Malignant gliomas, particularly glioblastoma, are among the most aggressive brain tumors and remain associated with a poor prognosis despite decades of research. The Stupp protocol has long been the standard first-line treatment for these tumors. However, survival benefits remain modest, highlighting the need for improved therapeutic strategies.

To address this challenge, MOLAB researchers developed a mathematical framework capable of simulating tumor response to chemoradiotherapy and testing alternative treatment schedules through virtual clinical trials.

The model was calibrated and validated using experimental data from mouse models treated with radiotherapy and temozolomide. It incorporates key biological mechanisms involved in treatment response, including cellular dormancy, phenotypic transitions, and therapy resistance.

Using digital twins, a wide range of treatment schedules were explored and several protracted regimens that could outperform the current standard-of-care protocol were identified. The results suggest that less intensive but more strategically timed therapies may improve outcomes while delaying the emergence of resistance. After scaling the model from mice to humans, the virtual trials predicted substantial improvements in median overall survival for the optimized schedules compared with the standard regimen.

The study was conducted by researchers from MOLAB in collaboration with colleagues from the Neurooncology Unit of UFIEC (ISCIII) and has been published in Applied Mathematical Modelling.

The full article is available at: https://doi.org/10.1016/j.apm.2026.117093