and ensuring the sustained and meaningful involvement of patient organizations throughout AI development, implementation, and evaluation processes. CONCLUSION: These recommendations provide actionable, patient-informed directions for advancing the integration of AI in cancer care. Although grounded in insights from specific cancer communities, they are broadly applicable across oncology. Progress will require the structured integration of patient organizations and experiential knowledge into governance, research, and implementation processes, in order to support more equitable, trustworthy, and patient-centered AI-enabled health systems. POLICY SUMMARY: The recommendations have implications for European policies on healthcare regulation, digital health infrastructure, and data governance. They highlight the importance of capacity building, stakeholder engagement, and embedding principles of equitable access, responsible implementation, and patient‑centered governance of AI‑enabled health services.
SN - 2213-5383
ER -