A pragmatic and readily implemented quality control strategy for HPLC-MS and GC-MS-based metabonomic analysis

Abstract

Metabonomic/metabolomic studies can involve the analysis of large numbers of samples for the detection of biomarkers and confidence in the analytical data, generated by methods such as GC and HPLC-MS, requires active measures on the part of the analyst. However, quality control for complex multi-component samples such as biofluids, where many of the components of interest in the sample are unknown prior to analysis, poses significant problems. Here the repeat analysis of a pooled sample throughout the run, thereby enabling the analysis to be monitored and controlled using targeted inspection of the data and pattern recognition, is advocated as a pragmatic solution to this problem.