Rapid and sensitive HPLC with fluorescence detection method for quantifying selpercatinib in liver microsomes and rat...

Selpercatinib (RETEVMO®) is a selective anticancer agent recently approved for thyroid and non-small cell lung cancer. Reliable analytical methods are essential for investigating its potential drug interactions. In this study, the fluorescence properties of selpercatinib were exploited for the first time to develop a sensitive high-performance liquid chromatography with fluorescence detection (HPLC-FLD) method to quantify selpercatinib in human and rat liver microsomes and rat plasma. The method was successfully validated according to M10 guidelines demonstrating excellent accuracy, precision, selectivity, and sensitivity across a concentration range of (50-2000) ng/mL in plasma samples, with a short run time of less than 4 min. The method was applied to metabolic stability studies, where selpercatinib exhibited moderate intrinsic clearance (CL_int) in human liver microsomes (CL_int of 44.9 μL/min/mg), low clearance in female rat liver microsomes (CL_int 10.6 μL/min/mg), and nearly no depletion in male rat liver microsomes. After treatment with dexamethasone, the clearance of selpercatinib was enhanced in both female and male rat liver microsomes, suggesting potential drug-drug interaction. Dexamethasone-treated female rat liver microsomes showed clearance similar to human liver microsomes, indicating their suitability as a surrogate model for studying human metabolism in vitro. Additionally, the inhibitory effect of myricetin on selpercatinib metabolism was comparable in both human and dexamethasone-treated female rat liver microsomes, with IC₅₀ values of 9.3 μM and 10.9 μM, respectively. These findings suggest the need to investigate these potential drug interactions in clinical settings, as they may affect selpercatinib efficacy and toxicity. This HPLC-FLD method offers a rapid, sensitive, and cost-effective alternative to LC-MS/MS for studying pharmacokinetics in various in vitro and in vivo models.