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An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis
An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis
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An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis
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An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis
An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis

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An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis
An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis
Journal Article

An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis

2025
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Overview
To combine pharmacovigilance and network toxicology methods to observe the acute pancreatitis (AP) following the use of antipsychotics, and potential toxic mechanisms, and to provide a reference for the safe use of drugs. This study combined pharmacovigilance methods using real-world data and network toxicology methods to investigate AP associated with antipsychotics and the potential toxicological mechanism involved. First, the reports of antipsychotics were extracted from the US FDA Adverse Event Reporting System (FAERS), and the signals of AP were detected by four pharmacovigilance algorithms. The gene targets of drugs were predicted using multiple databases. The disease targets of AP were determined by bioinformatics methods. Protein-protein interaction (PPI) analysis was conducted using STRING database, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were also performed through R software. Molecular docking was applied to test the molecular affinity using AutoDock. The signal intensity of AP was statistically significant in olanzapine, quetiapine, and fluphenazine. Due to the small number of reports associated with AP AEs on fluphenazine, our subsequent studies mainly focused on olanzapine and quetiapine. The results of stratification analysis suggested robustness of our results. Age ≤65, female, and weight >80 kg were identified as risk factors of the development of AP in patients receiving olanzapine, while weight >80 kg and age ≤65 were risk factors of that in patients receiving quetiapine. Network toxicology analysis and molecular docking suggested that olanzapine and quetiapine may exert their toxic effects through acting on hub genes. The pharmacovigilance analysis investigated the signal intensity, clinical features, risk factors, and onset time of AP associated with olanzapine and quetiapine. Network toxicology analysis suggested that the toxic effects of olanzapine and quetiapine may be related to their hub genes.