In order to understand in more detail the dynamics of complex biological systems, we also develop novel approaches and tools for modelling biological system. In the last decades, knowledge of molecular aspects of human physiology and pathophysiology has grown enormously. Often, this knowledge is qualitative. Since cellular signalling pathways are embedded in a complex dynamic system and interact with many other pathways, it is difficult to gain quantitative information which can be used to model cellular systems or organisms. Observing dynamic patterns in silico and comparing them to experimental data in vitro or in vivo could help us identify and quantify dynamic processes. Since modellers are faced with a high degree of complexity of biological systems and often encounter experimental difficulties (for example when determining kinetic constants), appropriate concepts of system descriptions are needed. The use of dynamic state variables is expected to make models applicable to a wider range of the dynamics of biological systems. This is demonstrated by the Multi-Hit-Repair (MHR-) model which is based on a transient dose equivalent. The model calculates the survival of cells irradiated by ionizing radiation and it describes correctly a large variety of radio-biological observations. In addition, the MHR-model is bridging the gap between processes at the molecular or cellular level and tissue dynamics. Actual research focus on the modelling of the synergistic effect of radiation therapy combined with hyperthermia.

 

The methodology derived by the running projects has a high potential for model based data analysis in a broader range of applications in medicine.

 

 

Main page

 

 

References:

 

Scheidegger S, Fuchs HU, Füchslin RM (2014): Computational Methods for Exploring the Dynamics of Cancer: The Potential of State Variables for Description of Complex Biological Systems. Proc. NOLTA 2014, 168-171.

 

Scheidegger S, Fuchs HU, Zaugg K, Bodis S, Füchslin RM (2013): Using State Variables to Model the Response of Tumour Cells to Radiation and Heat: A Novel Multi-Hit-Repair (MHR-) Approach. Computational and Mathematical Methods in Medicine, 2013, http://dx.doi.org/10.1155/2013/587543

 

Scheidegger S., Füchslin R.M., Lutters G., Bodis S.(2012): Dynamic modelling of the synergistic effect of hyperthermia and radiotherapy. Radiother. Oncol. 103, Suppl.1, S360-361.

 

Scheidegger S., Füchslin R.M. (2011): Kinetic model for dose equivalent – an efficient way to predict systems response of irradiated cells. Proc. of ASIM 2011 (full papers, ISBN 978-3-905745-44-3)

 

Scheidegger S., Lutters G., Bodis S. (2011): A LQ-based kinetic model formulation for exploring dynamics of treatment response of tumours in patients. Z. Med. Phys. 21,164–173

 

Lohse I., Lang, S., Hrbacek J., Scheidegger S., Bodis S., Sanchez-Macedo N., Feng J., Lütolf U.M., Zaugg K. (2011): Effect of high dose per pulse flattening filter – free beams on cancer cell survival. Radiother. Oncol. 101, 226-232

 

Füchslin RM, Dumont E, Flumini D, Fuchs HU, Hauser H, Jaeger C, Scheidegger S, Schönenberger-Deuel J, Lichtensteiger J, Luchsinger R, Weyland Mathias (2014): Morphological control: a design principle for applications in space science. JBIS 67, 305-313

 

Füchslin RM, Dzyakanchuk A, Flumini D, Hauser H, Hunt KJ, Luchsinger RH, Reller B, Scheidegger S, Walker R (2013): Morphological computation and morphological control: Steps toward a formal theory and applications. Artificial Life 19, 9-34

 

Spaeth, N., Wyss, M. T., Weber, B., Scheidegger, S., Lutz, A., Verwey, J., Radovanovic, I., Pahnke, J., Wild, D., Westera, G., Weishaupt, D., Hermann, D. M., Kaser-Hotz, B., Aguzzi, A., Buck A. (2004): Uptake of 18F-Fluorocholin, 18F-Fluoroethyl-L-Tyrosine, and 18F-FDG in Acute Celebral Radiation Injury in the Rat: Implications for Separation of the Radiation Necrosis from Tumor Recurrence. J. Nucl. Med., 45, 1931-1938

