Date of Award

3-2022

Degree Name

MS in Biomedical Engineering

Department/Program

Biomedical Engineering

College

College of Engineering

Advisor

Trevor Cardinal

Advisor Department

Biomedical Engineering

Advisor College

College of Engineering

Abstract

There is a need for a minimally invasive delivery method to enable cell therapies to combat peripheral artery occlusive disease (PAOD) in end stage patients. Myoblasts show promise as a cell mediated therapy but warrant an improved delivery method to increase cell retention in the region of interest because of their adherent nature, relative to previously used BM-MNC’s that are non-adherent. Contemporary issues with achieving successful cell therapies of vasculature can be mainly characterized by the lack of clinical translation from promising animal studies and absence of cell delivery scaffolding. Naturally, polymers have been widely experimented with as grafts to both culture and implant cells into tissue with recognizable success due to their analogous physical properties, such as stiffness, hydrophilicity, & surface energy, that mimic tissue conditions. Polymers having similar mechanical properties to anatomical structures are conducive to cell integration & retention, making polymers an effective biomaterial choice as a cell delivery vehicle. This thesis will evaluate the application of N-isopropylacrylamide (NIPAM) based copolymers as a biomaterial scaffold for myoblast delivery, as it is one of the most widely used biocompatible polymers with thermoreversible properties that is non-toxic and has manipulatable mechanical properties. We hypothesized that fluctuations in polymer construct stiffness, surface energy, and water retention affect myoblast proliferation & viability within the cell delivery vehicle. After measuring the physical properties and cellular proliferation in for each polymer composition, the goal of this thesis was to establish a statistical model to characterize the effect of polymer material properties on myoblast behavior and create a predictive model to optimize further iterations of NIPAM-based copolymers for cell delivery.

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