Abstract: In this study, a multi-scale mathematical model of the tumor immune microenvironment was developed, combining with experimental data from mouse models to investigate the regulatory mechanisms of combined therapy using the prostaglandin e2 receptor 4 (EP4) antagonist MF-766 and anti-programmed cell death protein 1 (anti-PD-1) on tumor immune microenvironment and tumor growth. The model quantitatively analyzed the dynamic changes in immunosuppressive cells, effector immune cells, and cytokines, revealing the synergistic effects of the combined therapy in reducing the concentration of myeloid-derived suppressor cells (MDSCs) and enhancing the function of effector immune cells. Experimental validation demonstrated that the model accurately described the dynamic changes in tumor volume and the immunomodulatory effects of the drugs. Furthermore, it revealed the nonlinear impact of drug dosage and dosing intervals on therapeutic efficacy. The simulation results not only deepened the understanding of the mechanisms of tumor metastasis but also provided a theoretical foundation for optimizing the dosage and dosing strategies of immunotherapy. This study lays a solid groundwork for the design and advancement of precision medicine.