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ELMUMY aims to elucidate the factors (clinical, epidemiological, environmental...) associated with the risk of developing Multiple Myeloma (MM), an incurable type of cancer, in patients with Monoclonal Gammopathy of Uncertain Significance (MGUS). MGUS is a blood disorder that affects between 3-5% of the population over the age of 65. A patient diagnosed with MGUS has an average risk of 1% per year of life of developing MM.  The etiology of MM is unknown, although different publications point to genetic, lifestyle and environmental factors. 
ARI's role will be to support the bioinformatics analysis and develop the AI-based personalized predictive models. Atos will develop and test the AI-based multimodal models in accordance with the ethical guidelines for reliable AI published by the European Commission.

The final outcome of the project will be a pioneering MM prediction model in patients with MGUs, in addition to the knowledge generated in MM development; the biomedical data has been generated by renowned research centers and hospitals and will be used to train and generate different predictive models of personalized risk of developing MM for patients with MGUS.

 

Our role

Atos, which has a leading role in both developing the idea and achieving the main objective of the project, will contribute its machine learning algorithm development capabilities, fostering a new generation of reliable AI applications based on multimodal analysis of heterogeneous biomedical data sources. These models can be easily adapted to address the scientific challenges of 21st century medicine: personalization and precision.

From ARI, Atos will collaborate with renowned research centers and hospitals of excellence, thus extending its network of partners and collaborators in the biomedical community. The results are expected to be published in high-impact journals and presented at various international forums and healthcare events.

Project website
Funding Program
Horizon Europe
Project Duration
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