Clayton, T. Andrew, Lindon, John C., Cloarec, Olivier, Antti, Henrik, Charuel, Claude, Hanton, Gilles, Provost, Jean-Pierre, Le Net, Jean-Loïc, Baker, David, Walley, Rosalind J., Everett, Jeremy R. ORCID: 0000-0003-1550-4482 and Nicholson, Jeremy K. (2006) Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature, 440 (7087). pp. 1073-1077. ISSN 0028-0836 (Print), 1476-4687 (Online) (doi:https://doi.org/10.1038/nature04648)

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Abstract

There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions1,2. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial
optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion3–5. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype
but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs6,7. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new ‘pharmaco-metabonomic’ approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects.We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between predose urinary composition and the extent of liver damage sustained after paracetamol administration.

Item Type:	Article
Additional Information:	[1] Supplementary Information is linked to the online version of the paper at www.nature.com/nature.
Uncontrolled Keywords:	metabonomics, pharmacometabonomics, NMR spectroscopy, prediction, personalised healthcare
Subjects:	Q Science > Q Science (General) R Medicine > RM Therapeutics. Pharmacology
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Science (SCI)
Related URLs:	Publisher
Last Modified:	17 Oct 2016 09:10
URI:	http://gala.gre.ac.uk/id/eprint/4415

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