Clinically driven design of multi-scale cancer models: the ContraCancrum project paradigm
- Marias, K. Institute of Computer Science at FORTH, Heraklion, Greece
- Dionysiou, D. In Silico Oncology Group, Institute of Communications and Computer Systems, National Technical University of Athens, Athens, Greece
- Sakkalis, V. Institute of Computer Science at FORTH, Heraklion, Greece
- Graf, N. Departments of Paediatric Oncology and Haematology, Pathology, Genetics, Universität des Saarlandes, Homburg, Germany
- Bohle, R. M. Departments of Paediatric Oncology and Haematology, Pathology, Genetics, Universität des Saarlandes, Homburg, Germany
- Coveney, P. V. Centre for Computational Science, Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
- Wan, S. Centre for Computational Science, Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
- Folarin, A. Cancer Research Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK
- Büchler, P. Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
- Reyes, M. Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
- Clapworthy, G. Department of Computer Science & Technology, University of Bedfordshire, Luton, UK
- Liu, E. Department of Computer Science & Technology, University of Bedfordshire, Luton, UK
- Sabczynski, J. Philips Technologie GmbH, Innovative Technologies, Hamburg, Germany
- Bily, T. Faculty of Mathematics and Physics, Department of Applied Mathematics, Charles University in Prague, Prague, Czech Republic
- Roniotis, A. Institute of Computer Science at FORTH, Heraklion, Greece
- Tsiknakis, M. Institute of Computer Science at FORTH, Heraklion, Greece
- Kolokotroni, E. In Silico Oncology Group, Institute of Communications and Computer Systems, National Technical University of Athens, Athens, Greece
- Giatili, S. In Silico Oncology Group, Institute of Communications and Computer Systems, National Technical University of Athens, Athens, Greece
- Veith, C. Departments of Paediatric Oncology and Haematology, Pathology, Genetics, Universität des Saarlandes, Homburg, Germany
- Messe, E. Departments of Paediatric Oncology and Haematology, Pathology, Genetics, Universität des Saarlandes, Homburg, Germany
- Stenzhorn, H. Departments of Paediatric Oncology and Haematology, Pathology, Genetics, Universität des Saarlandes, Homburg, Germany
- Kim, Yoo-Jin Departments of Paediatric Oncology and Haematology, Pathology, Genetics, Universität des Saarlandes, Homburg, Germany
- Zasada, S. Centre for Computational Science, Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
- Haidar, A. N. Centre for Computational Science, Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
- May, C. Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
- Bauer, S. Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
- Wang, T. Department of Computer Science & Technology, University of Bedfordshire, Luton, UK
- Zhao, Y. Department of Computer Science & Technology, University of Bedfordshire, Luton, UK
- Karasek, M. Faculty of Mathematics and Physics, Department of Applied Mathematics, Charles University in Prague, Prague, Czech Republic
- Grewer, R. Philips Technologie GmbH, Innovative Technologies, Hamburg, Germany
- Franz, A. Philips Technologie GmbH, Innovative Technologies, Hamburg, Germany
- Stamatakos, G. In Silico Oncology Group, Institute of Communications and Computer Systems, National Technical University of Athens, Athens, Greece
- 2011-3-30
Published in:
- Interface Focus. - The Royal Society. - 2011, vol. 1, no. 3, p. 450-461
English
The challenge of modelling cancer presents a major opportunity to improve our ability to reduce mortality from malignant neoplasms, improve treatments and meet the demands associated with the individualization of care needs. This is the central motivation behind the ContraCancrum project. By developing integrated multi-scale cancer models, ContraCancrum is expected to contribute to the advancement of
in silico
oncology through the optimization of cancer treatment in the patient-individualized context by simulating the response to various therapeutic regimens. The aim of the present paper is to describe a novel paradigm for designing clinically driven multi-scale cancer modelling by bringing together basic science and information technology modules. In addition, the integration of the multi-scale tumour modelling components has led to novel concepts of personalized clinical decision support in the context of predictive oncology, as is also discussed in the paper. Since clinical adaptation is an inelastic prerequisite, a long-term clinical adaptation procedure of the models has been initiated for two tumour types, namely non-small cell lung cancer and glioblastoma multiforme; its current status is briefly summarized.
The challenge of modelling cancer presents a major opportunity to improve our ability to reduce mortality from malignant neoplasms, improve treatments and meet the demands associated with the individualization of care needs. This is the central motivation behind the ContraCancrum project. By developing integrated multi-scale cancer models, ContraCancrum is expected to contribute to the advancement of
oncology through the optimization of cancer treatment in the patient-individualized context by simulating the response to various therapeutic regimens. The aim of the present paper is to describe a novel paradigm for designing clinically driven multi-scale cancer modelling by bringing together basic science and information technology modules. In addition, the integration of the multi-scale tumour modelling components has led to novel concepts of personalized clinical decision support in the context of predictive oncology, as is also discussed in the paper. Since clinical adaptation is an inelastic prerequisite, a long-term clinical adaptation procedure of the models has been initiated for two tumour types, namely non-small cell lung cancer and glioblastoma multiforme; its current status is briefly summarized.
- Language
-
- English
- Open access status
- bronze
- Identifiers
-
- DOI 10.1098/rsfs.2010.0037
- ISSN 2042-8898
- Persistent URL
- https://folia.unifr.ch/global/documents/60209
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