The aim of discovery metabolomics is to characterize, a priori, the complete metabolic composition of a sample. Building a robust discovery metabolomic platform is not trivial, and to be successful, careful attention to multiple facets of the analysis is required including robust extraction protocols, reproducibility and quality assurance, meaningful statistics, molecular identification capabilities, translatability, as well as custom data alignment and processing algorithms.
This presentation will briefly introduce common analytical platforms suitable for discovery metabolomic applications, emphasizing the efforts taken at PDI over the past ten years to build a successful discovery-to-validation MS-based analytical system. Specific discovery examples in Alzheimer’s Disease and colorectal cancer will be given.
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