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3D Printing of Neural Tissues Derived from Human Induced Pluripotent Stem Cells Using a Fibrin-Based Bioink
Emily Abelseth, Laila Abelseth, Laura De la Vega
1Aspect Biosystems, 1781 W 75th Avenue, Vancouver, British Columbia V6P 6P2, Canada.
ACS Biomaterials Science & Engineering
|January 6, 2021
Summary
This study details 3D bioprinting of human induced pluripotent stem cell (hiPSC)-derived neural aggregates. Researchers developed specialized bioinks and methods for creating 3D neural tissues for regenerative medicine applications.
Area of Science:
- Biomaterials Science
- Stem Cell Biology
- Tissue Engineering
Background:
- 3D bioprinting automates tissue engineering by positioning cells in bioinks to create tissue replacements.
- Human induced pluripotent stem cells (hiPSCs) are crucial for neural tissue engineering due to their expansion and differentiation capabilities.
- Current neural differentiation protocols involve hiPSC aggregates in microwells, but 3D bioprinting of these aggregates is underexplored.
Purpose of the Study:
- To develop and report methods for 3D bioprinting of hiPSC-derived neural aggregates.
- To create specialized bioinks supporting cell survival and differentiation into mature neural phenotypes.
- To demonstrate the feasibility of generating 3D neural tissues using advanced bioprinting technology.
Main Methods:
- Preparation of base material components for specialized bioinks.
- Production of bioinks optimized for hiPSC-derived neural aggregates.
- Utilizing Aspect Biosystems' RX1 printer and lab-on-a-printer (LOP) technology for 3D bioprinting.
Main Results:
- Successful development of methods for preparing and producing novel bioinks.
- Demonstration of 3D bioprinting of hiPSC-derived neural aggregates.
- Establishment of a workflow for creating 3D neural tissues from hiPSC aggregates.
Conclusions:
- This work presents a novel approach for 3D bioprinting of hiPSC-derived neural tissues.
- The developed methods and bioinks support cell survival and pave the way for mature neural tissue generation.
- This advancement holds significant potential for automating neural tissue engineering and regenerative medicine.

