Projects
PROJECTS WITHIN THE TRAIN NETWORK
The following section presents various translational research projects involving multiple TRAIN partner institutions. These projects were initiated by TRAIN, are currently co-coordinated or have already been completed. In addition, the section lists initiatives and projects that emerged from TRAIN events and are closely associated with TRAIN and TRAIN Omics.
All of the projects presented here are united by the shared use of infrastructures at TRAIN partner institutions and within the TRAIN network, as well as the promotion of the further development of these infrastructures. The research projects are cross-institutional and interdisciplinary and are based on close, cross-sector collaboration.
ExTENd – Expertise & Technology Exchange Lower Saxony
A planned digital platform for technology, infrastructure, and expertise in health research in Lower Saxony
Through the ExTENd (Expertise & Technology Exchange Lower Saxony) project, TRAIN is collaborating with partners to prepare for the launch of a central digital platform. This platform is designed to facilitate the connection of researchers in Lower Saxony with highly specialised technologies, scientific expertise and methodological guidance. The initial focus is on omics technologies, including genomics, transcriptomics, proteomics and metabolomics as well as bioinformatics, data analysis and data management. The implementation is the subject of a grant application that has been submitted.
ExTENd at a glance
Name: Expertise & Technology Exchange Lower Saxony (ExTENd)
Objective: To provide a central digital platform for scientific expertise, technology infrastructure, software and services.
Pilot area: Omics technologies, including bioinformatics, data analysis and data management
Partner structures: TRAIN partner institutions, TRAIN Omics, Niedersachsen.next and innomatch
Planned benefits: Improved discoverability and accessibility of technologies, data infrastructure and expertise; structured contact initiation; more efficient use of existing infrastructure; strengthening of cross-location collaborations as well as promotion of excellence, innovation and regional attractiveness
Status: Funding application submitted; implementation subject to a positive funding decision
Outlook: Expansion to additional high-end technology areas as well as training and technology transfer expertise in Lower Saxony is possible
Modern biomedical research is becoming increasingly dependent on complex technologies, high-performance data infrastructures and cross-site collaboration. ExTENd (Expertise & Technology Exchange Lower Saxony) aims to create a central digital hub to achieve this: research infrastructure, software, services, analytical methods and scientific expertise will become more visible and accessible in Lower Saxony.
TRAIN Omics connects research institutions, omics technology platforms and experts from medicine, the natural sciences, bioinformatics and data science. The initiative builds on previous TRAIN Omics activities. ExTENd intends to transform this network into a structured digital infrastructure, using the omics field as the first use case.
Key Objectives of ExTENd
The development of a digital platform that systematically catalogues technologies, services, software solutions, analytical methods and methodological expertise and presents them in a searchable format.
Examining the tax, legal and organisational frameworks for the shared use of infrastructure across institutional boundaries and identifying existing barriers. Developing solutions for communication channels, terms of use and responsibilities, with the ultimate goal of achieving harmonised access processes.
Creation of a central landing page serving as a one-stop shop where users can find relevant technologies, services, and contacts, get in touch, and eventually initiate structured inquiries or booking processes.
Applicant organizations at ExTENd:
Affiliated partner institutions at ExTENd:
The platform is to be developed in close collaboration with Niedersachsen.next and integrated into the existing digital structures of Lower Saxony’s innovation ecosystem. In this context, innomatch, the platform operated by Niedersachsen.next for connecting startups, companies, research institutions and technology transfer actors, can serve as the technical and structural foundation. In this way, ExTENd aims to link scientific infrastructure and expertise overviews with innovation- and transfer-oriented offerings in Lower Saxony.
In the long term, ExTENd is intended to be a scalable model. Following a successful Omics pilot, the platform could be gradually expanded to other technology-intensive areas, such as imaging, preclinical models, structural biochemistry, alternative methods, computer-aided analyses or transfer-oriented services.
ExTENd is currently being prepared for launch. Implementation is subject to a final funding decision.
