ArticleAnalytical chemistry2025
Improving Meropenem Quantification in a Compact SERS-Based Centrifugal Microfluidic Platform: Toward TDM of Antibiotics in ICU.
Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Microscale solid-phase extraction: advances in sorbent formats, system design, integration, and detection methods.Analytical and bioanalytical chemistry · 2026Review
- SERS-Based Nano- and Microsystems Toward Biomedical Applications.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- SERS-powered precision: revolutionizing therapeutic drug monitoring with nanoscale sensitivity.Mikrochimica acta · 2025Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infections are the leading causes of death, especially in intensive care units (ICUs), necessitating immediate and optimal antibiotic treatment with proper monitoring of the drug dosage. Present analytical techniques measuring antibiotic levels result in a long lag time for dose adjustments. Therefore, introducing versatile techniques that quickly quantify antibiotic levels in a patient's blood is essential. We developed a novel approach to advance the automation of label-free surface-enhanced Raman spectroscopy (SERS) in a centrifugal microfluidic setting (D-SERS device) to improve the quantification of meropenem (MER) in serum samples. The D-SERS device consists of a microfluidic disc cartridge, a spin motor, and an integrated Raman spectrometer module. In our assay method, we implemented a serum cleanup step, employing a monospin solid-phase extraction (ms-SPE) column, which was coupled with the D-SERS device. The MER label-free detection was performed on-disc by SERS scanning of a Ag nanopillar substrate integrated into the disc cartridge. We identified that coupling ms-SPE to the D-SERS device led to significant improvement in a signal-to-noise ratio and sensitivity. Chemometrics algorithms, such as partial least squares regression (PLSR), were implemented on a large data set for SERS analysis, allowing LoD and LoQ values of 12.12 and 36.37 μM, respectively. We compared the performance of our D-SERS device to that of a commercial Raman system, demonstrating its efficiency and reliability. Moreover, the D-SERS device was validated against HPLC employing samples from ICU patients, showing a good correlation (
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