Skip to main content

ORIGINAL RESEARCH article

Front. Neurol.

Sec. Epilepsy

Volume 16 - 2025 | doi: 10.3389/fneur.2025.1493201

Implementation and Validation of a 24/7 System for the Monitoring of Antiepileptic Drugs

Provisionally accepted
  • University Medical Center Göttingen, Göttingen, Germany

The final, formatted version of the article will be published soon.

    Background: Epilepsy is a common neurological disorder associated with seizures that impact patients' quality of life. Treatment includes antiepileptic drugs (AEDs), each effective only at a specific dose, making continuous therapeutic drug monitoring (TDM) useful in clinical cases under inpatient conditions. Conventional liquid chromatography-tandem mass spectrometry (LC-MS/MS) lacks automation for 24/7 operation, limiting clinical applicability. This study validates a fully automated 24/7 AED monitoring system using the Clinical Laboratory Automated Sample Preparation Module 2030 (CLAM-2030). Methods: The method was validated according to U.S. Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidelines by evaluating linearity, precision, accuracy, carry over, matrix effects, and calibration stability. 26 AEDs were quantified in plasma using multiple reaction monitoring (MRM) transitions in positive and negative electrospray ionization modes. Sample preparation was fully automated: 20 µL methanol was used to wet the column, followed by 20 µL internal standard and 100 µL acetonitrile for protein precipitation. The supernatant was filtered and injected directly into the LC system. Chromatographic separation was achieved within 4.5 minutes using a C18 column (2.1 × 50 mm, 2.7 µm) under gradient conditions with a mobile phase of 0.2 mM ammonium formate and 0.002% formic acid. Results: The method demonstrated excellent linearity over the validated concentration ranges (R² > 0.99 for all analytes). Within-run imprecision was <15% at the lower limit of quantitation (LLOQ), while between-run imprecision was <10% for most AEDs. Accuracy was within ±10% of nominal concentrations at all quality control (QC) levels. Matrix effects were within acceptable limits (<30% variation) for 23 of 26 analytes, with compensatory corrections applied for carbamazepine-D10, felbamate-D4, and levetiracetam-D6. Carry over was negligible (<2% for all AEDs except retigabine and Ndesmethylselegiline (NDMS), which remained below 6.5%). Calibration stability was maintained over five days with concentration and peak area variation <10%. An interlaboratory comparison (ring test) showed a relative standard deviation <20% for all analytes. Conclusion: This study establishes a robust, fully automated, high-throughput method for continuous AED monitoring in the clinical setting. The CLAM-2030-LCMS-8060NX system enables reliable 24/7 TDM with minimal technical expertise, ensuring optimized AED therapy and improved patient outcomes.

    Keywords: Epilepsy, Therapeutic drug monitoring, 24/7 automation, antiepileptic drugs, LC-MS/MS, CLAM-2030

    Received: 08 Sep 2024; Accepted: 03 Mar 2025.

    Copyright: © 2025 Khromov, Dihazi, Brockmeyer, Fischer and Streit. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Tatjana Khromov, University Medical Center Göttingen, Göttingen, Germany

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

    Research integrity at Frontiers

    Man ultramarathon runner in the mountains he trains at sunset

    94% of researchers rate our articles as excellent or good

    Learn more about the work of our research integrity team to safeguard the quality of each article we publish.


    Find out more