MINERVA II Project
PERsonalized cardIoreNal Medicine in NaVArrA
The MINERVA II project seeks to identify molecular alterations in patients with cardiorenal disease characterized by the presence of chronic heart failure (CHF) and chronic kidney disease (CKD) through a multi-omics approach.
This is the continuation of the public-private consortium that worked on the first phase, the MINERVA project, in which more than 700 patients were recruited. This consortium is made up of the Cima Universidad de Navarra, which coordinates the project, the Clínica Universidad de Navarra, Navarrabiomed, the Complejo Hospitalario de Navarra and the company NNBi 2020 S.L. The MINERVA II project aims to exploit and validate the information collected in the first phase to develop a new panel of biomarkers with diagnostic utility and to identify new targets with therapeutic potential.
The patients recruited will be followed up clinically for three years, which will make it possible to test the prognostic usefulness of these biomarkers through the application of specific "omics" technology.
The results of the project will provide the basis for the development of preventive therapeutic strategies for patients with cardiorenal disease. It is anticipated that these products will help specialists in the Navarra Health System (SNS) and the Autonomous Community as a whole to apply for personalized precision medicine in the context of cardiorenal disease. This project is aligned with the RIS3 strategy of Navarra and with the bases of the European Commission's Horizon Europe program.
Coordinator and partners in MINERVA II Project
- FIMA through Cima Universidad de Navarra
- Clínica Universidad de Navarra
- Navarra Hospital Complex
- Miguel Servet Foundation through Navarrabiomed
- NNBi 2020 S.L
Objectives of the MINERVA II consortium
Specialized teams to achieve the objective
Identify diagnostic biomarkers
Develop and validate a panel of biomarkers and an associated algorithm that reflects the molecular profile of poor prognosis cardiorenal disease using bioinformatics and machine learning analysis.
To analyze the diagnostic and prognostic usefulness of the biomarkers
identified with 3-year follow-up, as well as their dynamic fluctuation according to the evolution of the patients.
To identify common mediators
to cardiorenal involvement by transcriptomic analysis of endothelial cardiovascular disease in a subpopulation of patients.
Identifying therapeutic targets
To deepen the pathophysiological role of molecules identified in cellular models and microtissues to identify potential therapeutic targets.
Identify pharmacological modulators
of the identified targets either by repositioning existing drugs or by developing small molecules.
- Isabel Gil Aldea
- Ana Purroy
- Onintza Sayar