The key experimental results from this research are the viable and cost effective methods of diagnosing oral and pancreatic cancer with accuracies over 90%. Furthermore, development of the molecular windowing method to further narrow down the origins of those cancer biomarkers and further improve accuracy.Many papers are being published demonstrating how vibrational spectral biomarkers can be used to diagnose a whole variety of diseases, from cancers to colitis. However, much of the research, proposed as discovering a useful tool for clinical diagnosis, has not yet been widely utilised in clinical practice. This is due mainly to the lack or reproducibility of the findings and current lack of relating the spectral observation to a root biological cause. This thesis aims to highlight the inconsistencies between studies and propose an improved process for spectral biomarker identification, including suggestions for follow up studies to discover the foundation of the spectral change. This thesis reassesses, and adds to, ground covered by previous reviews regarding sample preparation, patient selection and multivariate analysis.Resultantly, this thesis brings light to the need, and suggests solutions, for:• a method to standardise results between detection devices,• knowledge of the additional requirements for using biomarkers for disease monitoring/prognosis,• understanding the biological root cause for the spectral shift.These promising results and suggestions for combined methodology improvements will provide guidance to enable this burgeoning research field to improve patient outcome in the clinical sphere
