Mental disorders contribute significantly to the global burden, and pharmacological therapy is the primary approach for managing major depressive disorder (MDD). However, the current response to treatment is not satisfactory, highlighting the need for effective strategies to predict the effectiveness of antidepressants. This study aimed to analyze a polygenic risk score and utilize a pharmacogenomic enrichment score (PES) to identify potential drugs and propose a viable treatment strategy for MDD patients. MDD data from the Taiwan Biobank were filtered using various p-value thresholds. Gene-set analysis was then conducted at each threshold, focusing on pathways with at least one gene known to interact with an approved pharmacological agent. PESs were calculated, and their correlation with treatment outcomes was examined. The analysis revealed that 15 out of 25 MDD-related pathways were associated with immune mechanisms, while the remaining pathways were primarily related to calcium ion binding and postsynaptic neurons. Three pathways, namely "RIG-I-like receptor signaling," "Cytosolic sensors of pathogen-associated DNA," and "Urs adipocyte differentiation upregulation," were significantly associated with treatment outcomes. The PES of the "RIG-I-like receptor signaling" pathway showed a positive correlation with systolic blood pressure, while the PES of the "Cytosolic sensors of pathogen-associated DNA" pathway correlated with cortisol levels. This study suggests a potential treatment strategy for MDD and identifies potential drug candidates using a PES pipeline. The immune system, calcium ion binding, and postsynaptic neurons were found to be significant pathways in MDD signal transduction, providing a basis for developing PES and precision medicine in MDD treatment.