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Optimal Cancer Treatment Using Radiovirotherapy

Ricardo Dunia, LabVIEW R&D, National Instruments, 11500 N. Mopac Expwy, Austin, TX 78759 and Thomas Edison, Chemical Engineering, University of Texas in Austin, 1 University Station C0400, Austin, TX 78712.

Protein engineering has enabled the production of viruses that infect tumor cells [1]. Models of tumor and virus interactions have been recently developed and validated [2][3]. This new and effective cancer therapy has been modeled at the cell level by three state variables, which include the population of free virus particles controlled by the virotherapy dosage. A three dimensional simulations of a solid tumor at the macroscopic level has shown that the tumor eradication requires widespread distribution within the tumor at the time of infection [3]. It has been suggested that virotherapy alone may failed to eliminate a tumor in cases where the tumor vascular irrigation is not homogenously widespread [4]. The use of radiovirotherapy has been also modeled at the macroscopic level and relevant therapeutic scenarios have been proposed for its optimal treatment. This research work develops an efficient control strategy to eliminate a localized tumor subject to the maximum free virus concentrations and radiotherapy frequency attainable by the human body. The controller adapts to the different stages of the therapy by reducing the dosage as the tumor reduces its size. Although the core therapy model is developed at the cellular level, the feedback information provided to the nonlinear controller is at a macroscopic level, making the implementation of the closed loop therapy feasible to real applications.

[1] Antibody Targeted Cell Fusion ; Nakamura, T., Peng, K. W., Vongpunsawad, S., Harvey, M., Mizuguchi, H., Hayakawa, T., Cattaneo, R., Russel, S., 2004. Nat. Biotechnology. 22 (3) 331-336.

[2] Modeling of cancer virotherapy with recombinant measles viruses ; Zeljko Bajzer, Thomas Carr, Kresimir Josic, Stephen J. Russel David Dingli, 2008, Journal of Theoretical Biology, 252, 109-122.

[3]Validation and Analysis of a Mathematical Model of a Replication-competent Oncolytic Virus for Cancer Treatment: Implication for Virus Design and Delivery; L.M. Wein, J. Wu and D. Kirn, 2003, Cancer Research, 63, 1317-1324.

[4] Mathematical Modeling of Cancer Radiovirotherapy; D. Dingli, M. Cascino, K. Josic, S. Russell, Z. Bajzer, 2006, Mathematical Biosciences, 199, 55-78.