ABSTRACT:
Metabonomics
is the comprehensive quantitative and qualitative analysis of all small
molecules in a system (in samples of cells, body fluids, tissues and so on).
One of the advantages of pharmacometabolomics over the other omics technologies
is that the metabolic profile represents the phenotype of the organism and
reflects the overall biological influences, including interactions between
multiple genomes (e.g., genomes from animals or humans and their gut
microbiome). Pharmacometabolomics uses the predose metabolite profiling in the
biofluids or fecal extracts to predict the responses of an individual to a
chemical intervention and to identify surrogate markers for subsequent drug
administration.
A
primary goal of personalized medicine is to provide the best medical treatment
for each individual patient by determining which drug will have the best
efficacy and have the least amount of toxicity and/or adverse effects.
Furthermore, understanding interindividual variations of response to drug
treatment, especially in patients with potential adverse reactions, might lead
to biomarkers that can be used to predict the low incidence of idiosyncratic
toxicity. Personalized medicine is usually based on the concept of
pharmacogenomics that studies the influence of an individual's genotype and/or
SNPs on their response to a drug or medical treatment. Despite enormous energy
and monetary efforts, pharmacogenomics has had limited success in clinical
pharmacology to predict drug response with absolute certainty using single or
multiple SNPs as biomarkers. The major reason for the limitation is that the
response is dependent upon the phenotype of an individual, which is determined
by both genotype and its complex interactions with other environmental factors.
These environmental factors include diet, lifestyle, gut microbiome, nutrition,
medications (polypharmacy), age and exposures to toxins or dietary supplements,
as well as the individual physical and pathological conditions (e.g., diabetes
and obesity).
The major limitation of proteomic screens is
that they are tissue specific and therefore require tissue to characterize
protein variability. Further tissue samples from organs such as lung, kidney,
heart, or brain are not easily obtained for proteomic screens. Therefore
this paper envisages the need for integration of all omics based technologies
like Pharmacogenomics, Proteomics and Pharmacometabonomics for an integrated
approach towards personalized drug therapy in order to maximize disease related
outcomes and minimize unwanted effects.
