Prostate　cancer　(PCa)　is　a　significant　global　health　concern　that　affects　the　male　population.　In　this　study,　we　present　a　numerical　approach　to　simulate　the　growth　of　PCa　tumors　and　their　response　to　drug　therapy.　The　approach　is　based　on　a　previously　developed　model,　which　consists　of　a　coupled　system　comprising　one　phase　field　equation　and　two　reaction-diffusion　equations.　To　solve　this　system,　we　employ　the　fast　second　-order　exponential　time　differencing　Runge-Kutta　(ETDRK2)　method　with　stabilizing　terms.　This　method　is　a　decoupled　linear　numerical　algorithm　that　preserves　three　crucial　physical　properties　of　the　model:　a　maximum　bound　principle　(MBP)　on　the　order　parameter　and　non　-negativity　of　the　two　concentration　variables.　Our　simulations　allow　us　to　predict　tumor　growth　patterns　and　outcomes　of　drug　therapy　over　extended　periods,　offering　valuable　insights　for　both　basic　research　and　clinical　treatments.