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Molecules 2017, 22(7), 1173; doi:10.3390/molecules22071173

Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review

1
,
1
,
2,3,* and 1,*
1
Center for Traditional Chinese Medicine and Systems Biology, Institute for Interdisciplinary Medicine Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
2
Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
3
Center for Translational Medicine, and Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
*
Authors to whom correspondence should be addressed.
Received: 6 June 2017 / Revised: 10 July 2017 / Accepted: 11 July 2017 / Published: 13 July 2017
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Abstract

Interindividual variability in drug responses and disease susceptibility is common in the clinic. Currently, personalized medicine is highly valued, the idea being to prescribe the right medicine to the right patient. Metabolomics has been increasingly applied in evaluating the therapeutic outcomes of clinical drugs by correlating the baseline metabolic profiles of patients with their responses, i.e., pharmacometabonomics, as well as prediction of disease susceptibility among population in advance, i.e., patient stratification. The accelerated advance in metabolomics technology pinpoints the huge potential of its application in personalized medicine. In current review, we discussed the novel applications of metabolomics with typical examples in evaluating drug therapy and patient stratification, and underlined the potential of metabolomics in personalized medicine in the future. View Full-Text
Keywords: metabolomics; personalized medicine; interindividual variability; pharmaco-metabonomics; patient stratification metabolomics; personalized medicine; interindividual variability; pharmaco-metabonomics; patient stratification
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Li, B.; He, X.; Jia, W.; Li, H. Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review. Molecules 2017, 22, 1173.

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