Etodolac Single Dose Metabolic Profile Elucidation: Pharmacokinetics and Adverse Events in Healthy Volunteers - Karen Sánchez-Luquez; Anne Michelli Reis Silveira; Salvador Sánchez-Vinces; Alex Ap. Rosini Silva; Joyce Barreto; Rhubia Bethania Socorro Lemos de Brito; Caroline de Moura Garcia; Ana Lais Vieira; Marcia Ap. Antonio; Patrícia de Oliveira Carvalho (Pharmaceuticals)
Background/Objectives: This study investigates the metabolic profile of a single dose of etodolac in healthy volunteers, focusing on pharmacokinetics, clinical parameters, and metabolomic variations to identify biomarkers and pathways linked to drug response, efficacy, and safety. Methods: Thirty-seven healthy volunteers, enrolled after rigorous health assessments, received a single dose of etodolac (Flancox® 500 mg). Pharmacokinetic profiles were determined using tandem mass spectrometry analysis, and the metabolomic profiling was conducted using baseline samples (pre-dose) and samples at maximum drug concentration (post-dose) via liquid chromatography coupled with a quadrupole time-of-flight mass spectrometer. Network analysis was employed to interpret the data. Results: Correlations were observed between metabolomic profiles and pharmacokinetic parameters as well as clinical characteristics. Notably, metabolites derived from arachidonic acid, such as prostaglandins and leukotrienes, were linked to etodolac’s pharmacokinetics. Other metabolites involved in pathways like cholesterol biosynthesis, bile salts, riboflavin, and retinoic acid signaling were correlated with hematological and liver function parameters. These findings are consistent with the infrequent adverse events reported by participants, including hematological and biochemical changes in liver function. Conclusions: A set of metabolites was identified in possible associations between specific pathways and unusual side effects, comparing the metabolic profiles before and after doses of etodolac. Our results highlight the importance of optimizing drug therapy and minimizing adverse events by taking into account individual metabolic profile information.