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A Hybrid Multiscale Approach in Cancer Modelling and Treatment Prediction

  • Gibin Powathil
  • Mark A. J. ChaplainEmail author
Chapter
Part of the Modeling and Simulation in Science, Engineering and Technology book series (MSSET)

Abstract

Cancer is a complex multiscale disease involving inter-related processes across a wide range of temporal and spatial scales. Multiscale mathematical models can help in studying cancer progression and serve as an in silico test base for comparing and optimizing various multi-modality anticancer treatment protocols. Here, we discuss one such hybrid multiscale approach, interlinking individual cell behavior with the macroscopic tissue scale. Using this technique, we study the spatio-temporal dynamics of individual cells and their interactions with the tumor microenvironment. At the intracellular level, the internal cell-cycle mechanism is modelled using a system of coupled ordinary differential equations, which determine cellular growth dynamics for each individual cell. The evolution of these individual cancer cells are modelled using a cellular automaton approach. Moreover, we have also incorporated the effects of oxygen distribution into this multiscale model as it has been shown to affect the internal cell-cycle dynamics of the cancer cells. The hybrid multiscale model is then used to study the effects of cell-cycle-specific chemotherapeutic drugs, alone and in combination with radiotherapy, with a long-term goal of predicting an optimal multimodality treatment plan for individual patients.

Keywords

Cancer Hybrid multiscale model Cell cycle Hypoxia Chemotherapy Radiotherapy 

Notes

Acknowledgements

The authors gratefully acknowledge the support of the ERC Advanced Investigator Grant 227619, M5CGS - From Mutations to Metastases: Multiscale Mathematical Modelling of Cancer Growth and Spread.

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© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Division of MathematicsUniversity of DundeeDundeeUK

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