Tumor growth is a complex process influenced by various mechanical and biochemical factors. Understanding the interplay between these factors is crucial for developing effective treatment strategies [1]. Within this context physics-based mathematical models have nowadays a pivotal role to better understand the physics at play and its coupling with biology, to predict the evolution of the disease and the response to treatments. This contribution presents a mathematical framework founded on mechanics of reactive and deformable porous media, offering a comprehensive approach to simulate and analyze the behavior of a tumor. The poromechanical approach considers the porous nature of biological tissues. The tumor is modeled as a multiphase material consisting of a solid phase, the extracellular matrix, an interstitial fluid phase, a tumor cell phase and all the other needed constituents for a realistic representation of the cancer-specific tumor microenvironment. The model is based on a coupled set of partial differential equations describing mass and momentum conservation of phases (and species) and including mass exchange and reaction terms to model cell proliferation, migration, and interactions. The final set of equations incorporates key parameters such as tissue permeability and other mechanical properties, providing a sound understanding of how these factors influence the behavior of the tumor. After a general presentation of the mathematical model and its rationale two application cases are presented. The first is an in vitro-in silico study focusing on growth of tumor spheroids confined within alginate porous capsules mimicking the in vivo physiological confinement [2]. The second application is the numerical simulation of glioblastoma growth based on a non-operable clinical case [3]. The results demonstrate the model’s ability to capture the spatial and temporal evolution of tumor growth in controllable conditions (in vitro case) while improvements are still needed at the organ level. Furthermore, sensitivity analyses reveal the impact of various parameters on tumor behavior, offering insights into potential therapeutic targets.