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Cola

mCRC subjects with WT (wild type) and RAS (matated)

The aim of using AI software to support physicians in choosing the most effective treatment.

Mario Roselli, PI

Enrico Mini, PI

Giandomenico Roviello, MD

Antonio Russo, PI

Antonio Galvano, MD, PhD

Silvia Riondino, Sub-Inv

Constantin Volovat, PI

Bogdan Gafton, PI

Eliza M Froicu, MD, PhD

Pablo Conesa-Zamora, PI

This is a clinical prospective, no-Profit, Interventional, Premarket Medical Device "early phase", multicentre, single-arm study, based on collecting data on predictive biomarkers of mCRC patients, integrate them with the results of the retrospective evaluation of outcomes and profiles of historical mCRC patients previously treated in the Oncology Units, in order to evaluate the efficacy of the best administered treatment. Results from the retrospective evaluation, will serve to build an AI-based profile capable to identify "good" or "poor" responders to therapy and to support the clinician towards the best treatment option. AI is a software based on algorithm defined as Medical Device Class IIa.

This is a clinical prospective, no-Profit, Interventional, Premarket Medical Device "early phase", multicentre, single-arm study, based on collecting data on predictive biomarkers of mCRC patients, integrate them with the results of the retrospective evaluation of outcomes and profiles of historical mCRC patients previously treated in the Oncology Units, in order to evaluate the efficacy of the best administered treatment. Results from the retrospective evaluation, will serve to build an AI-based profile capable to identify "good" or "poor" responders to therapy and to support the clinician towards the best treatment option. Following the first disease progression (PD), 2nd line therapy will be at Investigator's choice. The drugs under investigation are those commonly employed in mCRC patients as per usual standard of care. Artificial Intelligence (AI) is a software based on algorithm defined as Medical Device Class IIa.

The REVERT clinical trial is study, inserted within a wider European Project. The clinical study will take advantage of the results of the retrospective evaluation of mCRC patients' outcomes and profiles, aimed at evaluate the efficacy of treatment strategies, that will performed during the early activities of the European Project. In such retrospective analysis AI and Machine Learning (ML) will be instructed and used to derive predictive clinical data, after having analysed all possible variables including known mutational, biochemical and clinical features of samples from mCRC patients historically treated in the Oncology Units participating to the project and stored in partner Biobanks. AI and ML methodologies are based on Support Vector Machines and combine Multiple Kernel Learning and Random Optimization, incorporating already available large databases with new, potential prognostic/predictive biomarkers (e.g., gene mutations, epigenetic changes, gene expression profiling signatures). The emerging results will be used to help the choice of the best combinatorial therapy, for every prospectively enrolled mCRC patient. Sex and gender differences, also according to sidedness, will be analysed to evaluate their impact on survival and quality of life (QoL) in patients with mCRC.

Study length is planned to be about 24 months (12 months recruitment + 12 months of follow-up). The end of study is defined as the time when all enrolled patients will have experienced evidence of disease progression or will be out of treatment as per protocol, toxicity, medical decision or patient's withdrawal.

Patients, male and female, age ≥18 years, with WT (wild type) and RAS mutated (mut) affected by mCRC.

REVERT - taRgeted thErapy for adVanced colorEctal canceR paTients

Progression Free Survival (PFS), including PFS1 and PFS2, defined as the time from enrolment to the first documentation of objective disease progression or death due to any cause, whichever occurs first.

The time from enrolment to the date of death due to any cause. For patients still alive at the time of analysis, the OS time will be censored on the last date the patients were known to be alive.

The percentage of patients, relative to the total of enrolled subjects, achieving a complete (CR) or partial (PR) response, according to RECIST 1.1 criteria, during the phases of treatment.

As the percentage of patients, relative to the total of the enrolled subjects, achieving a \>20% decrease in the sum of diameters of RECIST target lesions.

measured using the EORTC QLQ-C30 questionnaire

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