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Cited by 262

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Metabonomics in pharmaceutical R & D

Open access
Lindon, John C., Holmes, Elaine, Nicholson, Jeremy K.·2007·The FEBS Journal

Abstract

This minireview is based on a lecture given at the First Maga Circe Conference on metabolomics held at Sabaudia, Italy, in March 2006 in which the analytical and statistical techniques used in metabonomics, efforts at standardization and some of the major applications to pharmaceutical research and development are reviewed. Metabonomics involves the determination of multiple metabolites simultaneously in biofluids, tissues and tissue extracts. Applications to preclinical drug safety studies are illustrated by the Consortium for Metabonomic Toxicology, a collaboration involving several major pharmaceutical companies. This consortium was able, through the measurement of a dataset of NMR spectra of rodent urine and serum samples, to build a predictive expert system for liver and kidney toxicity. A secondary benefit was the elucidation of the endogenous biochemicals responsible for the classification. The use of metabonomics in disease diagnosis and therapy monitoring is discussed with an exemplification from coronary artery disease, and the concept of pharmaco‐metabonomics as a way of predicting an individual's response to treatment is exemplified. Finally, some advantages and perceived difficulties of the metabonomics approach are summarized.

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Metadata

Authors
Lindon, J. C., Holmes, E., & Nicholson, J. K.
Venue
The FEBS Journal
Publisher
Wiley
Published
2007-02-09
Volume
274
Issue
5
Pages
1140-1151
ISSN
  • 1742-464X (ISSN-L)
  • 1742-4658
OpenAlex
W1597273370
Cited by
262
References
1
FWCI
13.65
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Metabonomics in pharmaceutical R & D. https://app.cochat.ai/papers/10.1111/j.1742-4658.2007.05673.x
The paper
Lindon, J. C., Holmes, E., & Nicholson, J. K. (2007). Metabonomics in pharmaceutical R & D. The FEBS Journal. https://doi.org/10.1111/j.1742-4658.2007.05673.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.