Vibrational Spectroscopy of Clinical Biofluids: Advances in FTIR and Raman-Based Biomarker Discovery for Disease Diagnosis and Monitoring

Human biofluids carry a continuously updated molecular record of systemic health, yet their diagnostic potential remains largely untapped by conventional single-analyte assay platforms. Fourier-transform infrared and Raman spectroscopy, including attenuated total reflection FTIR, surface-enhanced Raman spectroscopy, and FT-Raman, generate label-free spectral fingerprints encoding protein, lipid, nucleic acid, and metabolite composition of biological fluids within a single acquisition. Across five clinically accessible biofluids, namely serum, urine, saliva, cerebrospinal fluid, and tear fluid, diagnostic accuracies of 80-100% have been demonstrated for cancers, neurodegenerative, metabolic, infectious, and renal conditions, with surface-enhanced Raman spectroscopy achieving femtomolar sensitivity through plasmonic nanoparticle enhancement. Machine learning has transformed raw spectra into clinically actionable classifiers, with deep learning outperforming classical chemometric methods in multi-class discrimination. Portable instrumentation, microfluidic substrates, federated learning, and open spectral databases progressively resolve barriers of inter-instrument variability and pre-analytical irreproducibility. Structured multi-centre clinical investment is the outstanding requirement for realization as frontline diagnostic tools.