Development and Validation of a Highly Sensitive LC-MS/MS Method for the Quantification of Empagliflozin and Hydrocortisone in Plasma: Application to Therapeutic Drug Monitoring and Pharmacokinetic Studies

Abstract

This study presents the development and validation of a highly sensitive and specific Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS) method for the simultaneous quantification of Empagliflozin (EMP) and Hydrocortisone (HC) in human plasma. This method is optimized to detect both compounds at low concentrations (from parts per trillion to parts per million), essential for accurate therapeutic drug monitoring (TDM) and pharmacokinetic studies. Standard stock solutions for EMP and HC were prepared following rigorous protocols to ensure precision and minimize errors, with serial dilutions providing a broad range of concentrations. Special attention was given to the preparation of plasma samples, which were spiked with known concentrations of EMP to generate accurate calibration curves. The method was validated according to ICH M10 guidelines, evaluating specificity, linearity, accuracy, precision, and sensitivity. The results demonstrated high specificity with minimal interference from placebo samples, as shown in detailed chromatographic data. Calibration curves exhibited excellent linearity, with weighted linear regression applied to enhance accuracy. The robustness of the method was confirmed across multiple testing phases, ensuring its reliability under varied sample conditions. This optimized LC-MS/MS method has demonstrated its potential for routine clinical applications, providing a reliable tool for assessing drug levels in plasma. Its application in drug monitoring and pharmacokinetic profiling ensures precise management of Empagliflozin and Hydrocortisone therapies, thereby improving patient safety and therapeutic outcomes. The methodology is suitable for clinical laboratories, offering a critical resource for optimizing individualized treatment regimens in diverse patient populations.