Real-World Pharmacovigilance of Metoprolol: A Disproportionality Analysis of Adverse Events Using US FDA Adverse Event Reporting System (FAERS) and Bioinformatics
Author(s)
Shravanth R M, MPH1, Deeksha S, PharmD1, Rakshitha N, .2, Dr. Maheswari Eswar, .1.
1Department of Pharmacy Practice, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, Bangalore, India, 2Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, Bangalore, India.
1Department of Pharmacy Practice, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, Bangalore, India, 2Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, Bangalore, India.
OBJECTIVES: Cardiovascular diseases are a leading cause of morbidity and mortality globally, with beta-blockers like metoprolol widely used in managing hypertension. Despite its therapeutic value, post-marketing surveillance is essential to detect rare or previously unreported adverse events. This study aims to investigate adverse drug reactions (ADRs) associated with metoprolol using data mining techniques applied to the FDA Adverse Event Reporting System (FAERS).
METHODS: A retrospective disproportionality analysis was performed using FAERS data. Signal detection algorithms, including Proportional Reporting Ratio (PRR) and Reporting Odds Ratio (ROR), were applied with thresholds of PRR ≥ 2, ROR ≥ 2, and at least 2 reports. Additional investigation of associated genes and proteins was conducted using the PubMed gene database and STRING. Molecular docking studies were performed to evaluate the interaction of metoprolol with identified targets using PyRX, PYMOL, BIOVIA Discovery Studio, and Swiss PDB Viewer.
RESULTS: Among 29,661,136 reactions recorded in FAERS, 32,160 cases were linked to metoprolol. Signal detection identified three novel adverse events: 31 cases of epicondylitis (PRR 3.131), 47 cases of areflexia (PRR 2.475), and 17 cases of solar lentigo (PRR 2.68). Docking studies revealed strong binding affinities between metoprolol and proteins DYSF (PDB ID: 9B8K, docking score -8.8) and TRP1 (PDB ID: 5M8O, docking score -9.5), suggesting a plausible molecular basis for the observed events.
CONCLUSIONS: Post-marketing pharmacovigilance data revealed new safety signals associated with metoprolol that warrant further investigation. The integration of bioinformatics and molecular docking enhances understanding of potential drug-protein interactions. Further pharmacogenetic and pharmacoepidemiological studies are necessary to validate these findings and inform clinical risk mitigation strategies.
METHODS: A retrospective disproportionality analysis was performed using FAERS data. Signal detection algorithms, including Proportional Reporting Ratio (PRR) and Reporting Odds Ratio (ROR), were applied with thresholds of PRR ≥ 2, ROR ≥ 2, and at least 2 reports. Additional investigation of associated genes and proteins was conducted using the PubMed gene database and STRING. Molecular docking studies were performed to evaluate the interaction of metoprolol with identified targets using PyRX, PYMOL, BIOVIA Discovery Studio, and Swiss PDB Viewer.
RESULTS: Among 29,661,136 reactions recorded in FAERS, 32,160 cases were linked to metoprolol. Signal detection identified three novel adverse events: 31 cases of epicondylitis (PRR 3.131), 47 cases of areflexia (PRR 2.475), and 17 cases of solar lentigo (PRR 2.68). Docking studies revealed strong binding affinities between metoprolol and proteins DYSF (PDB ID: 9B8K, docking score -8.8) and TRP1 (PDB ID: 5M8O, docking score -9.5), suggesting a plausible molecular basis for the observed events.
CONCLUSIONS: Post-marketing pharmacovigilance data revealed new safety signals associated with metoprolol that warrant further investigation. The integration of bioinformatics and molecular docking enhances understanding of potential drug-protein interactions. Further pharmacogenetic and pharmacoepidemiological studies are necessary to validate these findings and inform clinical risk mitigation strategies.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
CO200
Topic
Clinical Outcomes, Medical Technologies, Real World Data & Information Systems
Topic Subcategory
Clinician Reported Outcomes, Performance-based Outcomes
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory), Musculoskeletal Disorders (Arthritis, Bone Disorders, Osteoporosis, Other Musculoskeletal), Neurological Disorders, Sensory System Disorders (Ear, Eye, Dental, Skin)