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Adv Healthc Mater. 2018 Jan;7(1). doi: 10.1002/adhm.201700605. Epub 2017 Oct 4.

Programmable Hydrogels for Cell Encapsulation and Neo-Tissue Growth to Enable Personalized Tissue Engineering.

Author information

1
Department of Chemical and Biological Engineering, University of Colorado, 3415 Colorado Ave, Boulder, CO, 80309-0596, USA.
2
Department of Mechanical Engineering, University of Colorado, 1111 Engineering Dr., Boulder, CO, 80309-0428, USA.

Abstract

Biomimetic and biodegradable synthetic hydrogels are emerging as a promising platform for cell encapsulation and tissue engineering. Notably, synthetic-based hydrogels offer highly programmable macroscopic properties (e.g., mechanical, swelling and transport properties) and degradation profiles through control over several tunable parameters (e.g., the initial network structure, degradation kinetics and behavior, and polymer properties). One component to success is the ability to maintain structural integrity as the hydrogel transitions to neo-tissue. This seamless transition is complicated by the fact that cellular activity is highly variable among donors. Thus, computational models provide an important tool in tissue engineering due to their unique ability to explore the coupled processes of hydrogel degradation and neo-tissue growth across multiple length scales. In addition, such models provide new opportunities to develop predictive computational tools to overcome the challenges with designing hydrogels for different donors. In this report, programmable properties of synthetic-based hydrogels and their relation to the hydrogel's structural properties and their evolution with degradation are reviewed. This is followed by recent progress on the development of computational models that describe hydrogel degradation with neo-tissue growth when cells are encapsulated in a hydrogel. Finally, the potential for predictive models to enable patient-specific hydrogel designs for personalized tissue engineering is discussed.

KEYWORDS:

ECM synthesis; computational models; degradation; hydrogels; personalized medicine

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