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In silico Acute Myeloid Leukaemia

Pefani, E, Velliou, Eirini, Panoskaltsis, N, Mantalaris, A, Georgiadis, MC and Pistikopoulos, EN (2017) In silico Acute Myeloid Leukaemia In: Modelling Optimization and Control of Biomedical Systems. Wiley, pp. 265-300. ISBN 9781118965597

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Abstract

The most common treatment for most types of leukaemia is intensive chemotherapy given through the vein (intravenous [IV]). Mathematical modelling is a useful tool that can be used for the automation of chemotherapy treatment due to its advantages in systematically exploring extensive datasets in order to capture a system's dynamics and subsequently provide better insight for process enhancement. Treatment for acute myeloid leukaemia (AML) with chemotherapy may result in acute and long-term life-threatening complications due to drug toxicity. With the advent of novel treatments and large amounts of patient and leukaemia-specific genomic data, there is a clear need for a systematic approach to the design and execution of chemotherapy regimens. This chapter addresses these challenges in AML treatment by deriving a mathematical model that combines the leukaemia-specific actions on the cell cycle (i.e. drug target) with patient-specific pharmacology of the drugs (pharmacokinetics).

Item Type: Book Section
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
NameEmailORCID
Pefani, EUNSPECIFIEDUNSPECIFIED
Velliou, Eirinie.velliou@surrey.ac.ukUNSPECIFIED
Panoskaltsis, NUNSPECIFIEDUNSPECIFIED
Mantalaris, AUNSPECIFIEDUNSPECIFIED
Georgiadis, MCUNSPECIFIEDUNSPECIFIED
Pistikopoulos, ENUNSPECIFIEDUNSPECIFIED
Date : 29 December 2017
Identification Number : 10.1002/9781118965580.ch8
Copyright Disclaimer : © 2018 John Wiley & Sons Ltd
Uncontrolled Keywords : cancer chemotherapy; cell cycle; chemotherapy protocol; in silico acute myeloid leukaemia; pharmacodynamic mathematical model; pharmacokinetic mathematical model
Depositing User : Melanie Hughes
Date Deposited : 23 Nov 2017 14:41
Last Modified : 23 Nov 2017 14:41
URI: http://epubs.surrey.ac.uk/id/eprint/845024

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