MoReHealth Lower Saxony
A Best Practice for Standardized Multi-omics Health Research in Personalized Medicine in Lower Saxony
MoReHealth Lower Saxony is a collaborative project focused on personalized medicine in Lower Saxony. The project aims to establish a standardized, multi-omics-based data and analysis infrastructure, using age-related susceptibility to infection as a case study, that can serve as a prototype for a state-wide molecular research data infrastructure in personalized medicine.
The research focuses on the scientific question of how individual molecular profiles can be used to better understand risks, disease progression and potential prevention and treatment approaches for infectious diseases. As a specific medical use case, the study examines age-related susceptibility to herpesvirus infections, particularly to the varicella-zoster virus and severe cases of herpes zoster (shingles).
This project integrates clinical cohorts, biobanking, multi-omics technologies, bioinformatics, data management and AI-driven analyses. In doing so, MoReHealth addresses a key challenge in personalized medicine: the quality-assured, standardized and interoperable use of complex molecular, functional and clinical data for research, prevention, diagnosis and treatment.
MoReHealth was established on the initiative of TRAIN and the RESIST Cluster of Excellence. It strengthens translational health research in the Hannover–Braunschweig–Göttingen region.
MoReHealth Lower Saxony at a Glance
Project duration: 09/2025 – 08/2029 Total grant amount: approx. 3 million euros
Funding Program: “New Challenges in Personalized Medicine in Prevention, Diagnosis, and Treatment” Funding: zukunft.niedersachsen, a joint funding program of Lower Saxony Ministry of Science and Culture and Volkswagen Foundation
Key objectives of MoReHealth Lower Saxony
First, existing datasets from the RESIST Senior Individuals cohort will be expanded and completed. These include high-dimensional flow cytometry, transcriptomic data and cytokine measurements. In addition, cutting-edge technologies such as long-read genome sequencing, mtDNA sequencing and quantitative metabolomics will be applied to selected samples.
Particular emphasis is placed on quality assurance throughout the entire process chain, from sample processing and data collection to analysis. To this end, standardized workflows, SOPs and quality-assured processes are established.
As part of MoReHealth, a scalable, secure and GDPR-compliant multi-omics data platform is being developed. It is designed to bring together clinical, molecular, functional and omics data in a structured manner and enable its use via defined governance, metadata and access processes.
The platform will initially be developed to house data from the RESIST Senior Individuals cohort. In the future, it is intended to serve as a prototype for a molecular health data repository in Lower Saxony and to be expandable for additional projects and disease areas.
The focus here is on the development and use of AI-based analytical tools to integrate individual and multiple omics levels. The goal is to identify diagnostic and prognostic biomarkers for severe cases of herpes zoster and to decipher the molecular networks that contribute to the onset of the disease and its complications.
AI-driven network and biomarker analyses are intended to identify molecular signatures, pathophysiological mechanisms and potential therapeutic targets.
Norddeutscher Rundfunk (NDR) has produced a video report on MoReHealth Lower Saxony.
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Consortium / Principal Investigators
Hannover Medical School, Hannover Unified Biobank
Prof. Dr. Thomas Illig (Project Manager & Spokesperson for the Steering Committee)
Dr. Sara Haag (Head of Project Management)
Dr. Markus Kersting
Hannover Medical School, Institute of Immunology
Prof. Dr. Reinhold Förster (Deputy Spokesperson for the Steering Committee)
Prof. Dr. Sarina Ravens
Hannover Medical School, Department of Dermatology and Allergy
Dr. Lennart Rösner
Prof. Dr. Thomas Werfel
Peter L. Reichertz Institute for Medical Informatics
Prof. Dr. Helena Zacharias
Helmholtz Centre for Infection Research, Department Experimental Immunology
Prof. Dr. Jochen Hühn
Technical University Braunschweig, Braunschweig Integrated Centre of Systems Biology
Prof. Dr. Thekla Cordes
Prof. Dr. Karsten Hiller
University Medical Center Göttingen, Institute of Human Genetics
Dr. Julia Schmidt
Prof. Dr. Bernd Wollnik
Physikalisch-Technische Bundesanstalt, Department of Biochemistry (Associate Partner)
Prof. Dr. Gavin O’Connor
Contact Person:
Dr. Sara Haag, TRAIN – Translationsallianz in Niedersachsen
Contact: sara.haag[at]translationsallianz.de
ImProVIT (2019 – 2022)
Transforming big data into knowledge: for deep immunoprofiling in vaccination, infectious diseases and transplantation
The immune system plays a central role in health and disease, but the available immune monitoring techniques (particularly FACS-based analysis of PBMCs) are expensive, time-consuming and difficult to reproduce. Moreover, they primarily provide distribution data and very little functional information.
