SOURCE-LINKED INTELLIGENCE
Reconstruction and Computational Modelling for Inherited Metabolic Diseases
s Our overall objectives are to accelerate the diagnosis, and enable personalised management, of inherited metabolic diseases (IMDs). Established academic technology for statistical genomic analysis, deep learning-based prediction of protein structure, and whole-body metabolic network modelling shall be applied to generate personalised computational models, given patient-derived genomic, transcriptomic, proteomic and metabolomic data. To train diagnostic models, a comprehensive clinical team will recruit 1,945 diagnosed patients with a wide variety of IMDs, then validate the clinical utility of personalised computational models on a set of 685 undiagnosed patients. An enhanced human metabolic network reconstruction, especially for lipid metabolism, reaction kinetics and inherited metabolic disease pathways, will increase the predictive capacity of cellular and whole-body metabolic network models. As an exemplar for other IMDs, personalised computational modelling will be used to identify compensatory and aggravating mechanisms that associate with clinical severity in Gaucher disease
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 7871902.71
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T01:21:06.728Z. This is not the publication date.