258958 A Decision Tool for the Design of Optimal Personalised Chemotherapy Protocols for the Treatment of Acute Myeloid Leukaemia (AML)

Wednesday, October 31, 2012: 4:18 PM
Pennsylvania East (Westin )
Eleni Pefani, Chemical Engineering, Imperial College of London, London, United Kingdom, Nicki Panoskaltsis, Department of Haematology, Northwick Park Hospital, London, United Kingdom, Athanasios Mantalaris, Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College, London, United Kingdom, Michael C. Georgiadis, Centre for Process Systems Engineering, Chemical Engineering, Imperial College London, London, United Kingdom and Efstratios N. Pistikopoulos, Chemical Engineering, Imperial College London, Centre for Process Systems Engineering, London, United Kingdom

AML is an aggressive cancer of the blood and bone marrow resulting in failure of the blood and immune systems. Immature white blood cells which are not able to develop into normal functioning blood cells are overproduced and build up in the bone marrow and blood. This inhibits the development of healthy blood and immune cells due to space restrictions and inhibitory and clonal factors specific to the disease (Panoskaltsis, 2003; Panoskaltsis, 2005).

The most common treatment for AML is intensive chemotherapy requiring high doses of anticancer drugs to eradicate cancer cells. Although effective for debulking of the leukaemia tumor burden, the use of these chemotherapy regimens is also highly destructive to normal tissues and cells, often to a life-threatening extent.  Currently, the choice of chemotherapy drugs, dose and schedule only take few patient-specific factors into consideration and the choice of treatment often depends on the treating physician’s experience. However, a more systematic approach for the design of treatment protocols that will depend on specific inter-patient and intra-leukaemia factors is required. This systematic treatment design will lead to drug individualization and treatment dose optimisation so as to balance the benefits of higher dose therapy against the increase in toxicity in normal tissue. As presented in previous work (Dua et. al., 2005; Dua et. al., 2008; Pefani et. al. 2011), this can be achieved by modelling the key biological mechanisms as a means to gain insight into the chemotherapy procedure, which can then be used as a predictive tool for patient response during treatment.

In this work, a mathematical model is derived by combining the actions on the cell cycle, (drug target), with pharmacokinetic and pharmacodynamic aspects. This combination should provide a comprehensive description of drug diffusion and action after administration. The derived model depends on patient characteristics such as age, sex, body mass index and on disease characteristics such as tumor burden at the point of diagnosis and individual AML cell cycle characteristics.

Simulation and optimisation results are presented using the derived model for two patient case studies. The studied patients are of same sex, age and body mass index characteristics. However, their initial tumour burden and cell cycle times differ. They are both treated with the same treatment protocol in the model as they would be in clinical practise (a combination of cytarabine and daunorubicin). At completion of the first chemotherapy cycle one patient displays a bone marrow which contains a higher number of normal cells, whilst the other exhibits  a higher number of AML cells. An optimisation problem is formulated thereafter for the latter patient resulting in the normal cell population incrementing enough to allow for normal bone marrow tissue recovery prior to the next chemotherapy cycle to further decrease AML cells.

Model analysis results of these two patient case studies reveal the potential future applicability of the proposed tool and indicate the need for an interdisciplinary approach between clinicians, experimental- and model-based experts to collaborate in enabling personalised schedules for chemotherapy delivery in cancers such as AML.



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Pefani E., Panoskaltsis N., Mantalaris A., Georgiadis M. C., Pistikopoulos E. N.. Modelling and Simulation of Drug Delivery Systems for the treatment of Acute Myeloid Leukemia. Proceedings of the 5th European Conference of International Federation for Medical and Biological Engineering (IFMBE), Budapest, Hungary, 2011.


This work is supported by European Research Council (MOBILE, ERC Advanced Grant, No: 226462), The Richard Thomas Leukaemia Fund and the CPSE Industrial Consortium.

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