Development of a relative molar sensitivity-based HPLC method for quantifying acetaminophen, two beta-lactams, amiodarone, and its metabolite
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Updated: Nov 4, 2026

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
Published on: April 23, 2019
Takashi Ohtsuki1, Yume Enomoto2, Akane Yasuda2
1College of Bioresource Sciences, Nihon University, 1866 Kameino, Fujisawa, Kanagawa, Japan. ohtsuki.takashi@nihon-u.ac.jp.
Background:
Therapeutic drug monitoring (TDM) is essential for drugs with narrow therapeutic ranges and high pharmacokinetic variability. However, significant barriers hinder TDM implementation. Outsourcing of testing can delay timely clinical decision-making, with possible delays of up to 1 week. Additionally, management of analyte-specific certified reference material (CRM) presents substantial operational challenges, particularly for unstable compounds. The present study therefore developed and validated a high-performance liquid chromatography (HPLC) method based on relative molar sensitivity (RMS) of stable non-analyte reference materials (carbamazepine and caffeine) to quantify five clinically important analytes-acetaminophen, two beta-lactam antibiotics (cefmetazole and cefazolin), and amiodarone and its active metabolite, N-desethylamiodarone.
Methods:
RMS values were calculated as the ratio of the analyte and non-analyte reference material calibration curve slopes. CRM solutions were used at 6 to 10 concentrations per analyte. HPLC analysis utilized analyte-specific detection wavelengths in the range 240-275 nm. For validation, control serum samples were spiked at 2 or 3 concentrations per analyte and processed via spin-column solid-phase extraction. Quantitative accuracy was assessed by comparing the RMS-based results with conventional absolute calibration methods.
Results:
All calibration curves demonstrated excellent linearity, with correlation coefficients in the range 0.9993-1.0000. Calibration curve slope reproducibility was high, with relative standard deviations of 0.3%-1.5% (n = 3). Quantitative analyses of spiked serum samples showed close agreement between the RMS and conventional methods, with relative differences not exceeding ± 0.50% for either calibrant for any analyte. Both methods achieved comparable precision, with relative standard deviations of < 4.6%.
Conclusions:
The validated RMS-based HPLC method provides accurate and precise quantification of structurally diverse drugs using stable, the International System of Units (SI)-traceable, non-analyte reference materials. This approach eliminates the need for analyte-specific authentic standards for routine analyses, thus substantially reducing procurement costs and addressing the instability of some analytes. The rapid and accurate analysis enables timely reporting, potentially leading to improved clinical outcomes through expedited in-house TDM implementation in hospital laboratories with limited resources.
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