Progress in electrochemical detection of levofloxacin and norfloxacin antibiotics: advanced functional materials, analytical performance, challenges, and perspectives.

Authors

Khursheed Ahmad, Vinay Kumar Tripathi, Rohit Kumar Singh Gautam, Vivek Mani Tripathi, Chellakannu Rajkumar, Tae Hwan Oh

Published in

The Analyst. Oct 09, 2026. Epub Oct 09, 2026.

Abstract

In recent years, electrochemical sensing of fluoroquinolone antibiotics has attracted significant research interest. However, the practical relevance of many reported sensors remains uncertain because their performance is evaluated primarily on the basis of detection limits. This review critically evaluates reported sensing systems for levofloxacin (LFN) and norfloxacin (NOR), two structurally related antibiotics that provide a stringent basis for assessing both signal amplification and molecular selectivity. Direct voltammetric detection, electrocatalytic electrodes, molecularly imprinted interfaces, biosensors, ion-selective membranes, and ion transfer across electrified liquid-liquid interfaces have been critically assessed using a unified analytical framework. Metal oxides, carbon-based materials, polymers, MXenes, porous frameworks, and hybrid composites are further examined in terms of their specific roles in molecular recognition, charge transfer, and signal generation. This review critically evaluates selectivity, analytical performance in real samples, reproducibility, operational stability, fabrication complexity, and compatibility with disposable sensing systems. It is also observed that more complex sensor designs do not always improve analytical performance. In many cases, simpler electrodes provide a better balance of sensitivity, reliability, and ease of fabrication. The practical application of electrochemical sensors for LFN and NOR is still limited by insufficient validation against established reference methods and the lack of testing with incurred samples. Future studies may focus on simpler and more reproducible sensing systems that can provide reliable results in routine LFN and NOR analysis. Finally, challenges and future research directions are discussed.

PMID:
42853220
Bibliographic data and abstract were imported from PubMed on 09 Oct 2026.

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