Future precision
medicine will be undoubtedly sustained by the
detection of validated biomarkers that enable a precise classification
of patients based on their predicted disease risk, prognosis, and
response to a specific treatment. Up to now, genomics, transcriptomics,
and immunohistochemistry have been the main clinically amenable tools
at hand for identifying key diagnostic, prognostic, and predictive
biomarkers. However, other molecular strategies, including metabolomics,
are still in their infancy and require the development of new biomarker
detection technologies, toward routine implementation into clinical
diagnosis. In this context, surface-enhanced Raman scattering (SERS)
spectroscopy has been recognized as a promising technology for clinical
monitoring thanks to its high sensitivity and label-free operation,
which should help accelerate the discovery of biomarkers and their
corresponding screening in a simpler, faster, and less-expensive manner.
Many studies have demonstrated the excellent performance of SERS in
biomedical
applications. However, such studies have also revealed several variables
that should be considered for accurate SERS monitoring, in particular,
when the signal is collected from biological sources (tissues, cells
or biofluids). This Perspective is aimed at piecing together the puzzle
of SERS in biomarker monitoring, with a view on future challenges
and implications. We address the most relevant requirements of plasmonic
substrates for biomedical applications, as well as the implementation
of tools from artificial intelligence or biotechnology to guide the
development of highly versatile sensors.