Omics
technologies have rapidly evolved with the unprecedented
potential to shape precision medicine. Novel omics approaches are
imperative toallow rapid and accurate data collection and integration
with clinical information and enable a new era of healthcare. In
this comprehensive review, we highlight the utility of Raman spectroscopy
(RS) as an emerging omics technology for clinically relevant applications
using clinically significant samples and models. We discuss the use
of RS both as a label-free approach for probing the intrinsic metabolites
of biological materials, and as a labeled approach where signal from
Raman reporters conjugated to nanoparticles (NPs) serve as an indirect
measure for tracking protein biomarkers in vivo and
for high throughout proteomics. We summarize the use of machine learning
algorithms for processing RS data to allow accurate detection and
evaluation of treatment response specifically focusing on cancer,
cardiac, gastrointestinal, and neurodegenerative diseases. We also
highlight the integration of RS with established omics approaches
for holistic diagnostic information. Further, we elaborate on metal-free
NPs that leverage the biological Raman-silent region overcoming the
challenges of traditional metal NPs. We conclude the review with an
outlook on future directions that will ultimately allow the adaptation
of RS as a clinical approach and revolutionize precision medicine.