The REVERT project will address the specific challenge of understanding at system level the pathophysiology of mCRC cancer in patients responding well or poorly to therapies, in order to design optimal strategy for mCRC on a case by case basis, with therapeutic interventions modulated depending on patient’s features.

Accordingly, REVERT will build up an innovative artificial intelligence (AI)-based decision support system using the experience and the real-world data of several general Hospitals operating in the EU healthcare system ultimately aimed at developing an improved and innovative model of combinatorial therapy - based on a personalised medicine approach - that identifies the most efficient and cost-effective therapeutic intervention for patients with unresectable mCRC.

This goal will be pursued through the building of the REVERT-DataBase (RDB) thanks to a large number of standardized biobank samples with related structured data, and clinical databases (including known clinical and biological features as well as new, potential prognostic/predictive biomarkers) from several major clinical European centres.

The RDB, in turn, will be used to build a sophisticated computational framework based on AI to evaluate its impact on survival and quality of life in a prospective clinical trial through testing of new treatment sequences of the available and authorised molecular targeted drugs in patients with mCRC.

In the end, the REVERT will also generate an EU- network among SMEs, Research Institutions, Clinical Centres and Biobanks focused on R&D in the field of AI-Health for the development of personalised medicine.

The REVERT software system will ensure the integrity of data and privacy management in respect to national rules, the EU's GDPR (Reg. EU 2016/679) and the EU Charter of Fundamental Rights.

The RDB and AI services will be open to all partners during and after project’s completion, available also to EU research Institutions for future studies.

Work Plan

Leader: San Raffaele

Objectives:

  1. To effectively monitor the project, in administrative and financial terms (Project follow-up, i.e. project progress control and planning)
  2. To guarantee the adherence to the work plan, to the overall project aim, available resources and timing with continuous update of project status to the European Commission
  3. To undertake quality assessment of the REVERT progress, results and impact
  4. To secure timely submission of interim progress reports and cost statements to the Commission
  5. To ensure that “Description of Work” and “Consortium Agreement” are maintained and updated when necessary
  6. High-level commitment with in-depth demonstration interactions

Leader: San Raffaele

Objectives:

  1. Produce a FAIR-Data Management Plan (DMP)
  2. Define the platform core services, data Representation and data management
  3. Guarantee cyber-security and legally compliant archiving of data respecting specific EU and national recommendations
  4. Build a web application which allows REVERT users to login and access data
  5. Ensure RDB maintenance and implementation throughout the project

Leader: UCAM

Objectives:

  1. Develop, implement and test ML-based predictive models (rational and interpretable) relevant to the clinical outcome of a specific treatment
  2. Define and implement a mobile app that will be used to facilitate the access to the predictive models available to the end users

Leader: LIH

Objectives:

  1. Standardization of preanalytical phases and production of shared SOPs
  2. Production of shared procedures for quality monitoring of preanalytical phases
  3. Standardization, analytical validation and clinical validation of analytical methods
  4. Production of shared procedures and choice of the QC material(s) for quality monitoring of analytical phases
  5. Assessment and validation of decision criteria suitable to translate biomarker results into clinical practice

Leader: MALMO UNIV

Objectives:

  1. To perform retrospective studies of traditional and innovative clinical biomarkers in mCRC using molecular diagnostics and imaging
  2. To develop and validate AI stratification models for tailored treatment in this clinical setting

Leader: UNITOV

Objectives:

  1. To evaluate the efficacy of the chosen treatment strategy, in terms of Progression-Free Survival (PFS1 and PFS2), Response Rate (RR), including both Early Tumour Shrinkage (ETS) and Depth of Response (DoR), Overall Survival (OS) and Quality of Life (QoL)

Leader: ULSS 4 - ProMIS

Objectives:

  1. To disseminate project knowledge, standards and results during the project duration
  2. To disseminate to relevant stakeholders and the general public information about innovative alternative therapy to treat mCRC patients with, the project outcomes and current results
  3. To create an effective and tangible dissemination and communication plan
  4. To develop a strategy for commercial exploitation of the results

Leader: San Raffaele

Objectives:

  1. To ensure compliance with the 'ethics requirements' set out in this work package