In this talk, we describe various methodologies designed to study the growth of low grade gliomas (brain tumors) and to take into account chemotherapy and radiotherapy. They have in common the use of mixed effects models and SAEM algorithm (Stochastic Approximation Expectation Maximization) for the estimation of the parameters of the model. Presented works are based on (i) ordinary differential equations and (ii) on partial differential equations (spatial aspects are taken into account, not only temporal ones). These works were done in collaboration with Emmanuel Grenier, Violaine Louvet and Benjamin Ribba. (i) Ribba et al. A tumor growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy. Clin Cancer Res. 2012 Sep 15;18(18):5071-80 (ii) Grenier, V. Louvet, P. Vigneaux. Parameter estimation in non-linear mixed effects models with SAEM algorithm: extension from ODE to PDE. INRIA Research Report no 8231. February 2013