This research presents a comprehensive mathematical model capturing the spatiotemporal dynamics of tumor growth within biological systems, incorporating cell proliferation, migration, and nutrient diffusion. The study explores diverse treatment strategies, including chemotherapeutic agents and immune responses, mathematically optimizing their efficacy. Utilizing a systematic parameter estimation process, the model is validated against experimental data. Results demonstrate the model's ability to predict treatment outcomes and reveal the influence of spatial heterogeneity on therapeutic effectiveness. This work contributes to advancing our understanding of tumor dynamics, offering insights into optimal treatment approaches and paving the way for personalized medicine in cancer treatment.