ImProVIT creates a knowledge-based framework that standardizes and integrates heterogeneous datasets from conventional flow cytometry (FACS) and innovative methods (chip cytometry, T/B cell receptor repertoire, single-cell analysis, cytokine arrays, transcriptomics, whole-genome sequencing). These data are consolidated into a knowledge graph enriched with biomedical ontologies (HPO, OMIM), thereby mapping the human immune system under homeostasis, following vaccination, infection or transplantation.
Using knowledge management and pattern discovery methods, researchers can identify, characterize and investigate new immunological patterns. The goal is to optimize immunoprofiling, which improves diagnostics, personalizes therapies and accelerates the development of new vaccines.
ImProVIT at a Glance
Objective: To gain a comprehensive understanding of the human immune system in both healthy and diseased states
Methodology:
- Integration of immunomonitoring data with information from open-source databases and ontologies to create a knowledge-based framework
- Development and validation of predictions (e.g., vaccine responsiveness, transplant rejection, or tolerance)
Project duration: Oct. 2019 – Sept. 2022
Total funding: approx. 1.1 million euros
Funding program: “Big Data in the Life Sciences of the Future”
Funding: zukunft.niedersachsen, a joint funding program of Lower Saxony Ministry of Science and Culture and Volkswagen Foundation
An interdisciplinary consortium of immunologists, clinicians and data scientists developed a methodology for determining patients’ immune status. To this end, immunomonitoring protocols were established and the resulting data were combined with other clinical data from the same patients as well as with information from various biomedical databases.
The combined data served as the basis for creating a so-called knowledge graph, which contributed to a better understanding of the human immune system. Furthermore, the knowledge graph formed the basis for predicting responses to new vaccines, for identifying biomarkers for transplant rejection or tolerance and helped predict the course and outcome of infectious diseases. The knowledge graph was continuously expanded with new data generated using a variety of immunological methods. The goal was to continuously expand knowledge of the human immune system and to establish immune monitoring as a standardized method for providing information on each patient’s immune status.
This knowledge will help develop optimized treatment options for patients and use the newly gained insights as a basis for the development of new intervention strategies and vaccines.
Consortium
TWINCORE Center for Experimental and Clinical Infection Research GmbH
Prof. Dr. Ulrich Kalinke
Technical Information Library (TIB)
Prof. Dr. Maria-Esther Vidal
Hannover Medical School (MHH)
Prof. Dr. Christine Susanne Falk
Hannover Medical School (MHH)
Prof. Dr. Markus Cornberg
TWINCORE Center for Experimental and Clinical Infection Research GmbH
PD Dr. Frank Pessler
Helmholtz Center for Infection Research (HZI)
Prof. Dr. Carlos Alberto Guzmán
INDIRA (2019 – 2022)
INtegrative Data analytIcs for Respiratory syncytiAl virus RIsk Assessment
The respiratory syncytial virus (RSV) is the most common cause of lower respiratory tract infections in infants. The course and outcome of a primary RSV infection vary widely and the factors that determine a severe course of the disease are not well understood. A prophylactic antibody is used to protect infants at very high risk (e.g., due to prematurity). However, because knowledge about the risk factors for RSV infection is incomplete, not all children in need can be protected.
