
Mathematical modeling techniques have been widely employed to understand how cancer grows, and, more recently, such approaches have been used to understand how cancer can be controlled. In this manuscript, a previously validated hybrid cellular automaton model of tumor growth in a vascularized environment is used to study the antitumor activity of several vascular‐targeting compounds of known efficacy. In particular, this model is used to test the antitumor activity of a clinically used angiogenesis inhibitor (both in isolation, and with a cytotoxic chemotherapeutic) and a vascular disrupting agent currently undergoing clinical trial testing. I demonstrate that the mathematical model can make predictions in agreement with preclinical/clinical data and can also be used to gain more insight into these treatment protocols. The results presented herein suggest that vascular‐targeting agents, as currently administered, cannot lead to cancer eradication, although a highly efficacious agent may lead to long‐term cancer control.
Angiogenesis Inhibitors, Antineoplastic Agents, Antibodies, Monoclonal, Humanized, Models, Biological, Medical applications (general), Neoplasms, Antineoplastic Combined Chemotherapy Protocols, Stilbenes, Temozolomide, Animals, Humans, Computer Simulation, Computational methods for problems pertaining to biology, Antineoplastic Agents, Alkylating, Cytotoxins, Antibodies, Monoclonal, Antineoplastic Agents, Phytogenic, Bevacizumab, Dacarbazine, Blood Vessels, Glioblastoma, Algorithms, Research Article
Angiogenesis Inhibitors, Antineoplastic Agents, Antibodies, Monoclonal, Humanized, Models, Biological, Medical applications (general), Neoplasms, Antineoplastic Combined Chemotherapy Protocols, Stilbenes, Temozolomide, Animals, Humans, Computer Simulation, Computational methods for problems pertaining to biology, Antineoplastic Agents, Alkylating, Cytotoxins, Antibodies, Monoclonal, Antineoplastic Agents, Phytogenic, Bevacizumab, Dacarbazine, Blood Vessels, Glioblastoma, Algorithms, Research Article
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