Therapeutic Drug Monitoring of Amikacin and Colistin in Patients with Multidrug-Resistant Gram-Negative Infections Using a Portable Plasmonic Biosensor

IF 6.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Alejandro Astúa, Maria Carmen Estevez, Sonia Luque, Santiago Grau, Luisa Sorlí, Milagro Montero, Juan P. Horcajada, Laura M. Lechuga
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Abstract

Innovative diagnostic tools that enhance antibiotic routine monitoring can improve the management of infections caused by antibiotic-resistant bacteria. Therapeutic drug monitoring (TDM) involves measuring drug levels in the patient bloodstream to ensure optimal efficacy and safety, particularly for drugs with a narrow therapeutic index (TI), assisting in dosage control and toxicity risk management. Amikacin (AK) and colistin (CS) are crucial antibiotics for treating multidrug-resistant (MDR) bacteria but they have side effects that require a precise TDM to try to minimize them. Current analytical techniques like immunoassays, high-performance liquid chromatography (HPLC), and liquid chromatography–mass spectrometry (LC-MS) are gold standards for the antibiotic analysis, but they may require transferring the human samples to centralized facilities, delaying crucial results and turnaround time. In contrast, plasmonic biosensors offer advantages for clinical diagnostics, enabling real-time drug detection with minimal sample volume and processing, being ideal for point-of-care applications. We have implemented plasmonic biosensors to quantify and rapidly monitor blood levels of amikacin and colistin. The biosensors provide high specificity and sensitivity, with limits of detection (LOD) of 0.92 ng/mL (1.57 nM) for amikacin and 9.11 pg/mL (7.88 pM) for colistin in blood serum. Statistics analyses demonstrated a strong correlation between the biosensor evaluation and the standard analytical methods (Spearman’s correlation coefficient of 0.9171 (p-value < 0.001) and 0.7435 (p-value = 0.04) for amikacin and colistin, respectively). Our plasmonic biosensors offer in addition, simplicity, portability, and label-free evaluation, with multiplexed capabilities. The rapid turnaround of results in under 20 min, coupled with minimal sample processing, enhances the feasibility of personalized TDM, supporting tailored treatment strategies that can improve patient outcomes. This work lays the foundation for creating an integrated point-of-care biosensor platform for effectively performing TDM of antibiotics and other drugs in real-time at the patient’s bedside in clinical settings.

Abstract Image

便携式等离子体生物传感器对多重耐药革兰氏阴性感染患者阿米卡星和粘菌素的监测
加强抗生素常规监测的创新诊断工具可以改善对抗生素耐药细菌引起的感染的管理。治疗性药物监测(TDM)包括测量患者血液中的药物水平,以确保最佳疗效和安全性,特别是对于治疗指数(TI)较窄的药物,有助于剂量控制和毒性风险管理。阿米卡星(AK)和粘菌素(CS)是治疗耐多药(MDR)细菌的关键抗生素,但它们有副作用,需要精确的TDM来尽量减少它们。目前的分析技术,如免疫测定、高效液相色谱(HPLC)和液相色谱-质谱(LC-MS)是抗生素分析的金标准,但它们可能需要将人体样本转移到集中设施,从而延迟关键结果和周转时间。相比之下,等离子体生物传感器为临床诊断提供了优势,能够以最小的样本量和处理实现实时药物检测,是护理点应用的理想选择。我们已经实施等离子体生物传感器来定量和快速监测阿米卡星和粘菌素的血液水平。该传感器具有较高的特异性和灵敏度,对阿米卡星和粘菌素的检测限(LOD)分别为0.92 ng/mL (1.57 nM)和9.11 pg/mL (7.88 pM)。统计分析表明,生物传感器评价与标准分析方法之间存在很强的相关性(Spearman相关系数为0.9171 (p值<;阿米卡星和粘菌素分别为0.001和0.7435 (p值= 0.04)。此外,我们的等离子体生物传感器提供简单,便携性和无标签评估,具有多路复用功能。结果在20分钟内的快速周转,加上最少的样品处理,增强了个性化TDM的可行性,支持可改善患者预后的定制治疗策略。这项工作为创建一个集成的护理点生物传感器平台奠定了基础,该平台可在临床环境中在患者床边实时有效地执行抗生素和其他药物的TDM。
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来源期刊
Analytical Chemistry
Analytical Chemistry 化学-分析化学
CiteScore
12.10
自引率
12.20%
发文量
1949
审稿时长
1.4 months
期刊介绍: Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.
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