Reconstruction and Computational Modelling for Inherited Metabolic Diseases (Recon4IMD)

Inherited metabolic diseases (IMDs) are a collection of ~1,450 rare diseases, each with a prevalence < 0.2% and each of which is caused by a genetic defect in a metabolic pathway1. For a considerable proportion of IMDs, specific therapies are available that can dramatically improve patient outcomes, so it is essential to achieve an accurate and timely diagnosis.
● Overall objectives: Accelerate diagnosis and personalise management of inherited metabolic diseases.
● Primary output: Clinically validated decision support tools enabling accelerated diagnosis and personalised management of inherited metabolic diseases, based on genomic, proteomic, and metabolomic data-driven computational models.
● Sustainability: Development of academic technology to meet medical regulatory standards and a roadmap for exploitation within a European foundation to aid personalised diagnosis and management of inherited metabolic diseases.
● Implemented by: A group of world-class scientists and clinicians from a diversity of disciplines who have collaborated multiple times and have a track record of leading key national and EU-funded initiatives to deliver high-impact results.

Overall objective: To accelerate the diagnosis of patients at risk of an IMD by computational modelling of genetic risk, enzyme structure, and metabolic networks, personalised using genomic, proteomic and metabolomic data.

This project is being led at DkIT by Dr Zaffar Haider in developing a Process Assessment Model to to aid the software developments within this project towards regulatory compliance.

https://www.recon4imd.org/

Recon4IMD is co-funded by the European Union's Horizon Europe Framework Programme (101080997), the Swiss State Secretariat for Education, Research and Innovation (23.00232), and by United Kingdom Research and Innovation (10083717 & 10080153).