Descrizione del progetto
Una piattaforma basata sull’intelligenza artificiale aiuta l’immunoterapia per il cancro al polmone
Sebbene l’immunoterapia sia il nuovo standard di cura per il carcinoma polmonare non a piccole cellule (NSCLC, Non-Small Cell Lung Cancer) avanzato, meno del 50 % dei pazienti trae beneficio da questo trattamento a lungo termine. Il biomarcatore «ligando di morte programmata 1» si utilizza per prevedere gli esiti dell’immunoterapia con un’efficacia limitata, mentre altri potenziali biomarcatori non sono ancora stati convalidati in sperimentazioni cliniche randomizzate. Il progetto I3LUNG, finanziato dall’UE, si propone di sviluppare strumenti basati sull’intelligenza artificiale (IA) per migliorare la sopravvivenza e la qualità di vita dei pazienti. I3LUNG si occuperà di creare una piattaforma globale contenente dati di 2 000 pazienti, per convalidare i modelli di IA; inoltre, raccoglierà i dati multiomici di 200 soggetti affetti da NSCLC al fine di integrare le informazioni e applicarle per orientare le decisioni nell’ambito dell’immunoterapia.
Obiettivo
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.
Campo scientifico
Parole chiave
Programma(i)
- HORIZON.2.1 - Health Main Programme
- HORIZON.2.1.6 - Health Care Systems
Meccanismo di finanziamento
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinatore
20133 Milan
Italia