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I3LUNG: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy

Sponsored by Fondazione IRCCS Istituto Nazionale dei Tumori, Milano

About this study

I3LUNG is an international project aiming to develop a medical device to predict immunotherapy efficacy for NSCLC patients using the integration of multisource data (real word and multi-omics data). This objective will be reached through a retrospective - setting up a transnational platform of available data from 2000 patients - and a prospective - multi-omics prospective data collection in 200 NSCLS patients - study phase. The retrospective cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model), that will be used in the prospective study phase to create a first version of the PDSS tool, an AI-based tool to provide an easy and ready-to-use access to predictive models, increasing care appropriateness, reducing the negative impacts of prolonged and toxic treatments on wellbeing and healthcare costs. The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. This cohort will be used to validate the results obtained from the retrospective model through the creation of a new model (P-Model), which will be used to create the final PDSS tool.

The I3LUNG project aims to achieve the highest performance in personalized medicine through Artificial Intelligence/Machine Learning (AI/ML) modelled on multimodal patients' data, together with implementing an AI/ML model in a real-life setting. A set of patient-centered ML tools designed and validated for the project, which make use of the novel virtual patient AVATAR entity for predicting progression and outcome. To maximize its impact, the use of Trustworthy explanaible AI methodology will integrate the AI's inherent performances with the input of human intuition to construct a responsible AI application able to fully implement truly individualized treatment decisions in NSCLC interpretable and trustworthy for clinicians. The final objective is the establishment of a Worldwide Data Shar…

Where this study is enrolling

Who can participate

Inclusion criteria

  • ✓Age \>/= 18 years.
  • ✓Eastern Cooperative Oncology Group (ECOG) performance status \</= 2.
  • ✓Histologically confirmed diagnosis of stage IIIB/C-IV Non-Small-Cell Lung Cancer
  • ✓Received any line immunotherapy (maintenance therapy with Durvalumab is allowed) for retrospective cohort; clinical indication for frontline treatment with immunotherapy as first line treatment for prospective cohort.
  • ✓Patients with CNS metastasis are allowed
  • ✓Patients with driver genomic alterations are allowed (only for retrospective cohort)
  • ✓Evidence of a personally signed and dated ICF indicating that the patient has been informed of and understands all pertinent aspects of the study before enrolment (only for prospective cohort)
  • ✓Availability of at least one FFPE block for -omics data generation (only for prospective cohort)

Exclusion criteria

  • ✕Patients without minimal treatment information data to be included in the retrospective cohort
  • ✕Prior treatment for advanced disease (only for prospective cohort)
  • ✕Unavailability or inability to comply with the requested study procedures, including compilation of QoL questionnaires

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Trial data sourced from ClinicalTrials.gov.