Periodic Reporting for period 1 - GLIOMATCH (The malignant Glioma immuno-oncology matchmaker: towards data-driven precision medicine using spatially resolved radio-multiomics)
Okres sprawozdawczy: 2024-01-01 do 2025-06-30
Scientific impact: GLIOMATCH will apply state-of-the-art AI/deep learning models to predict and monitor treatment strategies, creating a powerful tool for personalised therapy. This approach not only advances the field of neuro-oncology but also establishes a framework applicable to other cancers. By adopting open science principles and FAIR data standards, the project will create a harmonised data lake that enables large-scale, cross-sectoral research collaborations. This will strengthen Europe’s leadership in bioinformatics, immunotherapy, and precision oncology.
Societal impact: GLIOMATCH will directly address GBM burden by providing earlier, more accurate detection of tumour progression and enabling adaptive treatment monitoring. The project supports Europe’s Beating Cancer Plan and the EU Cancer Mission’s goals by collaborating with the EU Cancer Mission’s ‘Understanding (Tumour-Host) Interactions’ Cluster. At a global level, GLIOMATCH contributes to the UN Sustainable Development Goal 3 (Good Health and Well-Being) by helping reduce premature mortality from non-communicable diseases and improving the well-being of patients and survivors. The project’s co-creation approach, involving patients, caregivers, and healthcare professionals, ensures that outcomes are grounded in societal needs and that knowledge is shared across communities.
Economic impact: GLIOMATCH aims to introduce cost-effective and scalable innovations, which reduce reliance on costly invasive procedures and enable more efficient patient stratification. The clinical decision-making algorithm is designed to be applicable across diverse healthcare systems, including resource-limited settings, thereby increasing accessibility. The project also establishes a new standardised method for MRI data interpretation, facilitating alignment across European clinics and fostering innovation in medical imaging technologies. The discovery of new biomarkers and targets will open opportunities for drug developers, diagnostics companies, and healthcare providers to invest in personalised medicine solutions. Moreover, the project’s data lake will provide a resource for medical software developers, enabling the creation of new algorithms and services with potential for international licensing.
To ensure further uptake and success, several key needs have been identified. Continued research is required to validate classifiers and therapeutic targets, for which large, independent cohorts have been identified within the consortium, and to functionally characterise the candidate pathways. Demonstration activities, including the planned prospective clinical trials, are essential for clinical translation and are aimed to start in the upcoming months. Additional funding streams (e.g. EIC Transition) will be necessary to support preclinical evaluation of therapeutic hypotheses and to bridge toward market uptake. Internationalisation of the consortium, with inclusion of further clinical centres, will e required to strengthen generalisability and broaden impact, and is foreseen to start towards the end of the project. Finally, alignment with regulatory and standardisation frameworks (IVDR, EU Clinical Trials Regulation) and targeted capacity-building activities will be critical to sustain adoption in clinical and research contexts.