Dynamics of multi-modal anti-angiogenic, anti-vascular, and cytotoxic therapies: Potential for significant clinical impact

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The application of physics and mathematics to medicine is one of the most rapidly growing areas of interdisciplinary research. Mathematical modeling can provide a quantitative framework to discuss, in detail, the interaction between all components of complex biological systems, as well as to test various therapeutic interventions. The combination of novel computational techniques and mathematical models, grounded in experimental and clinical data, thus provides a powerful new tool in biomedical research. The identification of major factors that influence treatment response in cancerous tumors has been a problem of long-standing interest and relevance to clinical oncology. While conventional cytotoxic treatments like radiotherapy and chemotherapy have contributed to major advancement in cancer control, there remains significant room for further improvement in many tumor sites. Novel molecularly-targeted treatments, like inhibitors of tumor angiogenesis (the formation of blood vessels from pre-existing vessels), have the potential to complement conventional treatments. There is currently minimal pre-clinical or clinical evidence on which to base decisions about how to optimally combine anti-angiogenic and cytotoxic therapies. Our working hypothesis is that mathematical modeling based on existing and novel biophysical models of the interactions between the vascular, interstitial and cellular compartments of a tumor, and the impact on these interactions on nutrient delivery to cancer cells, can guide the rationale sequencing of anti-angiogenic therapies with existing cytotoxic treatments. The project will revolve around a dynamic process of mathematical model development and refinement, using data derived from histologic and imaging studies in animals, and patient data from ongoing clinical studies in patients with cervix cancer and other tumors.