Novel, accurate molecular diagnostics are driving new advances across medicine, public health, and environmental monitoring. Surface-enhanced Raman spectroscopy (SERS) nanotags are powerful platforms for ultrasensitive, multiplexed, and quantitative detection of molecular targets. This review focuses on indirect sensing strategies, where SERS nanotags act as signal transducers, resulting in enhanced and unique Raman spectra upon binding of target analytes (high specificity) and allowing for ultralow limits of detection. These indirect SERS sensors typically consist of a plasmonic core, a Raman reporter molecule, and a ligand that targets the analyte of interest. Each of these components contributes to the sensitivity, stability, and selectivity of the system. Rational design of SERS nanotags requires balancing enhancement efficiency with reproducibility, biocompatibility, and assay integration. The choice of reporter molecules, for instance, governs spectral uniqueness and enables multiplexed detection of multiple analytes within a single sample. Recent advances in artificial intelligence and machine learning are accelerating nanotag development by enabling predictive control over nanostructure geometry, composition, and optical response. SERS nanotags are increasingly being integrated into diagnostic formats, such as lateral flow assays and microfluidic devices, offering both qualitative and quantitative analysis at the point of care. This review provides an overview of key design principles, common strategies for nanostructure functionalization and stabilization, and emerging biosensing applications, serving as a practical guide for researchers seeking to design and implement SERS nanotags.
Pinkley et al. (Mon,) studied this question.