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We are thrilled to introduce a companion project, ''Doctoral Network for Inherited Metabolic Diseases'' (DN4IMD), within the Recon4IMD consortium, designed to build upon our interdisciplinary research into inherited metabolic diseases (IMDs). This initiative explores cutting-edge approaches, including biomarker discovery, advanced computational modeling, and therapeutic innovation, to enhance the diagnosis, prognosis, and management of IMDs.With a strong focus on integrating expertise from fields such as analytical chemistry, bioinformatics, clinical medicine, and metabolic modeling, this project offers a unique opportunity to advance research while fostering international collaboration and training the next generation of IMD experts.

If you’re intrigued by our work and want to stay informed or collaborate, we’d love to hear from you! Please send your c.v. to  work package leaders or recruit.recon4imd(at)gmail.com 

Work Package 1

Development & deployment of accessible metabolic decision support tools

WP Summary

WP1 focuses on advancing tools and models to revolutionize the diagnosis, monitoring, and treatment of inherited metabolic disorders (IMDs). Highlights include the development of a structured, machine-readable database of IMDs, integration of large-language models for clinical decision support, and dynamic, whole-body metabolic modeling for infants. Cutting-edge approaches such as metabolomic data-driven personalization of metabolic models and web-based simulation tools will empower researchers and clinicians to enhance diagnostic precision, personalize treatments, and deepen mechanistic understanding of IMDs. This interdisciplinary effort combines expertise in computational biology, metabolomics, and clinical care to drive innovation and improve patient outcomes.

Work Package 2

Clinical recruitment and data management

WP Summary

WP2 focuses on recruiting patients with genetically confirmed inherited metabolic disorders (IMDs) and collecting comprehensive clinical and biological data. Through standardized phenotypic descriptions and biological sample acquisition , this work package aims to support cutting-edge research in clinical metabolomics, metabolic modeling, and proteomics. Leveraging the IMDhub platform, WP2 ensures seamless management of patient data, sample logistics, and collaborative analyses, enabling researchers to connect clinical insights with omic-driven discoveries. This interdisciplinary effort bridges clinical care and advanced computational research to enhance understanding and treatment of IMDs

Open positions

A variety of PhD, Postdoc and Clinical Fellow positions are currently open, or shall be opening shortly. Please send your c.v. to recruit.recon4imd(at)gmail.com with a one paragraph letter of motivation that indicates the work-package and task(s) below that match your interests and experience. Formal applications at the corresponding institutions may subsequently be solicited.

Work Package 3

Clinical metabolomics & metabolic modelling

WP Summary

WP3 focuses on developing advanced metabolomics methods and biomarkers to enhance the diagnosis and treatment of inherited metabolic disorders (IMDs). It includes improving global metabolomics platforms for accurate quantitation, profiling metabotypes in inherited metabolic diseases to link metabolic patterns with clinical outcomes, and identifying biomarkers for neuronopathic lysosomal storage disorders. Blood cell metabolomics will be explored for sugar metabolism disorders like Galactosaemia, while efforts to improve newborn screening will focus on uncovering metabolomic signatures for better diagnostic sensitivity. These initiatives aim to personalize treatments, refine diagnostics, and advance clinical care for IMDs.

Work Package 4

Cellular and organoid modelling of inborn errors of metabolism

WP Summary

WP4 develops advanced cellular and organoid models to evaluate the effects of treatments for inherited metabolic disorders (IMDs). Using patient-derived cells and organoids, metabolic flux analysis with isotope-labeled nutrients will assess therapeutic interventions such as amino acid supplementation and gene editing. Specific models for propionic acidemia, methylmalonic acidemia, and fatty acid oxidation disorders will provide insights into how treatments restore normal metabolic activity. Collaborative efforts will integrate omics data, metabolic modeling, and clinical findings to uncover pathways and mechanisms driving disease progression and therapeutic responses, advancing personalized medicine for IMDs.

Work Package 5

Network-wide training activities

WP Summary

WP5 provides an extensive interdisciplinary training program to equip doctoral candidates (DCs) with advanced skills in IMD research and professional development. Through the MetabERN Academy, DCs will gain accreditation in IMD diagnosis and treatment, alongside systematic training in IMD databases and classifications. Regular workshops and proficiency testing schemes will enhance collaboration and technical expertise, while annual summer schools offer hands-on training in metabolomics, computational modeling, and clinical data analytics. Opportunities for scientific dissemination, networking at SSIEM conferences, and elective specialized training with industry partners ensure DCs are well-prepared for impactful careers. A focus on career development and open science principles ensures compliance with FAIR standards and fosters professional growth.

Work Package 6 & 7

Dissemination, exploitation and outreach
& Coordination

WP Summary

WP6 and 7 focuses on dissemination, exploitation, and communication of project results and scientific advancements while raising public awareness about the benefits of interdisciplinary research on inherited metabolic disorders (IMDs). These work packages also focus on ensuring the smooth operation of the project by facilitating effective communication within the consortium and with the European Commission

Express your Interest

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