ArticleFrontiers in pharmacology2025
An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis.
Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Integration of FAERS database and network toxicology to investigate adverse drug events and potential toxicological mechanisms of triazole antifungal agents.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- An integrative pharmacovigilance, network toxicology and molecular docking study on drug-induced cheilitis.Frontiers in pharmacology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: 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. Methods: 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. Results: 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. Conclusion: 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.