Literature DB >> 26220091

Exploration of individuality in drug metabolism by high-throughput metabolomics: The fast line for personalized medicine.

Oxana Trifonova1, Richard A Knight2, Andrey Lisitsa1, Gerry Melino2, Alexey V Antonov3.   

Abstract

In many cases, individuality in metabolism of a drug is a reliable predictor of the drug efficacy/safety. Modern high-throughput metabolomics is an ideal instrument to track drug metabolism in an individual after treatment. Productivity and low cost of the metabolomics are sufficient to analyse a large cohort of patients to explore individual variations in drug metabolism and to discover drug metabolic biomarkers indicative of drug efficacy/safety. The only potential disadvantage of metabolomics becoming a routine clinical procedure is a need to treat the patient once before making a prognosis. However, in many clinical applications this would not be a limitation. Here, we explore current opportunities and challenges for translating high-throughput metabolomics into the platform for personalized medicine.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 26220091     DOI: 10.1016/j.drudis.2015.07.011

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  5 in total

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Authors:  J Rafael Montenegro-Burke; Aries E Aisporna; H Paul Benton; Duane Rinehart; Mingliang Fang; Tao Huan; Benedikt Warth; Erica Forsberg; Brian T Abe; Julijana Ivanisevic; Dennis W Wolan; Luc Teyton; Luke Lairson; Gary Siuzdak
Journal:  Anal Chem       Date:  2017-01-03       Impact factor: 6.986

Review 2.  New horizons in treatment of osteoporosis.

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Journal:  Daru       Date:  2017-02-07       Impact factor: 3.117

3.  Diagnostic Value of 1H NMR-Based Metabolomics in Acute Lymphoblastic Leukemia, Acute Myeloid Leukemia, and Breast Cancer.

Authors:  Hanaa M Morad; Mohamed M Abou-Elzahab; Salah Aref; Ahmed M A El-Sokkary
Journal:  ACS Omega       Date:  2022-02-22

Review 4.  Parkinson's Disease: Available Clinical and Promising Omics Tests for Diagnostics, Disease Risk Assessment, and Pharmacotherapy Personalization.

Authors:  Oxana P Trifonova; Dmitri L Maslov; Elena E Balashova; Guzel R Urazgildeeva; Denis A Abaimov; Ekaterina Yu Fedotova; Vsevolod V Poleschuk; Sergey N Illarioshkin; Petr G Lokhov
Journal:  Diagnostics (Basel)       Date:  2020-05-25

5.  Drug Metabolite Cluster-Based Data-Mining Method for Comprehensive Metabolism Study of 5-hydroxy-6,7,3',4'-tetramethoxyflavone in Rats.

Authors:  Yuqi Wang; Xiaodan Mei; Zihan Liu; Jie Li; Xiaoxin Zhang; Shuang Lang; Long Dai; Jiayu Zhang
Journal:  Molecules       Date:  2019-09-09       Impact factor: 4.411

  5 in total

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