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Metabolomic-Profiling-in-Drug-Discovery-Understanding-Factors-that-Influence-a-Metabolomics-Study-and-Strategies-to-Reduce-Biochemical-and-Chemical-Noise_Metabalomics_AN562-125x166
Metabolomic Profiling in Drug Discovery: Understanding Factors that Influence a Metabolomics Study and Strategies to Reduce Biochemical and Chemical Noise

Metabolomic Profiling in Drug Discovery: Understanding Factors that Influence a Metabolomics Study and Strategies to Reduce Biochemical and Chemical Noise

App Note 562: Metabolomics is used within the pharmaceutical industryto investigate biochemical changes resulting from pharmacologicalresponses to potential drug candidates. The abilityto identify markers of toxicity/efficacy can significantlyaccelerate drug discovery and help define the appropriateclinical plan. Data from liquid chromatography-massspectrometry (LC-MS) metabolomic profiling experimentscontains large amounts of chemical background that oftenconfounds biomarker discovery. New mass spectrometertechnology and data processing software were utilizedhere to reduce chemical background in animal experimentsinvestigating the relation of animal age and nutrition todiscerning drug-induced changes.In typical LC-MS metabolomics studies, much ofthe data is redundant (multiple ions per component)and irrelevant (chemical noise). External factors thatinfluence metabolic profiles (age, nutrition) increasebiological variation. Because many of the chemical entitiesare unknowns, it is especially important to filter falsepositives before implementing structure elucidation. Ultrahighresolution instruments combined with ultra-highperformance LC (UHPLC) separations address the issuesof chemical noise and redundancy by providing sufficientresolution to distinguish metabolites from chemicalbackground. Accurate mass data allows sophisticatedprocessing needed to recognize related signals. Thisleads to significant reduction in data size and providingimproved quantitation of targeted metabolites. Biologicalfactors have profound impact on metabolic profiles andeven modest metabolic changes can obscure drug-inducedmetabolic effects. Understanding normal metabolicchanges in rats helps to minimize “biological noise” andprovides more confidence in assigning specific drug-relatedmetabolic changes.

Technique: LC-MS Resource Type: Application Note
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