Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT05550961 |
Other study ID # |
INT128/22 |
Secondary ID |
|
Status |
Recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
October 1, 2022 |
Est. completion date |
October 1, 2032 |
Study information
Verified date |
October 2023 |
Source |
Fondazione IRCCS Istituto Nazionale dei Tumori, Milano |
Contact |
Arsela Prelaj, M.D. |
Phone |
+390223903647 |
Email |
arsela.prelaj[@]istitutotumori.mi.it |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
APOLLO 11 main aim is to build a strong Italian long-lasting lung cancer network (in around
48 Italian centres) on real world data and translational research by creating a decentralized
long-term national database (settle locally in each centre) and a "virtual" multilevel
biobank in each centre. Besides, APOLLO 11 will take advantage of the translational research
joint effort with the credo "unity is strength".
Description:
With the advent of several innovative therapies ("target" therapies, immunotherapy (IO)
and/or next generation therapies), the identification of prognostic/predictive and/or
resistance biomarkers represents the main goals of translational research in advanced lung
cancer (aLC). In particular, with the arrival of IO the treatment landscape of advanced
Non-Small Cell Lung Cancer (NSCLC) patients (pts), have radically changed prolonging
significantly the overall survival (OS). The role of Programmed Death Ligand 1 (PD-L1)
remains undefined and to date no other biomarker are used to select patients for IO.
Artificial Intelligence (AI) frameworks, which synthesize and correlate information from
different data sources, is a potentially highly efficient instrument to construct algorithms
reinforcing the individualized prediction.
APOLLO 11 main aim is to build a strong Italian long-lasting lung cancer network (in around
48 Italian centres) on real world data and translational research by creating a decentralized
long-term national database and a "virtual" multilevel biobank. This will allow to avoid
worthless dispersion of single institution data, which often remaine unused and inconclusive
due to limited number of patients and low statistical power. Besides, APOLLO 11 will take
advantage of the translational research joint effort with the credo "unity is strength". The
multilevel structure is designed also for smallest centres of give them possibility to
contribute to biobank looking at their internal facilities.
APOLLO 11 have the goal to establish the consortium by fully activating at least 20 of the 48
involved centres able to collect data within the database and to guarantee the activation
ready for at least 10 biobanks able to collect samples (tumour tissue, blood, stool and
urine). Moreover, the key scientific aim of the project is to provide answers about aNSCLC
pts treated with IO. In particular, try to find a "software" biomarker able to better predict
IO selection compare to standard of care single biomarker (e.g., PD-L1, TMB) using artificial
intelligence/machine/deep learning (AI/DL/ML) methodologies. Real world (demographic,
histology, PD-L1, molecular, treatment and outcomes information etc), radiomics and where
available (from previous researches) multiomic data from all the activated centres will be
collected. Furthermore, single-cell RNA sequencing (scRNA seq) analysis will be carry out.
Finally, AI/ML/DL will be used to integrate the multisource data, analyse them and develop
predictive algorithms of IO efficacy in NSCLC pts. Explainable trustworthy AI (XAI)
methodology will be used in order to better understand black box for explaining clinical and
biological insight.