Hyndman, Lauren (2021) Mathematical modelling to guide experimental protocols for in vitro cell culture. PhD thesis, University of Glasgow.
Full text available as:
PDF
Download (14MB) |
Abstract
The development of a single drug from discovery to approval is a long and expensive process. Often, many potential drugs that appear promising in preclinical studies are subsequently eliminated during human clinical trials. In recent years, there has been a move away from animal testing in favour of cell-based in vitro methods, so to improve the correlation between the outcome of preclinical studies and clinical trials, and therefore to increase the efficiency of the drug development process, it is essential that in vitro tests provide physiologically relevant results. There have been great advances in the development of in vitro cell culture techniques, from the traditional static monolayer to the advent of flow-based bioreactor devices, and a common approach is to combine conventional cell culture methods with sophisticated systems that expose cells to conditions that are more representative of their native environment. One of the drawbacks associated with the advancement of in vitro techniques is that there is a lack of knowledge and understanding of the physical and chemical environment generated within complex cell culture systems. To overcome this obstacle, mathematical models can be employed to characterise the conditions to which cells are exposed within novel in vitro devices. Mathematical analysis can offer insight to aid in the effective tailoring of operating parameters and interpretation of experimental results, as well as providing estimations of quantities that can be difficult or impossible to obtain experimentally.
The aim of this thesis is to use mathematical models to describe the environment within static and dynamic in vitro cell culture systems, with the aim of highlighting the relationships between key model parameters and, ultimately, guiding the design and set-up of experiments. Mathematical models of varying complexity are developed, ranging from 1D diffusion-reaction partial differential equations to coupled 3D models of fluid flow and solute transport. A variety of mathematical techniques are employed to solve each model: in Chapter 2, analytical approaches are used to derive approximations to the numerical solutions, and the models in Chapter 3 are solved using the finite element method, implemented via commercially available software. In each chapter, simple expressions are derived from the governing equations to provide information on how to adjust experimentally controllable operating parameters such that the desired cell culture conditions can be achieved. In Chapter 4, the main goal of the thesis is realised by applying the models developed in Chapter 3 to help determine the optimal configuration of a commercially available bioreactor device for two different applications.
Item Type: | Thesis (PhD) |
---|---|
Qualification Level: | Doctoral |
Subjects: | Q Science > QA Mathematics T Technology > T Technology (General) |
Colleges/Schools: | College of Science and Engineering > School of Engineering > James Watt Nanofabrication Centre |
Supervisor's Name: | Mcginty, Dr. Sean |
Date of Award: | 2021 |
Depositing User: | Theses Team |
Unique ID: | glathesis:2021-82510 |
Copyright: | Copyright of this thesis is held by the author. |
Date Deposited: | 18 Oct 2021 15:30 |
Last Modified: | 26 Oct 2021 14:37 |
Thesis DOI: | 10.5525/gla.thesis.82510 |
URI: | https://theses.gla.ac.uk/id/eprint/82510 |
Related URLs: |
Actions (login required)
View Item |
Downloads
Downloads per month over past year