Current Applications Pharmacometabolomics

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1 current applications

1.1 predicting treatment outcome

1.1.1 metabotype informs treatment outcomes


1.2 monitoring drug-related alterations in metabolic pathways





current applications
predicting treatment outcome
metabotype informs treatment outcomes

pharmacometabolomics may used in predictive manner determine correct course of action in regards patient undergo type of drug treatment. involves determining metabolic profile of patient prior treatment, , correlating metabolic signatures outcome of pharmaceutical treatment course. analysis of patient’s metabolic profile can reveal factors may contribute altered drug metabolism, allowing predictions of overall efficacy of proposed treatment, potential drug toxicity risks may differ general population. approach has been used identify novel or characterized metabolic biomarkers in patients, can used predict expected outcome of patient following treatment pharmaceutical compound. 1 example of clinical application of pharmacometabolomics studies looked identify predictive metabolic marker treatment of major depressive disorder (mdd)., in study antidepressant sertraline, pharmacometabolomics network illustrated metabolic profile @ baseline of patients major depression can inform treatment outcomes. in addition study illustrated power of metabolomics defining response placebo , compared response placebo response sertraline , showed several pathways common both. in study escitalopram citalopram, metabolomic analysis of plasma patients mdd revealed variations in glycine metabolism negatively associated patient outcome upon treatment selective serotonin reuptake inhibitors (ssris), important drug class involved in treatment of disease.


monitoring drug-related alterations in metabolic pathways

the second major application of pharmacometabolomics analysis of patient’s metabolic profile following administration of specific therapy. process secondary pre-treatment metabolic analysis, allowing comparison of pre- , post-treatment metabolite concentrations. allows identification of metabolic processes , pathways being altered treatment either intentionally designated target of compound, or unintentionally side effect. furthermore, concentration , variety of metabolites produced compound can identified, providing information on rate of metabolism , potentially leading development of related compound increased efficacy or decreased side effects. example of approach used investigate effect of several antipsychotic drugs on lipid metabolism in patients treated schizophrenia. hypothesized these antipsychotic drugs may altering lipid metabolism in treated patients schizophrenia, contributing weight gain , hypertriglyceridemia. study monitored lipid metabolites in patients both before , after treatment antipsychotics. compiled pre- , post-treatment profiles compared examine effect of these compounds on lipid metabolism. interestingly, researchers found correlations between treatment antipsychotic drugs , lipid metabolism, in both lipid-class-specific , drug-specific manner, establishing new foundations around concept pharmacometabolomics provides powerful tools enabling detailed mapping of drug effects. additional studies pharmacometabolomics research network enabled mapping in ways not possible before effects of statins, atenolol , aspirin. totally new insights gained effect of these drugs on metabolism , highlighted pathways implicated in response , side effects.








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