Phenobarbital serves as an antiepileptic drug (AED) and finds application in the treatment of epilepsy either as monotherapy or adjunctive therapy. This drug exhibits various pharmacodynamic properties that account for its beneficial effects as well as potential side effects. Accurate measurement of its concentration is critical for optimizing AED therapy through appropriate dose adjustments. Therefore, our objective was to develop and validate a new reference measurement procedure (RMP) for the accurate quantification of phenobarbital levels in human serum and plasma. A sample preparation protocol based on protein precipitation followed by a high dilution step was established in combination with a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method using a C8 column to separate target analytes from known and unknown interferences. Assay validation and determination of measurement uncertainty were performed based on current guidelines. Selectivity and Specificity were assessed using spiked serum and plasma samples; to investigate possible matrix effects (MEs) a post-column infusion experiment and a comparison of standard line slopes was performed. Precision and accuracy were determined within a multiday precision experiment. The RMP was shown to be highly selective and specific, with no evidence of matrix interferences. It can be used to quantify phenobarbital in the range of 1.92 to 72.0 μg/mL. Intermediate precision was less than 3.2 %, and repeatability coefficient of variation (CV) ranged from 1.3 to 2.0 % across all concentration levels. The relative mean bias ranged from -3.0 to -0.7 % for native serum levels, and from -2.8 to 0.8 % for Li-heparin plasma levels. The measurement uncertainties (k=1) for single measurements and target value assignment were 1.9 to 3.3 % and 0.9 to 1.6 %, respectively. A novel LC-MS/MS-based candidate RMP for the quantification of phenobarbital in human serum and plasma is presented which can be used for the standardization of routine assays and the evaluation of clinically relevant samples.
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