The New Delhi metallo-β-lactamase-1 biosensor rapidly and accurately detected antibiotic plasma concentrations in cefuroxime-treated patients.

Journal: International Journal Of Antimicrobial Agents
Published:
Abstract

Objective: Therapeutic drug monitoring (TDM) of β-lactam antibiotics in critically ill patients may benefit dose optimisation, thus improving therapeutic outcomes. However, rapidly and accurately detecting these antibiotics in blood remains a challenge. This research group recently developed a thermometric biosensor called the New Delhi metallo-β-lactamase-1 (NDM-1) biosensor, which detects multiple classes of β-lactam antibiotics in spiked plasma samples.

Methods: This study assessed the NDM-1 biosensor's effectiveness in detecting plasma concentrations of β-lactam antibiotics in treated patients. Seven patients receiving cefuroxime were studied. Plasma samples collected pre- and post-antibiotic treatment were analysed using the NDM-1 biosensor and compared with liquid chromatography coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).

Results: The biosensor detected plasma samples without dilution, and a brief pre-treatment using a polyvinylidene fluoride filter significantly lowered matrix effects, reducing the running time to 5-8 minutes per sample. The assay's linear range for cefuroxime (6.25-200 mg/L) covered target concentrations during the trough phase of pharmacokinetics in critically ill patients. The pharmacokinetic properties of cefuroxime in treated patients determined by the NDM-1 biosensor and the UPLC-MS/MS were comparable, and the cefuroxime plasma concentrations measured by the two methods showed statistically good consistency.

Conclusions: These data demonstrate that the NDM-1 biosensor assay is a fast, sensitive, and accurate method for detecting cefuroxime plasma concentrations in treated patients and highlights the NDM-1 biosensor as a promising tool for on-site TDM of β-lactam antibiotics in critically ill patients.

Authors
Qinglai Meng, Yao Wang, Yali Long, Qi Wang, Yajing Gao, Junsheng Tian, Changxin Wu, Bin Xie