Description du projet
Une plateforme fondée sur l’IA au service de l’immunothérapie du cancer du poumon
L’immunothérapie a beau être la nouvelle norme de soins pour le cancer du poumon non à petites cellules (CPNPC) avancé, moins de la moitié des patients bénéficient de ce traitement sur le long terme. Le biomarqueur du ligand de mort cellulaire programmée de type 1 est utilisé pour prédire l’issue de l’immunothérapie avec une efficacité limitée, et d’autres biomarqueurs potentiels n’ont pas encore été validés dans le cadre d’essais cliniques randomisés. Le projet I3LUNG, financé par l’UE, entend mettre au point des outils fondés sur l’IA pour améliorer la survie et la qualité de vie des patients. Pour ce faire, le projet mettra en place une plateforme mondiale comprenant les données de 2 000 patients afin de valider les modèles d’IA; de plus, il collectera les données multi-omiques de 200 patients atteints de CPNPC afin d’intégrer ces informations et leur application dans les principales décisions relatives à l’immunothérapie.
Objectif
Immunotherapy (IO) is the new standard of care for many patients with advanced Non-Small Cell Lung Cancer (aNSCLC), yet only around 30-50% of treated patients benefit from IO in the long term. Programmed Death-Ligand 1 (PD-L1) remains the only biomarker used to predict patient outcome to IO, though its efficacy is limited. Other potential biomarkers have been identified, yet not validated in prospective randomized clinical trials, providing only partial evidence. Due to the dynamic complexity of the immune system-tumour microenvironment, its interaction with the host and patient behaviour, it?s unlikely for a single biomarker to accurately predict patient outcome. Artificial Intelligence (AI) and machine learning (ML) frameworks, that synthetize and correlate information from multiple sources, are essential to develop powerful decision-making tools able to deal with this highly complex context and provide individualized predictions to improve patient outcomes reducing the economic burden of health care systems in NSCLC.
The aim of the I3LUNG project is to develop such AI-based tools to assist in improving survival and quality of life, preventing undue toxicity, and reducing treatment costs. I3LUNG adopts a two-pronged approach: setting up a transnational platform of available data from 2000 patients in order to validate the AI models, and generating a multi-omics prospective data collection in 200 NSCLC patients integrating diverse -omic information then validate its usefulness in leading IO therapeutic decisions. A psychological study will help in defining the impact of AI-guided decisions on patients, eliciting their preference, and physicians comparing AI with Human Intuition. The final goal is the construction of a novel integrated AI-assisted Data Storage and Elaboration Platform backed up by Trustworthy Explainable AI methodology, ensuring its accessibility and ease of use by healthcare providers and patients alike.
Champ scientifique
Mots‑clés
Programme(s)
- HORIZON.2.1 - Health Main Programme
- HORIZON.2.1.6 - Health Care Systems
Régime de financement
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinateur
20133 Milan
Italie