Chemometric contributions to the evolution of metabonomics: mathematical solutions to characterising and interpreting complex biological NMR spectra

Abstract

The pharmaceutical industry has embraced emerging technologies such as genomics, proteomics and metabonomics over the past decade with a view to minimizing attrition and expanding drug development pipelines. Metabonomic technology, based on the multivariate analysis of complex biological profiles generated from spectroscopic instruments, has enabled the construction of successful expert systems for toxicity screening and disease diagnosis. Here we describe the evolution of chemometric and bioinformatic methodologies to accommodate the multi- and megavariate data generated by high resolution NMR spectroscopy of biofluids, tissues and cell cultures and explore their potential role in mining, modeling and predicting metabolic data.