Integrative platform for personalized lung cancer care using AI
I3LUNG: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy
This study is trying to create a smart tool that helps doctors predict how well immunotherapy will work for people with non-small cell lung cancer, so they can make better treatment choices.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 2200 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Fondazione IRCCS Istituto Nazionale dei Tumori, Milano Academic / other |
| Drugs / interventions | Durvalumab, immunotherapy |
| Locations | 4 sites (Chicago, Illinois and 3 other locations) |
| Trial ID | NCT05537922 on ClinicalTrials.gov |
What this trial studies
I3LUNG is an international initiative focused on developing a medical device that predicts the efficacy of immunotherapy for patients with non-small cell lung cancer (NSCLC) by integrating diverse data sources, including real-world and multi-omics data. The project consists of a retrospective phase involving data from 2000 patients to create a predictive model, followed by a prospective phase that collects multi-omics data from 200 NSCLC patients. The aim is to enhance personalized medicine through AI and machine learning, ultimately leading to the creation of a user-friendly decision support tool for clinicians and patients. This tool will help in making informed treatment decisions while minimizing the negative impacts of prolonged therapies.
Who should consider this trial
Good fit: Ideal candidates include adults aged 18 and older with stage IIIB/C-IV NSCLC who have received immunotherapy.
Not a fit: Patients with early-stage lung cancer or those who have not received any form of immunotherapy may not benefit from this study.
Why it matters
Potential benefit: If successful, this project could significantly improve treatment personalization for NSCLC patients, leading to better outcomes and reduced side effects.
How similar studies have performed: Other studies utilizing AI and multi-omics approaches in cancer treatment have shown promise, indicating potential success for this novel approach.
Eligibility criteria
Show full inclusion / exclusion criteria
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
Where this trial is running
Chicago, Illinois and 3 other locations
- University of Chicago — Chicago, Illinois, United States (Recruiting)
- Metropolitan Hospital — Athens, Greece (Recruiting)
- Shaare Zedek Medical Center — Jerusalem, Israel (Recruiting)
- Vall D'Hebron Institute of Oncology — Barcelona, Spain (Recruiting)
Study contacts
- Study coordinator: Arsela Prelaj, MD
- Email: arsela.prelaj@istitutotumori.mi.it
- Phone: +39 022390 3647
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.