The overarching goal of the Tumor Modeling Group is to develop predictive mathematical and computational models for tumor initiation, growth and decline in response to treatment modalities. Using a theoretical framework based on biological and physical principles, the Hallmarks of cancer and empirical data, we integrate a variety of components of predictive science that enables to deal with model selection, calibration, and validation in the presence of uncertainty. We develop hybrid model classes, and numerical methods that are employed to depict events at molecular, cellular, and tissue levels. Our central hypothesis is that the new methodologies as those developed by the team may provide a valuable approach to cancer therapies, contributing to significantly reduce fatalities.
The research is tailored by interdisciplinairy efforts on different skills, including essencial knowledge of applied mathematics, numerical and computational methods and equally the complementary expertise of theoretical cancer Biology.