 

Scheidegger S, Grosse N, Füchslin R (2014): Homologous Recombination in the View of the MHR-Model. Proc. of Joint Conference of SSRMP, DGMP and ÖGMP 2014 (ISBN 987-3-9816508-5-3), 194-195

 

Scheidegger S, Marder D, Timm O, Bonmarin M, Rhodes S (2014): Measuring skin perfusion after superficial hyperthermia using IR-cam technology. SSBE Annual Meeting 2014, 20

 

Scheidegger S, Bonmarin M, Timm O, Rhodes S, Datta NR (2014): Estimating radio-sensitisation based on re-oxygenation after hyperthermia by using dynamic models. Panminerva Medica 56, suppl. 1 (2), 24

 

Scheidegger S, Rohrer-Bley C, Bodis S (2013): Impact of variation of cellular repair, fractionation and timing on synergistic effect of radiotherapy and hyperthermia. Strahlenther Onkol 12, 1067

 

Scheidegger S, Lomax N, Timm O, Datta N, Füchslin RM, Bodis S (2013):Characterisation of hyperthermia in combination with radiotherapy: temporal homogeneity and limitations of the CEM-concept. . Proc. of 28th Annual Meeting of the European Society for Hyperthermic Oncology 2013, P131

 

Datta NR, Uric E, Lomax N, Scheidegger S, Marder D, Bodis S (2013): Time-Temperature Areau Under Curve (AUC): A proposal for  a novel thermometric parameter for clinical hyperthermia in bladder cancer. Proc. of 28th Annual Meeting of the European Society for Hyperthermic Oncology 2013, P122

 

Scheidegger S, Füchslin, RM, Lutters G, Bodis S (2012): The dynamic view to hyperthermia – a comparison of the CEM43° concept. Strahlenther. Onkol. 188(8), 738

 

Lohse I., Lang S., Scheidegger S., Sanchez-Macedo N., Hrbacek J., Bodis S., Lütolf U.M., Zaugg K. (2011): Dose-rate effect of novel radiation technologies: relevance for the clinical use and radiobiological models. Molecular Radiation Biology / Oncology, 9/2011, 48.

 

Scheidegger S., Zaugg K., Bodis S. (2011): Induced repair as an unique approach to model apoptotic and non-apoptotic cell survival. Strahlenther. Onkol. 187, 520

 

Füchslin R.M., Luchsinger R.H., Reller B., Hauser H., Scheidegger S. (2011): Morphological computation: applications on different scales exploiting classical and statistical mechanics. Proc. of  ICMC 2011,  41 - 43

 

 

Scheidegger S. (2010): A theoretical framework to explore low dose hypersensitivity. Proc. of SSRMP Annual Scientific Meeting 2010, ISBN 3 908 125 52 9, 57-59

 

Scheidegger, S., Lutters, G. (2010): A novel biophysical model describing repair modifications and growth inhibition of irradiated cells. Bulletin SPG SSP, 27, 41.

 

Scheidegger, S., Lutters, G., Bodis, S. (2010): Computer simulation of oxygenation and growth inhibition of tumours during fractionated radiotherapy: Exploration of the dynamic system behaviour. Radiother. Oncol. 95, Suppl.1, 512.

 

Scheidegger S., Lutters G., Bodis S. (2010): A kinetic LQ – based model for exploring the tumor response onto radiation including the vascular system. Strahlenther. Onkol. 186, 731

 

Scheidegger, S., Lutters, G., Bodis, S. (2009): A novel approach for biomathematical modelling to predict treatment response for combined radiotherapy modalities in patients. Molecular Radiation Biology / Oncology, 8 (2009), 72

 

Scheidegger, S., Lutters, G., Bodis, S. (2009): Understanding tumour dynamics in vivo: The potential of kinetic models in radio-oncology. Proc. of SSRMP Annual Scientific Meeting 2009, 18-23.