ArticleInternational journal of molecular sciences2026
Investigation of Adverse Events Associated with Predicted GnRHR Agonists Using the FAERS Database.
Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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2 authors.
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Abstract
Gonadotropin-releasing hormone receptor (GnRHR) agonists are widely used therapeutically, yet their adverse event profile remains insufficiently characterized. We developed a machine-learning model using Tox21 GnRHR agonist activity data and molecular descriptors to predict GnRHR agonist activity among FDA Adverse-Event Reporting System (FAERS)-listed drugs. BalancedRandomForest achieved the highest ROC-AUC (0.810) and was applied to 5523 FAERS-listed drugs. Following applicability-domain assessment, 1191 drugs were retained, of which 367 were predicted to have GnRHR agonist activity. FAERS data from 2004 Q1 through 2024 Q3 were analyzed using reporting odds ratios (RORs) and Fisher's exact test for MedDRA Preferred Terms (PTs). Overall, 330 unique PTs corresponding to 531 PT-SOC assignments met prespecified criteria: at least 1000 reports, ln(ROR) > 1, and
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