Descripción del proyecto
Una plataforma basada en inteligencia artificial para ayudar en la inmunoterapia del cáncer de pulmón
Aunque la inmunoterapia es el nuevo tratamiento de referencia para el cáncer de pulmón no microcítico (CPNM) avanzado, menos del 50 % de los pacientes se benefician de este tratamiento a largo plazo. El biomarcador del ligando 1 de muerte celular programada se utiliza para predecir los resultados de la inmunoterapia con una eficacia limitada, y otros posibles biomarcadores aún no se han validado en ensayos clínicos aleatorizados. El equipo del proyecto I3LUNG, financiado con fondos europeos, pretende desarrollar herramientas basadas en inteligencia artificial (IA) para mejorar la supervivencia y la calidad de vida de los pacientes. En el marco del proyecto se creará una plataforma mundial con datos de dos mil pacientes para la validación de modelos de IA. Además, se recopilarán datos multiómicos de doscientos pacientes con CPNM para la integración de la información y su aplicación en la toma de decisiones relativas a la inmunoterapia.
Objetivo
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.
Ámbito científico
Palabras clave
Programa(s)
- HORIZON.2.1 - Health Main Programme
- HORIZON.2.1.6 - Health Care Systems
Régimen de financiación
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinador
20133 Milan
Italia