5D-01 - Post-Marketing Safety Analysis of Timolol in Real-World Settings Using Bioinformatics and Disproportionality Analysis with FDA Adverse Event Reporting System (FAERS) Data

Background: Beta-blockers, especially Timolol, are commonly used in the treatment of hypertension, capitalizing on their ability to block Beta receptors in blood vessels and reduce blood pressure. This study aimed to unravel the novel safety signals associated with Timolol by leveraging real-world data for analysis.

Objectives: The study was conducted to unravel potential novel signals of Timolol to support patient safety and clinical decision-making.

Methods: A robust retrospective case and non-case disproportionality analysis of Timolol was performed using real-world data extracted from the US FDA Adverse Event Reporting System (FAERS) database. This disproportionality analysis employed advanced data mining algorithms, including Reporting Odds Ratio (ROR) and Proportional Reporting Ratio (PRR), with data sourced from the Open Vigil database. The threshold for identifying novel adverse reactions as positive signals was reactions having PRR≥2, ROR≥2, and N≥2. Proteins and genes implicated in these events were further investigated through bioinformatics tools, utilizing the PubMed gene database and STRING for protein target interaction analysis. Additionally, molecular docking simulations were performed using PyRX, PYMOL, BIOVIA Discovery Studio, and Swiss PDB Viewer to evaluate the binding affinities and interaction profiles of the drugs with their target genes, incorporating docking scores, binding energy, and protein-ligand interactions.

Results: The analysis revealed a total of 29661136 reactions recorded in the FAERS database, with 147 cases linked to Timolol. Signal detection analysis in the Open Vigil database identified 45 distinct adverse events for Timolol after high throughput screening. The novel signals are Vertebral End Plate Deformity having PRR 2779.40, Macular degeneration with 5.11, Sciatica with 3.37, Dementia Alzheimer’s type with 2.98 and Nodal Rhythm with 11.30 PRR. The total number of instances for the identified signals are 10, 57, 41, 30 and 17. In-silico studies conducted on these drugs and their novel signals produced significant results, demonstrating strong binding affinities with highest binding scores of -6.7, -6.6, -6.2, -5.3 and -5.5 for ESR1 (4Q50), CCR2 (8XYU), IFNG (1N6V), APP (5TPT) and EGFR (7V99) proteins that are involved in respective identified signals.

Conclusions: This study effectively identified significant adverse reactions that warrant further consideration. Future pharmacogenomic and pharmacoepidemiological investigations are critical to substantiate our findings and establish the precise correlation between these drugs and the implicated proteins.