Pharmaco-metabonomic phenotyping and personalized drug treatment
Andrew Clayton, T., 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. and Nicholson, Jeremy K. (2006) Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature: international weekly journal of science, 440 (7087). pp. 1073-1077. ISSN 0028-0836 (print), 1476-4687 (eISSN)Full text not available from this repository.
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.
|Additional Information:|| Supplementary Information is linked to the online version of the paper at www.nature.com/nature.|
|Uncontrolled Keywords:||metabonomics, pharmacometabonomics|
|Subjects:||Q Science > QD Chemistry|
R Medicine > RM Therapeutics. Pharmacology
|School / Department / Research Groups:||School of Science > Department of Pharmaceutical, Chemical & Environmental Sciences|
School of Science
|Last Modified:||05 Oct 2012 16:04|
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