Designing Effective Trials Regarding Treatments against Cancerous TUMOR Growth

Monday, November 9, 2009: 12:30 PM
Canal C (Gaylord Opryland Hotel)

Ileana C. Carpen, Department of Chemical Engineering, Tennessee Tech University, Cookeville, TN
Nemoy Rau, Department of Chemical Engineering, Tennessee Tech University, Cookeville, TN

Cellular adaptation to changing environments is intricately coordinated through many molecular and mechanical responses. As cells evolve, abnormal growth patterns occur (that cannot be controlled by normal mechanisms) leading to cancer. With mathematical modeling we can integrate different characteristics of tumor growth for a non-experimental study of cancer.1 Through integration of some of the prior clinical, experimental, and mathematical studies, we utilize a cellular automata model to take into account multiple factors affecting tumor growth in healthy tissue.2 This in silico simulation model of tumor growth is based upon molecular and life cycle features that effect the growth rates of cancer. The life cycle parameters used in this model include replication rate, nutrient concentrations for proliferation and survival, and possible drug effects.3 This 3-D in silico model is used to study the effects of drugs upon the growth and development of the tumor and optimize a drug treatment protocol under various conditions.

References

1. Quaranta V, Cummings P, Anderson A. (2005). “Mathematical modeling of cancer: The future prognosis and treatment.” Clinical Chimica Acta 357,173-179.

2. An-Shen Q, Xiang Z, Chan Y, Bao-Sheng A. (1993). “A Cellular Automaton Model of Cancerous Growth.” J. Theor. Biol. 161, 1-12.

3. S.C. Ferreira, Jr., M.L. Martins, M.J. Vilela (2002). "Reaction-diffusion model for the growth of avascular tumor." Phys. Rev. E65, 021907.

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See more of this Session: In Silico Systems Biology: Cellular and Organismal Models
See more of this Group/Topical: Topical A: Systems Biology