Disruptive and high accuracy test for early colorectal cancer detection in blood

Project Information

PreveCol

Grant agreement ID: 190177779

DOI

10.3030/190177779

Project closed

EC signature date 22 July 2022

Start date 1 August 2022

End date 31 March 2025

Funded under

• The European Innovation Council (EIC)

Total cost

€ 3 567 954,55

EU contribution

€ 2 497 568,00

Coordinated by

ADVANCED MARKER DISCOVERY SL
Spain

Periodic Reporting for period 2 - PreveCol (Disruptive and high accuracy test for early colorectal cancer detection in blood)

Reporting period: 2023-08-01 to 2025-03-31

Summary of the context and overall objectives of the project

With 1.93 M new cases diagnosed in 2020 and 48% mortality rate, colorectal cancer (CRC) is the second cause of cancer-related deaths worldwide. Most of these deaths could have been prevented by increasing the use of recommended screening tests. Furthermore, regular screening increases the likelihood that CRC will be detected at early stage, when it is more likely to be cured, treatment is less expensive, and recovery is faster. CRC screening programs are recommended to average risk healthy individuals from 50 to 75 years old (45-85 years in US), but compliance is a huge problem – only 10% of eligible population is screened in EU. Besides, the incidence of CRC in people younger than 50 years has increased. The use of new disruptive technologies and the identification of other relevant risk factors for the disease than age would help to define better CRC screening programs. There is a clear unmet need for cost-effective screening tests that improve population adherence and allow early CRC detection through a personalized and precise approach based on individual features.

The main objective of this project PreveCol is to develop, validate and commercialize a novel, non-invasive, blood-based test (PreveCol™) for the early detection of CRC and premalignant lesions called advanced adenomas (AA). PreveCol™ uses cutting-edge technology to screen healthy population, years in advance before the symptoms appear, extending people´s lives. PreveCol™ combines a novel set of biomarkers with a panel of risk factors (lifestyle, food, environmental as example) identified from individual clinical records through Artificial Intelligence (AI) and Big Data (BD) tools. The combination of the selected d risk factors with molecular biomarkers will enable PreveCol™ to identify patients with risk of developing CRC and/or AA improving their survival chances, avoiding invasive procedures while reducing healthcare costs. The commercialization of PreveCol™ will have clear impact in improving survival of patients and reducing mortality by CRC cancer, with better compliance, cost-effectiveness and significant cost savings for National Health Services.
PreveCol’s project approach will have two main goals:
1. Definition of new screening populations, by defining new criteria to be eligible not only based on age and;
2. The inclusion of the identified risk factors in PreveCol™ algorithm, increasing the accuracy of the test.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During the 32 months of the project the main technical achievements according to the project plan are the following ones:
Patient recruitment:
• Three protocols and clinical documentation approved by Ethical Committee and Regulatory Authorities
• Database generation and clinical data collection.
• Agreements signed by the participating sites and institutions.
• Participating Hospitals enlarged to achieve the number of participants for the clinical validation of PreveCol, risk factors analysis and cross-reactivity evaluation.
• EHR study: 6,204 EHRs from patients were extracted.
• Molecular study: 638 patients were recruited.
• Cross-reactivity study: 237 patients were recruited.
Validation of a diagnostic prediction model based on risk factors identified by big data tools:
• Extraction, anonymization, and structuring of data from the electronic health records (EHRs) of 6,204 patients with colonoscopies recorded in the last 5 years.
• Verification of the 27 risk factors identified in a previous project in this population and identification new risk factors.
• Creation of a risk factor-based algorithm capable of identifying individuals at higher risk of developing CRC or AA.

Clinical validation of PreveCol combined algorithm:
• Molecular analysis of samples.
• Develop and validate the combined algorithm including molecular data and risk factors
• Evaluation of combined algorithm’s specificity in a cross-reactivity study.
• Statistical anysis

Optimization and Industrialization of PreveCol’ IVD (In Vitro Diagnostic) kit production:
Design the components, quality controls, and manufacturing process of the prototype biomarker kit.
Development of own antibodies.
Development of software: overview of all requirements and the methodology for data interpretation.
Design the kit format (reagent container) and the kit's graphic design

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The main results achieved during the 32 months of the project are related to:
1. Identification and selection of sites and clinical Principal Investigators for the clinical studies.
2. Approval of the clinical study protocols by the Ethical Committees of Clinical Research.
3. Definition of technical and clinical protocols, agreements with the sites and regional commissions.
4. Reached the number of recruited patients and EHR in the three clinical studies necessary for the development of the algorithm.
5. Database generation, implementation and set up for clinical data collection from Electronic Health Records.
6. Identification and selection of providers for the development of proprietary reagents and technological platform for biomarker analysis, kit manufacturing and production.
7. Development of the communication and dissemination strategy.
8. Compliance with regulatory requirements to design and define both algorithm and kit.