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NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

Everett, Jeremy R. ORCID: 0000-0003-1550-4482 (2017) NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine. Progress in Nuclear Magnetic Resonance Spectroscopy, 102-3. pp. 1-14. ISSN 0079-6565 (Print), 1873-3301 (Online) (doi:10.1016/j.pnmrs.2017.04.003)

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Abstract

Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systems-based approaches in biology and medicine. The experiments are typically done in a diagnostic fashion where changes in metabolite profiles are interpreted as a consequence of an intervention or event; be that a change in diet, the administration of a drug, physical exertion or the onset of a disease. By contrast, pharmacometabonomics takes a prognostic approach to metabolic profiling, in order to predict the effects of drug dosing before it occurs. Differences in pre-dose metabolite profiles between groups of subjects are used to predict post-dose differences in response to drug administration. Thus the paradigm is inverted and pharmacometabonomics is the metabolic equivalent of pharmacogenomics. Although the field is still in its infancy, it is expected that pharmacometabonomics, alongside pharmacogenomics, will assist with the delivery of personalised or precision medicine to patients, which is a critical goal of 21st century healthcare.

Item Type: Article
Uncontrolled Keywords: NMR spectroscopy; Metabonomics; Pharmacometabonomics; Metabolic profiling; Personalised or precision medicine
Subjects: R Medicine > RM Therapeutics. Pharmacology
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Pharmaceutical, Chemical & Environmental Sciences
Last Modified: 31 Aug 2017 12:03
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/17377

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