While for 1H NMR techniques there already exist common analytical and reporting standards, this does not apply to LC-MS metabolic profiling approaches. These standards are the more recommended when applying metabonomics to human biofluids, particularly urine samples, due to the high degree of biological variation compared to animals. A control study was performed, and urine samples of 30 healthy male and female human subjects were collected at intervals of 8 h twice a day for three consecutive days. Using selective multiple reaction monitoring in combination with a column-switching tool for the analysis of the mercapturate pattern, samples were screened for time and gender differences, the most common confounders. Data preprocessing parameters, alignment, scaling to internal standards, and normalization techniques were optimized by PCA, PLS-DA, and OPLS models. Great care was taken in the validation process of both analytical and chemometric protocols. Additionally, a problem of LC-MS, the combination of "different-batch" data to "one-batch" data could be solved by a batchwise scaling procedure. Based on these results, the use of metabolic profiling via mercapturates will be feasible for the detection of disease or toxicity markers in the future since mercapturates are important biomarkers of reactive metabolites known to be involved in many toxic processes.