Metabolic profiling of biofluids such as urine, plasma or fecal water in combination with multivariate statistical modeling tools, can provide a window for investigating the impact of disease on human health and can be used to define metabolic phenotypes associated with a wide range of physiological and pathological conditions. The growing demand for sensitive, high quality disease diagnostics has facilitated the development of new technological and statistical methods for extracting biomarkers from spectral data. Analytical pipelines for monitoring metabolic events, utilising a combination of spectroscopic methods focusing on specific molecular properties, are required to enable the assembly of panels of biomarkers that are associated with human clinical conditions e.g. inflammation, cardiovascular disease risk or gut microbial functionality. Tailored approaches to spectral acquisition can be combined with statistical methods for processing and modeling the spectral data with a view to achieving downstream diagnostic assays that are clinically translational.