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用于治疗药物监测的表面增强拉曼光谱技术进展

Advances in Surface-Enhanced Raman Spectroscopy for Therapeutic Drug Monitoring.

作者信息

Lai Huasheng, Wang Xinlan, Qi Menghan, Huang Hao, Yu Bingqiong

机构信息

Jiangxi Province Key Laboratory of Pharmacology of Traditional Chinese Medicine, School of Pharmacy, Gannan Medical University, Ganzhou 341000, China.

出版信息

Molecules. 2024 Dec 24;30(1):15. doi: 10.3390/molecules30010015.

Abstract

Therapeutic drug monitoring (TDM) is pivotal for optimizing drug dosage regimens in individual patients, particularly for drugs with a narrow therapeutic index. Surface-enhanced Raman spectroscopy (SERS) has shown great potential in TDM due to high sensitivity, non-destructive analysis, specific fingerprint spectrum, low sample consumption, simple operation, and low ongoing costs. Due to the rapid development of SERS for TDM, a review focusing on the analytical method is presented to better understand the trends. This review examines the latest advancements in SERS substrates and their applications in TDM, highlighting the innovations in substrate design that enhance detection sensitivity and selectivity. We discuss the challenges faced by SERS for TDM, such as substrate signal reproducibility and matrix interference from complex biological samples, and explore solutions like digital colloid-enhanced Raman spectroscopy, enrichment detection strategies, microfluidic SERS, tandem instrument technologies, and machine learning-enabled SERS. These advancements address the limitations of traditional SERS applications and improve analytical efficiency in TDM. Finally, conclusions and perspectives on future research directions are presented. The integration of SERS with emerging technologies presents a transformative approach to TDM, with the potential to significantly enhance personalized medicine and improve patient outcomes.

摘要

治疗药物监测(TDM)对于优化个体患者的给药方案至关重要,尤其是对于治疗指数较窄的药物。表面增强拉曼光谱(SERS)由于具有高灵敏度、无损分析、特定指纹光谱、低样品消耗、操作简单和持续成本低等优点,在TDM中显示出巨大潜力。由于SERS在TDM方面的快速发展,本文提出了一篇聚焦于分析方法的综述,以便更好地了解其发展趋势。本综述考察了SERS基底的最新进展及其在TDM中的应用,突出了基底设计中提高检测灵敏度和选择性的创新。我们讨论了SERS用于TDM所面临的挑战,如基底信号重现性以及复杂生物样品的基质干扰,并探索了诸如数字胶体增强拉曼光谱、富集检测策略、微流控SERS、串联仪器技术以及机器学习辅助SERS等解决方案。这些进展克服了传统SERS应用的局限性,提高了TDM中的分析效率。最后,给出了关于未来研究方向的结论和展望。SERS与新兴技术的整合为TDM提供了一种变革性方法,有望显著提升个性化医疗水平并改善患者治疗效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9573/11721930/21cbcf58601e/molecules-30-00015-g003.jpg

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