Ongoing
The MIRIADE (Multi‐omics Interdisciplinary Research Integration to Address DEmentia diagnosis) project brings together a multidisciplinary team of scientists from academia, industry and patient organizations. The goal is to train a new generation of young scientists to optimize and accelerate the development of novel biomarkers for dementia. A total of 15 PhD students, residing in 8 different countries across Europe, learn a unique combination of skills in big data analysis, biomarker assay development, innovation management, and a thorough understanding of medical needs.

Biomarker Identification

The need for novel biomarkers for dementias is high as they could help in differentiating different types of dementia as well as understanding the underlying disease pathologies. In MIRIADE, multiple datasets will be combined to identify possible biomarker candidates and further characterization of the proteins will help to predict the best assay conditions.

Assay Development

Assays for previously identified biomarker candidates will be developed based on different methodologies. These assays will be thoroughly validated for their analytical and clinical reliability and will be prepared for commercialization to facilitate usage in clinical practice.

Process Analysis

The complete process from biomarker identification over assay development to commercialization will be analyzed regarding experimental hurdles, collaboration and data sharing. Based on these results, a dementia roadmap will be established that will show possible obstacles in biomarker development and suggest how to overcome these.

Partners

ADX Neurosciences, Alzheimer Europe, Alzheimer Nederland, Centre Hospitalier Universitaire Montpellier, ENPICOM, Gachon University, Instituto de Salud Carlos III, KTH Royal Institute of Technology, LGC Limited, Olink Proteomics, PeopleBio Inc., Quanterix Corporation, Roche Diagnostics, Amsterdam UMC, University of Gothenburg, University of Luxembourg, University of Montpellier, University of Perugia, Ulm University, Vrije Universiteit Amsterdam.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197.