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

IF 3.4 2区 医学 Q2 PHARMACOLOGY & PHARMACY
Megha Sajakumar Pillai, Sree Teja Paritala, Ravi P Shah, Nitish Sharma, Pinaki Sengupta
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引用次数: 0

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.

关于翻译代谢组学的代谢物表征和量化的前沿策略和关键进展。
尽管药物发现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然存在重大挑战。科学家们正在设计创造性的方法来弥合科学研究和转化研究之间的差距。代谢组学在其他组学技术中是一个独特的领域,用于鉴定新的代谢物和生物标志物。幸运的是,由于正交分析技术的进步,代谢物的表征和定量变得越来越快。本文详细介绍了样品制备的进展,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)。数据处理工具的进步使人们更容易获得包括多种代谢物的公正数据。此外,新的突破,包括小型化及其与其他设备的集成,代谢物阵列技术和基于晶体海绵的方法,导致更快,更高效,更具成本效益和全面的代谢组学分析。使用尖端技术来识别人类代谢物,包括生物标志物,已被证明在早期疾病识别、跟踪疾病进展和个性化治疗的可能性方面是有利的。这篇综述讨论了当前代谢组学研究的限制,这些限制阻碍了从实验室到临床研究的转化。然而,从这些限制和翻译代谢组学的未来方向可能的出路已经被授予。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Drug Metabolism Reviews
Drug Metabolism Reviews 医学-药学
CiteScore
11.10
自引率
1.70%
发文量
21
审稿时长
1 months
期刊介绍: Drug Metabolism Reviews consistently provides critically needed reviews of an impressive array of drug metabolism research-covering established, new, and potential drugs; environmentally toxic chemicals; absorption; metabolism and excretion; and enzymology of all living species. Additionally, the journal offers new hypotheses of interest to diverse groups of medical professionals including pharmacologists, toxicologists, chemists, microbiologists, pharmacokineticists, immunologists, mass spectroscopists, as well as enzymologists working in xenobiotic biotransformation.
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