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Engineering scalable immobilized cell culture systems for diabetes cellular therapy

Engineering scalable immobilized cell culture systems for diabetes cellular therapy
用于糖尿病细胞治疗的可扩展固定化细胞培养系统
批准号:
RGPIN-2020-05877
负责人:
Hoesli, Corinne
金额:
$2.4万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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英文摘要
Advances in stem cell research and tissue engineering have led to the development of complex three-dimensional (3D) tissue constructs that hold great promise for disease modelling as well as tissue replacement. The long-term goal of this research program is to develop scalable therapeutic cell production and transplantation systems, in particular for diabetes cellular therapy. The 5-year goal of this program is to optimize methods for hydrogel immobilized culture of islet-like cell clusters (ILCs). The specific aims of the 5-year program are to (1) microencapsulate ILCs by microchannel emulsification, (2) generate vascularized ILC-containing constructs, (3) optimize vessel geometries based on oxygen mass transfer models and (4) study the effects of oxygen tension and vascular cells on ILC differentiation. First, a highly scalable microchannel emulsification process developed in my laboratory will be adapted to better control bead residence time in acidified oil. After assessing cell survival and function, the microencapsulated ILCs will be cultured in vascularized cm scale tissue constructs as a potential macroencapsulation system. These vascular channels will be generated through embedded writing of sacrificial materials into ILC-containing hydrogel support matrices. To do so, a fugitive bioink will be 3D printed into the support matrix material, which will be selected based on its vasculogenic potential, mechanical properties and print fidelity. After gelation of the support matrix, the fugitive ink will be evacuated to create hollow channels. Following ILC survival and functional assessment, the resulting tissue constructs will be cultured under perfusion for several weeks to allow ILC maturation. To optimize vascular lattice geometries, a numerical model predicting oxygen tension profiles in constructs of different configuration will be developed. Model predictions will be compared to experimental oxygen concentration profiles determined using a paramagnetic oxygen-sensitive probe. These studies will be conducted with or without adding vascular endothelial cells into the vasculogenic support matrix to study their interactions with the ILCs. These studies will pave the way towards engineering a vascularized bioartificial pancreas used for in vitro drug testing as well as eventual transplantation. The proposed research program provides fertile grounds for training highly qualified personnel, which includes 3 PhDs, 1 Master's and 5 undergraduate trainees. This research program is expected to have far-reaching impact on the biomedical community and the health of Canadians. Translation of the research findings will be accelerated by existing collaborations with industry and clinicians.
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Cellular Therapy Bioprocess Engineering
  • 批准号:
    CRC-2016-00058
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $2.19万
  • 财政年份:
    2022
  • 负责人:
    Hoesli, Corinne
  • 依托单位:
Canada Research Chair in Cellular Therapy Bioprocess Engineering / Chaire de recherche du Canada en génie des bioprocédés pour la thérapie cellulaire
  • 批准号:
    CRC-2021-00246
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $5.46万
  • 财政年份:
    2022
  • 负责人:
    Hoesli, Corinne
  • 依托单位:
Engineering scalable immobilized cell culture systems for diabetes cellular therapy
  • 批准号:
    RGPIN-2020-05877
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2022
  • 负责人:
    Hoesli, Corinne
  • 依托单位:
Cellular Therapy Bioprocess Engineering
  • 批准号:
    CRC-2016-00058
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $8.74万
  • 财政年份:
    2021
  • 负责人:
    Hoesli, Corinne
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis