Pharmaco-metabonomic phenotyping and personalized drug treatment (original) (raw)

Nature volume 440, pages 1073–1077 (2006)Cite this article

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 excretion3,4,5. 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 pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.

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Acknowledgements

We thank the technical staff of Pfizer Global R&D in Amboise, France, for their assistance in performing the animal-related work, and thank R. L. Smith for discussions. T.A.C. thanks Pfizer for financial support. O.C. acknowledges the support of the Wellcome Trust (BAIR project).

Author information

Authors and Affiliations

  1. Biological Chemistry, Biomedical Sciences Division, Faculty of Natural Sciences, Sir Alexander Fleming Building, Imperial College London, South Kensington, London, SW7 2AZ, UK
    T. Andrew Clayton, John C. Lindon, Olivier Cloarec & Jeremy K. Nicholson
  2. Department of Chemistry, Umeå University, 901 87, Umeå, Sweden
    Henrik Antti
  3. Pfizer Global Research & Development, Centre de Recherche, 37401, Amboise Cedex, France
    Claude Charuel, Gilles Hanton, Jean-Pierre Provost & Jean-Loïc Le Net
  4. Development, Centre de Recherche, 37401, Amboise Cedex
    Claude Charuel, Gilles Hanton, Jean-Pierre Provost & Jean-Loïc Le Net
  5. Pfizer Inc., 2800 Plymouth Road, Michigan, 48105, Ann Arbor, USA
    David Baker
  6. Pfizer Global Research & Development, Ramsgate Road, Kent, CT13 9NJ, Sandwich, UK
    Rosalind J. Walley & Jeremy R. Everett
  7. Development, Ramsgate Road
    Rosalind J. Walley & Jeremy R. Everett

Authors

  1. T. Andrew Clayton
  2. John C. Lindon
  3. Olivier Cloarec
  4. Henrik Antti
  5. Claude Charuel
  6. Gilles Hanton
  7. Jean-Pierre Provost
  8. Jean-Loïc Le Net
  9. David Baker
  10. Rosalind J. Walley
  11. Jeremy R. Everett
  12. Jeremy K. Nicholson

Corresponding author

Correspondence toJeremy K. Nicholson.

Ethics declarations

Competing interests

Authors J.R.E., R.J.W., D.B., C.C., G.H. and J.-L.L.N. are employees of Pfizer. Authors J.K.N. and J.C.L. have interests in Metabometrix in addition to holding academic posts at Imperial College London. Authors T.A.C. and O.C. are employees of Imperial College London with T.A.C. funded by Pfizer. H.A. holds an academic post at the University of Umeå, Sweden. In addition, T.A.C., J.R.E., J.C.L. and J.K.N. are named as inventors on patent applications relating to pharmaco-metabonomic technologies.

Supplementary information

Supplementary Table 1

This table describes the system for scoring the histology in individual liver lobes in the paracetamol study. (DOC 26 kb)

Supplementary Figure 1

This figure relates to the system for scoring the histopathological changes observed in individual liver lobes in the paracetamol study and contains four photographs showing microscopically-visible liver changes typical of histology scores 0, 1, 2 and 3, respectively. (DOC 738 kb)

Supplementary Table 2

This table summarizes the results of the standard clinical chemistry analysis of the blood plasma samples taken at ca. 24 h post-dosing in the paracetamol study. (DOC 39 kb)

Supplementary Methods

This file contains a detailed description of the methodology employed in the paracetamol study and outline descriptions of the studies on galactosamine and allyl alcohol. (DOC 60 kb)

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Andrew Clayton, T., Lindon, J., Cloarec, O. et al. Pharmaco-metabonomic phenotyping and personalized drug treatment.Nature 440, 1073–1077 (2006). https://doi.org/10.1038/nature04648

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Editorial Summary

Medicines for one

We may one day benefit from 'personalized medicine', which will involve analysing key characteristics of an individual and predicting which drugs will be effective for that patient. Although the pharmacogenomic approach looked promising, its usefulness is limited as it does not take account of potentially important environmental factors. Enter 'pharmaco-metabonomics', which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the response of an individual. A 'proof-of-principle' for this approach, in which the metabolic effects of paracetamol in rats were predicted, is published this week. This approach involves the analysis of a patient's metabolic phenotype, which is influenced not only by genotype but also by factors such as nutritional status, age and disease, so it could be an important step towards personalized human healthcare.