Osimertinib-induced interstitial lung disease insights from faers signal detection and network toxicology analysis

Osimertinib is a key treatment for EGFR-mutated non-small cell lung cancer, but interstitial lung disease (ILD) remains a rare yet potentially life-threatening pulmonary adverse event. Early recognition of osimertinib-associated ILD and clarification of its underlying mechanisms are important for improving clinical management. In this study, real-world pharmacovigilance data from the FDA Adverse Event Reporting System (FAERS; 2015Q4-2025Q2) were extracted, deduplicated, and evaluated using four disproportionality algorithms. Potential molecular links between osimertinib and ILD were further explored by integrating drug- and disease-related targets from SwissTargetPrediction, CTD, GeneCards, and DisGeNET, followed by intersection analysis, protein-protein interaction (PPI) network construction, and functional enrichment analysis. A total of 24,676 osimertinib-related adverse event reports were identified, and ILD emerged as one of the strongest pulmonary safety signals. Among 484 ILD reports, cases were more commonly observed in older patients, women, and Asian patients, and were associated with high rates of hospitalization and serious clinical outcomes. Twenty-one overlapping targets between osimertinib and ILD were identified, and PPI network analysis highlighted CTNNB1, KRAS, STAT3, and TP53 as central nodes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated significant involvement of cancer-related pathways, EGFR tyrosine kinase inhibitor resistance, and multiple signaling and regulatory pathways, including PI3K-Akt, MAPK, and Wnt/β-catenin-related signaling, suggesting potential roles in inflammation, epithelial injury, and fibrotic remodeling. Together, these findings integrate pharmacovigilance evidence with network-based mechanistic prediction and provide a basis for risk-stratified monitoring and further experimental validation of osimertinib-associated ILD.