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Multiscale Modelling and Analysis of Tumour Growth and Treatment Strategies
Author(s) -
Sara Hamis
Publication year - 2021
Language(s) - English
Resource type - Dissertations/theses
DOI - 10.23889/suthesis.56917
Subject(s) - prodrug , radiation therapy , in silico , hypoxia (environmental) , cancer treatment , computer science , computational biology , cancer , medicine , chemistry , biology , pharmacology , oxygen , biochemistry , organic chemistry , gene
A multiscale, agent-based mathematical framework is here used to capture the multiscale nature of solid tumours. Tumour dynamics and treatment responses are modelled and simulated in silico. Details regarding cell cy-cle progression, tumour growth and oxygen distribution are included in the mathematical framework. Treatment responses to conventional anti-cancer therapies, such as chemotherapy and radiotherapy, as well as to more novel drugs, such as hypoxia-activated prodrugs and DNA-damage repair inhibit-ing drugs, are studied. Uncertainty and sensitivity analyses techniques are discussed in order to mitigate model uncertainty and interpret model sen-sitivity to parameter perturbations. This thesis furthermore discusses the role of mathematical modelling in current cancer research.

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