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    University of Skövde, link to startpage

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      University of Skövde, link to startpage

      Transplant Tissue Engineering

      Research Group Translational Bioinformatics
      Resarch Environment Systems Biology

      Quick Facts

      Full project name

      Transplant Tissue Engineering

      Duration

      April 2019 – September 2021

      Funding and collaboration

      The Knowledge Foundation, VeriGraft, XVIVO

      The Transplant Tissue Engineering (TransTissuE) is a collaboration project between the University of Skövde, VERIGRAFT and XVIVO. We develop methods and strategies for optimization of the production process of personalized tissue-engineered vascular transplants.

      These transplants are manufactured by the removal of the cellular content, decellularization (DC), from donor blood vessels while preserving the structural and functional molecular units of the remaining extracellular matrix (ECM). A recellularization (RC) procedure is then applied to repopulate the ECM with autologous cells and other components from blood samples from the recipient patient (Figure 1).This strategy allows the modulation of the immunological response system and limits implant rejection. However, knowledge about how this critical modulation is controlled is still lacking. By applying extensive data analysis on large-scale omics datasets, the project aims to implement a modeling approach to reveal how the risk of implant rejection could be reduced. 

      How does the procedure for manufacturing transplants work?

      After isolating and decellularizing the donated blood vessels, the extracellular matrix is recellularized with whole blood from the recipient patient. The customized blood vessel is then implanted into the patient. Sample collection for the generation of omics data will be carried out continuously during the procedure.

      Large-scale data mining

      The project will analyze comprehensive proteomics and transcriptomics datasets from the different stages during the DC and RC procedures of blood vessels (Figure 2). Advanced large-scale data mining will be applied to these complex omics datasets, including machine learning techniques to investigate the mechanisms related to the modified immunological response and reduction in transplant rejection. Furthermore, biomarkers will be identified and selected for development of decision support systems for quality control of the RC and DC processes.

      Development of personalized transplants

      The results of this project are anticipated to contribute to the development of personalized transplants and to improved treatments for patients with damaged blood vessels.

       

      Project Leader

      Participating Researchers

      Annelie Sigvardsson
      Intellectual Property Manager and R&D project leader at XVIVO Perfusion
      Lachmi Jenndahl
      Tissue Engineer VERIGRAFT
      Petter Björquist
      CEO VERIGRAFT
      Raimund Streil
      CTO VERIGRAFT
      Published: 1/10/2020
      Edited: 1/10/2020
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