Goal of INDIRA is to identify biomarkers that predict severe RSV disease and to understand how they influence disease severity.
INDIRA integrates comprehensive biological and clinical datasets from patients with severe primary RSV infection. Using computational methods, including machine learning techniques, individual markers and combinations of markers are linked to severe disease and validated in functional virological and immunological experiments.
The project aims to gain new insights into the determinants of severe RSV infections in infants in order to develop molecular diagnostics that will ultimately enable personalized prophylaxis for the most at-risk infants.
INDIRA at a Glance
Objective: Development of novel diagnostic methods for respiratory syncytial virus (RSV) infections
Methodology:
- Integration of multi-omics data to analyze the course and outcome of RSV infections in infants.
- Identification of a panel of genetic and/or quantitative biomarkers that predict disease severity
Project duration: 09/2019 – 08/2022
Total funding: approx. 1.1 million euros
Funding line: “Big Data in the Life Sciences of the Future”
Funding: zukunft.niedersachsen, a joint funding program of Lower Saxony Ministry of Science and Culture and Volkswagen Foundation
Consortium
TWINCORE Center for Experimental and Clinical Infection Research GmbH
Prof. Dr. Thomas Pietschmann
Hannover Medical School (MHH)
Prof. Dr. Thomas Illig
University Medical Center Greifswald
Prof. Dr. Lars Kaderali
Gottfried Wilhelm Leibniz University Hannover
Prof. Dr. Jörn Ostermann
Gottfried Wilhelm Leibniz University Hannover
Prof. Dr. Bodo Rosenhahn
Helmholtz Centre for Infection Research (HZI)
Dr. Robert Geffers
Leibniz Institute DSMZ—German Collection of Microorganisms and Cell Cultures GmbH
Prof. Dr. Jörg Overmann
Hannover Medical School (MHH)
Prof. Dr. Gesine Hansen
Technical University of Braunschweig
Prof. Dr. Karsten Hiller
FibrOmics (2019 – 2022)
Translating Omics studies into clinically relevant insights for lung fibrosis patients
Pulmonary fibrosis incurs healthcare costs of 10 billion euros and approximately 750,000 people in Europe are affected by the disease. Idiopathic pulmonary fibrosis (IPF) is the most common form of this disease, with an estimated median survival time of 3 years and a variable disease course. The number of deaths due to fibrosis is twice that of cancer. After more than two decades of research, available therapies extend the median survival time of treated patients to only 4.5 to 5 years. A significant part of the history of drug development for IPF can be attributed to substantial limitations in the available models.
Recent advances in single-cell RNA sequencing technologies enable researchers to capture cellular activity in fibrotic lungs with unprecedented detail. They can examine subpopulations of cells using integrative computational analysis to deepen the understanding of the underlying mechanisms and signaling pathways of IPF. By applying these data to pharmaceutical risk assessment, the disease signatures will also enable the development of alternative methods for hazard characterization, thereby reducing the need for animal testing.
Given the complexity of fibrotic diseases, as well as the technological challenges and opportunities arising from novel sequencing technologies, a key strength of this project lies in its interdisciplinary approach, which brings together expertise in medicine, biology and data science at three leading research institutions in Hannover.
FibrOmics at a Glance
Objective: To understand the underlying mechanisms and signaling pathways of pulmonary fibrosis using single-cell RNA sequencing technologies
Project duration: Oct. 2019 – Sept. 2022
Total funding: approx. 1.1 million euros
Funding program: “Big Data in the Life Sciences of the Future”
Funding: zukunft.niedersachsen — a joint funding program of Lower Saxony Ministry of Science and Culture and Volkswagen Foundation
Consortium
Hannover Medical School (MHH)
Prof. Dr. David deLuca
Hannover Medical School (MHH)
Prof. Dr. Thomas Illig
Hannover Medical School (MHH)
Prof. Dr. Antje Prasse
Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM)
Prof. Dr. Sylvia Escher
University of Veterinary Medicine Hannover
Prof. Dr. Klaus Jung
