Early cancer diagnostics using evanescent wave Mid-IR spectroscopy

Cancer continues to be one of the most prevalent diseases worldwide. Cancer is associated with a very high mortality rate (50% survival at 10 years) as most cancers are diagnosed at a late stage. Recent advances have been made in early detection, though the assays employed are still experimental, highly expensive and can suffer from poor sensitivity and specificity. On the other hand, Mid-IR spectroscopy have shown to be robust in detecting cancer-specific analytes within the blood and other bodily fluids. However, conventional FTIR based measurements (including the use of ATR crystals) are insufficiently sensitive for such diagnostics at low analyte concentrations. In this project, we will exploit highly sensitive evanescent wave Mid-IR spectroscopy using signal enhanced ATR chips and waveguide chips and will use machine learning approach for rapid early cancer diagnostics as well as therapy monitoring. In specific this project will involve the design and fabrication of highly sensitive disposable ATR and waveguide chips optimised for cancer (breast and ovarian) biomarker sensing. The fabricated chips will be utilised for Mid-IR spectroscopy of blood plasma samples obtained from our collaborators from Cancer Research UK at Cambridge University and the results will be analysed using machine learning and deep learning algorithms specifically developed for this purpose.