The project aims to address the issue of the lack of access to basic blood tests in a majority of the world’s population. We will explore the potential of Raman spectroscopy to provide a reagent-less alternative to traditional clinical chemistry methods. By proving that Raman spectroscopy, in conjunction with advanced machine learning, is able to quantitate critical yet low-concentration analytes, it is possible to develop a purpose-built, commercial, reagent-less clinical chemistry analyzer platform providing critical insight into the health of patients in low resource settings.