Mathematical modeling of cancer radiovirotherapy
| Autor: | David Dingli, Krešimir Josić, Željko Bajzer, Matthew D. Cascino, Stephen J. Russell |
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| Rok vydání: | 2006 |
| Předmět: |
Statistics and Probability
Mathematical optimization Population Tumor cells Biology Bioinformatics Models Biological Outcome (game theory) General Biochemistry Genetics and Molecular Biology Iodine Radioisotopes Mice Neoplasms medicine Animals Humans Combined Modality Therapy Computer Simulation Least-Squares Analysis Virotherapy education Oncolytic Virotherapy education.field_of_study Symporters General Immunology and Microbiology Extramural Applied Mathematics Cancer Neoplasms therapy General Medicine medicine.disease Xenograft Model Antitumor Assays Measles virus Modeling and Simulation Multiple Myeloma General Agricultural and Biological Sciences Algorithms |
| Zdroj: | Mathematical Biosciences. 199:55-78 |
| ISSN: | 0025-5564 |
| DOI: | 10.1016/j.mbs.2005.11.001 |
| Popis: | Cancer virotherapy represents a dynamical system that requires mathematical modeling for complete understanding of the outcomes. The combination of virotherapy with radiation (radiovirotherapy) has been recently shown to successfully eliminate tumors when virotherapy alone failed. However, it introduces a new level of complexity. We have developed a mathematical model, based on population dynamics, that captures the essential elements of radiovirotherapy. The existence of corresponding equilibrium points related to complete cure, partial cure, and therapy failure is proved and discussed. The parameters of the model were estimated by fitting to experimental data. By using simulations we analyzed the influence of parameters that describe the interaction between virus and tumor cell on the outcome of the therapy. Furthermore, we evaluated relevant therapeutic scenarios for radiovirotherapy, and offered elements for optimization. |
| Databáze: | OpenAIRE |
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