A reliable, validated test would enhance our ability to treat and research chronic conditions. Early and accurate diagnosis would provide an entry point into clinical care, give access to benefits, remove the stigma associated with these conditions, and importantly, provide researchers with a fundamental tool they require to study these heterogeneous disorders. In this chapter, we describe how Raman microspectroscopy can be utilised to study the biology of peripheral blood mononuclear cells (PBMCs) isolated from human blood samples. Using machine learning approaches, the data generated can be used to attempt to separate different patient and control groups, subgroups within a patient cohort, and identify differences in intracellular metabolites which may provide clues about disease mechanisms.