Efficient analysis of adverse drug events and toxicological mechanisms of newly marketed drugs by integrating pharmacovigilance and network toxicology: selumetinib as an example - Xiong, Rui; Lei, Jing; Wang, Lu; Zhang, Shipeng; Liu, Hengxu; Wang, Hongping; Liu, Tao; Lai, Xiaodan (Frontiers in Pharmacology, 2024)
Objective: To integrate pharmacovigilance and network toxicology methods to explore the potential adverse drug events (ADEs) and toxic mechanisms of selumetinib, and to provide a reference for quickly understanding the safety and toxicological mechanisms of newly marketed drugs. Methods: Taking selumetinib as an example, this study integrated pharmacovigilance methods based on real-world data and network toxicology methods to analyze its ADE and its potential toxicological mechanism. First, the ADE reports of selumetinib were extracted from the US Food and Drug Administration (FDA) adverse event reporting system (FAERS), and the ADE signals were detected by reporting odds ratio (ROR) and UK medicines and healthcare products regulatory agency (MHRA) methods. The ADE signals were classified and described according to the preferred terms (PTs) and system organ class (SOC) derived from the Medical Dictionary for Regulatory Activities (MedDRA). The network toxicology method was used to analyze the toxicological mechanism of the interested SOCs. The specific steps included predicting the potential targets of selumetinib using TOXRIC, STITCH, ChEMBL, CTD, SwissTargetPreditcion, and Super-PRED databases, collecting the targets of SOC using GeneCards database, conducting protein-protein interaction (PPI) analysis through STRING database, conducting gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis through DAVID database, and testing the molecular affinity using AutoDock software. Results: A total of 1388 ADE reports related to selumetinib were extracted, and 53 positive signals were detected by ROR and MHRA methods, of which 20 signals were not mentioned in the package insert, including ingrowing nail, hyperphosphatemia, cardiac valve disease, hematuria, neutropenia, etc. Analysis of the toxicological mechanism of six SOCs involved in positive ADE signals revealed that the key targets included EGFR, STAT3, AKT1, IL6, BCL2, etc., and the key pathways included PI3K/Akt pathway, apoptosis, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance, etc. Molecular docking assays showed spontaneous binding of selumetinib to key targets in these pathways. Conclusions: The pharmacovigilance analysis identified some new potential ADEs of selumetinib, and the network toxicology analysis showed that the toxic effects of selumetinib may be related to PI3K/Akt pathway, apoptosis, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance.