The EU-funded I 3 LUNG Project: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy

Although immunotherapy (IO) has changed the paradigm for the treatment of patients with advanced non-small cell lung cancers (aNSCLC), only around 30% to 50% of treated patients experience a long-term benefit from IO. Furthermore, the identification of the 30 to 50% of patients who respond remains a...

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Published inClinical lung cancer Vol. 24; no. 4; p. 381
Main Authors Prelaj, Arsela, Ganzinelli, Monica, Trovo', Francesco, Roisman, Laila C, Pedrocchi, Alessandra Laura Giulia, Kosta, Sokol, Restelli, Marcello, Ambrosini, Emilia, Broggini, Massimo, Pravettoni, Gabriella, Monzani, Dario, Nuara, Alessandro, Amat, Ramon, Spathas, Nikos, Willis, Michael, Pearson, Alexander, Dolezal, James, Mazzeo, Laura, Sangaletti, Sabina, Correa, Ana Maria, Aguaron, Alfonso, Watermann, Iris, Popa, Crina, Raimondi, Giulia, Triulzi, Tiziana, Steurer, Stefan, Lo Russo, Giuseppe, Linardou, Helena, Peled, Nir, Felip, Enriqueta, Reck, Martin, Garassino, Marina Chiara
Format Journal Article
LanguageEnglish
Published United States 01.06.2023
Subjects
Artificial Intelligence
B7-H1 Antigen
Biomarkers
Carcinoma, Non-Small-Cell Lung - pathology
European Union
Humans
Immunotherapy
Lung - pathology
Lung Neoplasms - pathology
Prospective Studies
Quality of Life
Retrospective Studies
Tumor Microenvironment
Predictive biomarkers
Machine learning
Non-small cell lung cancer
Personalized medicine
Artificial intelligence
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Summary:Although immunotherapy (IO) has changed the paradigm for the treatment of patients with advanced non-small cell lung cancers (aNSCLC), only around 30% to 50% of treated patients experience a long-term benefit from IO. Furthermore, the identification of the 30 to 50% of patients who respond remains a major challenge, as programmed Death-Ligand 1 (PD-L1) is currently the only biomarker used to predict the outcome of IO in NSCLC patients despite its limited efficacy. Considering the dynamic complexity of the immune system-tumor microenvironment (TME) and its interaction with the host's and patient's behavior, it is unlikely that a single biomarker will accurately predict a patient's outcomes. In this scenario, Artificial Intelligence (AI) and Machine Learning (ML) are becoming essential to the development of powerful decision-making tools that are able to deal with this high-complexity and provide individualized predictions to better match treatments to individual patients and thus improve patient outcomes and reduce the economic burden of aNSCLC on healthcare systems. I LUNG is an international, multicenter, retrospective and prospective, observational study of patients with aNSCLC treated with IO, entirely funded by European Union (EU) under the Horizon 2020 (H2020) program. Using AI-based tools, the aim of this study is to promote individualized treatment in aNSCLC, with the goals of improving survival and quality of life, minimizing or preventing undue toxicity and promoting efficient resource allocation. The final objective of the project is the construction of a novel, integrated, AI-assisted data storage and elaboration platform to guide IO administration in aNSCLC, ensuring easy access and cost-effective use by healthcare providers and patients.
ISSN:1938-0690