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关于转化代谢组学中代谢物表征与定量的前沿策略及关键进展。

Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics.

作者信息

Pillai Megha Sajakumar, Paritala Sree Teja, Shah Ravi P, Sharma Nitish, Sengupta Pinaki

机构信息

Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India.

出版信息

Drug Metab Rev. 2022 Nov;54(4):401-426. doi: 10.1080/03602532.2022.2125987. Epub 2022 Nov 9.

Abstract

Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.

摘要

尽管药物研发策略取得了显著进展,但在将新见解转化为临床应用方面仍存在重大挑战。科学家们正在设计创新方法来弥合科学研究与转化研究之间的差距。代谢组学是其他组学技术中一个独特的领域,用于识别新型代谢物和生物标志物。幸运的是,由于正交分析技术领域的进展,代谢物的表征和定量变得更快。本综述详细介绍了样品制备以及数据处理技术(包括数据挖掘工具、数据库及其质量控制(QC))的进展。数据处理工具的进步使得获取包含各种代谢物的无偏数据变得更加容易。此外,包括小型化以及它们与其他设备的集成、代谢物阵列技术和基于结晶海绵的方法等新突破,已带来更快、更高效、更具成本效益和更全面的代谢组学分析。利用前沿技术识别包括生物标志物在内的人类代谢物,已证明在疾病早期识别、跟踪疾病进展以及个性化治疗可能性方面具有优势。本综述探讨了当前代谢组学研究的制约因素,这些因素阻碍了研究从实验室到临床的转化。然而,也给出了摆脱这些制约因素的可能途径以及转化代谢组学的未来方向。

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