Design of Treatments for Overcoming Drug Resistance in Glioblastoma Cultures with a Mathematical Model of Cellular Adaptation

Drug resistance is one of the main limiting factors for the success of existing cancer therapies and the development of new ones. In particular, for glioblastoma, the most aggressive brain cancer, more than half of the patients do not respond to the current chemotherapy treatment with temozolomide. In this work, we use a previously formulated and calibrated mathematical model, that takes into account the cellular adaptation leading to resistance, to in silico test alternative drug dosages that may improve the treatment outcome. Even if in silico tests have to be validated with in vitro and in vivo experiments, this work illustrates how computational models may help to design new treatment schedules.