Chronic obstructive pulmonary disease is a severe lung disease characterized by tissue destruction and limited airflow, mainly caused by exposure to harmful environmental substances. Primary symptoms of this lung disorder include dyspnea, sputum production, and cough, which leads to respiratory failure. Prevalence increases with age, making it the most common cause of death worldwide. The primary objective of this study was to identify novel therapeutic targets via gene expression meta-analysis and to utilize them for drug reprofiling of FDA-approved drugs in treating chronic obstructive pulmonary disease. Multiple microarray and RNA-seq datasets from alveolar macrophages comprising healthy and diseased patients were processed to pinpoint significant dysregulated genes involved in this disease. Next, a meta-analysis was performed to identify the consistently differentially expressed genes in all datasets. Functional enrichment and protein-protein interaction analyses were conducted to single out the hub genes. Moreover, 3D structure prediction, virtual screening, and molecular dynamics simulations were utilized to explore the selected hub gene for drug repurposing. The number of significantly dysregulated genes identified via RNA-seq and microarray meta-analysis was found to be 104 and 57, respectively. Interestingly, VGLL3, ITIH5, ELOVL7, ACOD1, LAMB1, CXCL9, and GBP5 were common between the two sets revealing their significant association with the disease. CXCL9 and CCL3L3 were identified as the common hub genes between both sets. However, CXCL9, a chemokine, was prioritized for drug repurposing endeavors as it exhibits remarkable involvement in immune response and inflammation. Virtual screening of CXCL9 against selected drugs disclosed that CXCL9 has the highest binding affinity of -7.3 kcal/mol for Nintedanib, and binding affinities ranged from -2.4 kcal/mol to -7.3 kcal/mol. Moreover, Tepotinib and Crizotinib were found to be the second and third top-scoring drugs of -6.8 kcal/mol and -6.2 kcal/mol, respectively. Furthermore, the molecular dynamics simulation revealed that Crizotinib showed the most prominent results; however, its binding affinity is lower than Nintedanib. Therefore, Nintedanib is suggested as the better therapeutic agent to inhibit CXCL9 for treating chronic obstructive pulmonary disease.