Pharmacometabonomics: The Prediction of Drug Effects Using Metabolic Profiling
Metabonomics, also known as metabolomics, is concerned with the study of metabolite profiles in humans, animals, plants and other systems in order to assess their health or other status and their responses to experimental interventions. Metabonomics is thus widely used in disease diagnosis and in understanding responses to therapies such as drug administration. Pharmacometabonomics, also known as pharmacometabolomics, is a related methodology but with a prognostic as opposed to diagnostic thrust. Pharmacometabonomics aims to predict drug effects including efficacy, safety, metabolism and pharmacokinetics, prior to drug administration, via an analysis of pre-dose metabolite profiles. This article will review the development of pharmacometabonomics as a new field of science that has much promise in helping to deliver more effective personalised medicine, a major goal of twenty-first century healthcare.
KeywordsMetabolic phenotyping Metabolomics Metabonomics Metabotypes NMR spectroscopy Personalised medicine Pharmacometabolomics Pharmacometabonomics Precision medicine Systems medicine
I would like to acknowledge productive and enjoyable collaborations with Professor Jeremy Nicholson, Professor John Lindon, Professor Ian Wilson, Professor Elaine Holmes and Professor Elizabeth Shephard over the past 35 years or more. I have gained very much from these stimulating interactions.
The integral over time of the concentration of a drug in blood plasma: a measure of the exposure of a patient to the drug.
An electrophoretic separation methodology based on molecular charge and mobility that can be hyphenated to mass spectrometry.
The maximal blood plasma concentration achieved by a drug.
The characterisation of an organism, disease state, phenotype or response to an intervention.
Gas chromatography: a powerful method for the separation of volatile compounds. For use in metabonomics, pre-derivatisation of metabolites is required in order to achieve volatility.
High density lipoprotein.
High performance liquid chromatography: a powerful analytical separation technology often hyphenated with mass spectrometry.
Low density lipoprotein.
The degree of disorder of metabolite concentrations in an individual or in a group of subjects.
Multicomponent metabolic characteristics that result from the cumulative interactions of genetic variation, gene products and environmental exposures and that can be related directly to disease risks and therapeutic responses: also known as the metabotype.
The changes in metabolite concentrations over time in response to an intervention.
A compound in a biological matrix of an organism that is produced in that organism by an enzymatic pathway.
The full set of metabolites within, or that can be secreted from, a biological system such as a cell type or tissue.
Metabolic profiling defined in an observational fashion as “a comprehensive analysis in which all the metabolites of a biological system are identified and quantified”.
The full set of metabolites contained within an organism, i.e. the sum of all the metabolomes.
Metabolic profiling defined in an experimental fashion as “the quantitative measurement of the multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification”.
A probabilistic, multiparametric description of an organism in a given physiological state based on analysis of its cell types, biofluids and tissues: see metabolic phenotype.
The collection of microorganisms present both in and on an organism, in a variety of environmental niches.
Mass spectrometry: a sensitive analytical methodology for the detection and characterisation of metabolites in biological matrices.
Multivariate (statistical) analysis: a method for the analysis of multiple variables in an experiment or observation at a time and the simplification of the analysis problem by reduction of the large number of initial variables to a small number of key factors.
Nuclear magnetic resonance spectroscopy: the most powerful method for molecular structure identification in solution, including metabolites in biological fluids.
Orthogonal projection to latent structures with discriminant analysis: a supervised (and therefore potentially biased) approach to multivariate data analysis with the aim of finding metabolites that are statistically significantly discriminating between two groups, e.g. responders and non-responders, and which also discards metabolite variations that are orthogonal to the group discrimination.
The use of genomic, molecular and clinical information to select treatments or medicines that are more likely to be both effective and safe for that patient: also known as precision medicine or stratified medicine.
The prediction of the effects of a drug on the basis of individual genetic profiles.
The measurement of the time course of the absorption, distribution, metabolism and excretion of a drug.
This term is used synonymously with pharmacometabonomics (see below), but is sometimes erroneously used to describe the investigation of the effects of a drug on an organism: this is just diagnostic metabonomics.
The prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles.
The quantitative or qualitative measurement of specific parameters or traits that characterise individual functional biological classes or groups.
The prediction of the outcome of an intervention in an individual based on a mathematical model of pre-intervention metabolite profiles. The intervention could be a change in diet, exercise, the passage of time, surgical treatment, etc. Pharmacometabonomics is one case of predictive metabonomics, which covers the prognosis of any intervention.
An unsupervised (and therefore unbiased) multivariate statistical method for analysing high dimensional data, such as spectral data from metabonomics experiments. The PCA effects a drastic dimensionality reduction and transformation so that new principal components readily display the variance present in the dataset and therefore patterns in the data like clusters or groupings can be readily discerned and outliers identified.
The prediction of disease onset, disease outcome or the outcome of an intervention such as drug treatment.
Type 2 diabetes mellitus.
The TI measures the ratio of the effective dose of a drug for 50% of patients (expressed as ED50) to the toxic dose expressed as the TD50. Usually a minimal TI of 10 is required in drug development: some companies will aim for a more conservative TI of 30.
Ultra-performance liquid chromatography: a more efficient and effective form of HPLC using smaller column packings and higher pressures.
Very low density lipoprotein.
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