A combined application of high resolution (1)H NMR spectroscopy and multivariate statistical techniques focused on establishing a consistent statistical approach to metabonomic studies was tested. The data reduction, which is preliminary to the application of multivariate analysis to NMR spectra, was carried out by means of two complementary methods: pure Pattern Recognition (PR) and Assigned Signal Analysis (ASA). The simultaneous use of both approaches allowed us to obtain additional information in the analysis of metabonomic data, compared to the use of PR alone. This additional information consists in the possibility of a biochemical interpretation of the effects induced by treatment with xenobiotics, such as drugs or drug vehicles, on the metabolic networks of the systems under investigation. This approach allowed us to ascertain that a single-dose treatment with ST1959 vehicled by Sesame oil affects the production of hepatic glucose associated to an increment of the amino acid ketogenic process.