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Title: Mathematical modelling of both Chronic Lymphocytic Leukemia and Acute Myeloid Leukemia for their personalized treatment
Author: Savvopoulos, Symeon Vasileios
ISNI:       0000 0004 7658 9018
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2019
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This work is focused on developing models for two most common leukemia types which affect the different areas of haematopoiesis. These are the Chronic Lymphocytic Leukemia and the Acute Myeloid Leukemia. The first is a slow progressive disease which affects mostly the elderly and progresses in various tissues in the human body, whereas the second has an aggressive nature which progresses in the bone marrow. Our developed physiologically relevant models for both diseases are tested in hypothetical and semi-real patients with or without applied treatment and sensitivity analysis was performed for both. This kind of approach is still on the trial phase and is based mostly on data published in the literature. In Chronic Lymphocytic Leukemia, two different models were developed. These models approximate the growth and the metastasis of cells within the human body. The former contained time delay differential equations (TDDE) with empirical terms and the latter described the disease with population balance models (PBMs) which use data mostly measurable from experiments. The most critical parameters for both models were identified by sensitivity analysis. The standard treatment protocol in CLL was also applied in a semi-hypothetical patient. In Acute Myeloid Leukemia, the disease investigation was performed in different patients with multiclonal growth. In this model, the pharmacokinetics and the pharmacodynamics were directly connected because this disease is aggressive. Sensitivity analysis estimated the most important parameters under different treatment doses and protocols. Apart from the cancerous clonal growth, the neutrophil dynamic model was used in order to approximate the neutrophils in the peripheral blood in treated patients. This was seen to be affected by the growth of clones in the bone marrow. We suggest future efforts should be focussed on incorporating patient biological characteristics, like clonal evolution, clonal interactions and interactions between the clones and their microenvironment. The incorporation of the disease biological characteristics will validate our work, improve the model predictability and achieve efficient treatment protocols minimizing the life-threatening effects that chemotherapy has in patients. Last but not least, developing validated and flexible mathematical models for the most common leukemia types, can be used for drug development purposes that would allow promising and more effective therapies in the future than the standard treatment protocols used nowadays.
Supervisor: Mantalaris, Athanasios ; Panoskaltsis, Nicki Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral