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The three-dimensional (3D) structure of solid tumors inherently limits oxygen and nutrient diffusion to deeper cells, resulting in morphological and metabolic variations. Non-physiological levels of oxygen and nutrients within the tumors result in heterogeneous cell populations that exhibit distinct necrotic, hypoxic, and proliferative zones. Among these zonal cellular properties, metabolic rates strongly affect the overall growth and invasion of tumors. Here we report on a hybrid discrete-continuum (HDC) mathematical framework that uses data from a biomimetic three-dimensional (3D) in vitro cancer model to accurately predict cancer growth and treatment response. The mathematical model integrates the continuum field of variables with a discrete approach and incorporates the random walk method for individual cell migration. By tracking the moving boundary of tumoroids, the HDC model separates volumetric growth …