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Insight into the Design of Aerosol Spray Systems for Cell Therapies for Retinal Diseases using Computational Modelling and Experimental Assessment

Nweze, Miriam; (2020) Insight into the Design of Aerosol Spray Systems for Cell Therapies for Retinal Diseases using Computational Modelling and Experimental Assessment. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

Retinal degenerative diseases affect numerous people worldwide and in the UK; they lead to dysfunction of retinal cells and retinal dysfunction, in turn leading to vision loss and in some cases blindness. Existing treatments aim to alleviate current risk factors leading to retinal degeneration, such as increased high pressure. However, these procedures do not restore lost cell, vision nor retinal function, and therefore may still lead to blindness. Developing cell-based therapies to replace lost cells provides one option for retinal tissue repair in order to restore retinal function. These therapies involve delivering stem cells to encourage neural cell-like functions within the retinal tissue. Despite progress in developing stem-cells compatible with the retinal layers, there is also a need to developing a minimal invasive technique for cell delivery, without damaging the neighbouring optical structure. After evaluating several methods of cell delivery, this thesis explores the need for developing aerosol spraying systems for stem-cell delivery into the human eye. Mathematical modelling is used as a tool to define spraying parameters which, alongside experimental work, may accelerate the design of aerosol spraying systems to treat retinal degenerative disease such as glaucoma. Firstly, an organic biomaterial is developed and used as scaffold to spray and protect cells from aerodynamic forces and stresses associated with aerosolization. The rheological properties of this biomaterial are incorporated within a computational model to predict cell-spraying into a human eye. Boundary and initial conditions mimic the experimental spraying conditions, and the parameterised model is used to explore the link between operator-defined conditions (namely volume flow rate of the cell-laden hydrogel, external pressure needed for aerosolization and angle of the spraying) and spraying outputs (surface area of the retina covered, droplets speed, wall shear stress on the retinal surface). Data from both computational and experimental analyses were gathered. Computational modelling is used to explore the impact of spraying parameters (pressure and volume flow rate at the injector nozzle, outer cone angle for the spray) on key outputs of high priority, namely the spatial distribution of the delivered hydrogel on the retinal wall, the surface area of the retina covered and droplet speed. Droplets speed at the retinal wall appeared to increase with increasing pressure conditions and were observed at a constant volume flow rate. Experimental assessments were used to validate the computational data and determine cell viability under set environmental conditions (external pressure and volume flow rate of cell-laden hydrogel) through in-vitro testing. This thesis defines indicative spraying parameters for delivering therapeutic cells to the human retina, based on a combination of computational modelling and experimental studies. Mathematical modelling provides the potential to transfer these findings to other organ systems, aligning with broader effects to develop cell delivery systems to treat organ disease and repair.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Insight into the Design of Aerosol Spray Systems for Cell Therapies for Retinal Diseases using Computational Modelling and Experimental Assessment
Event: UCL
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2020. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Engineering Science Faculty Office
URI: https://discovery.ucl.ac.uk/id/eprint/10093741
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