Pseudomonas aeruginosa, a WHO "critical priority" pathogen, poses a major threat due to its multidrug resistance and nosocomial infections. Conventional antibiotics are increasingly ineffective; thus, antivirulence strategies that disarm pathogenicity such as toxin release, adhesion, biofilms formation, offer promise. Yet, despite extensive genomic data, integrated computational frameworks for systematic antivirulence target discovery remain scarce. Here we present the development of a reproducible, data-driven pipeline for prioritising antivirulence targets through multi-database integration. Curated datasets from the VFDB (virulence), CARD (resistance), DEG (essential genes), and NCBI (reference Genomes) were integrated. Annotated coding sequences from 150 human-derived P. aeruginosa genomes were used to construct unified presence–absence matrices of 1,129 virulence and 376 resistance genes. Each virulence factor was scored through a five-step framework: (i) VF-AMR coupling via Fisher’s test; (ii) functional weighting; (iii) essentiality filtering; (iv) AMR-decoupling via PCA covariance; and (v) composite Antivirulence Index (AVI) integration. Proteins with highest AVI scores underwent structural refinement using InterProScan domain annotation, SignalP/Phobius localisation, UniProt-PDB-AlphaFold mapping, and catalytic-site verification.   Highest-ranked targets included algP/algR3, pilY1, pilY2, pilX, pilE, exoS, exoY, tse6, and lasR, representing biofilm, adhesion, secretion, and quorum-sensing. All were highly conserved yet functionally decoupled from AMR signatures (decoupling >0.9). Structural annotation revealed potentially druggable catalytic pockets in exoS, exoY, tse6, and lasR, and accessible surface or DNA-binding interfaces in Type IV pilins and algP. This two-tier framework integrates genomic conservation metrics, AMR-decoupling analysis, and structural feasibility to enable scalable, reproducible platform for rational antivirulence drug-targets in clinical P. aeruginosa isolates.