Development trends of surface-enhanced Raman spectroscopy in clinical applications: From nanostructures to...

Traditional biological detection techniques often struggle to achieve high sensitivity, specificity, and non-invasiveness in complex biological samples, while laborious sample pretreatment and poor results reproducibility further limit their application in precision medicine. Surface-enhanced Raman spectroscopy(SERS), leveraging molecular fingerprint recognition and ultrahigh sensitivity, provides a promising strategy for low-abundance biomarkers. Starting from the enhancement mechanisms of SERS, this article reviews the structural design and performance modulation of substrate materials, compares different detection modalities and their applicable scenarios, summarizes advances in clinical application, analyzes common challenges limiting clinical translation, and explores the potential of artificial intelligence in improving SERS signal interpretation accuracy. The main limitation for further development of SERS has shifted from merely enhancing sensitivity to establishing standardized detection systems with high reproducibility, robust quantitative capability, and clinical interpretability. In the future, the integration of artificial intelligence-assisted spectral analysis with high-uniformity substrate design is expected to reshape the application paradigm of SERS in precision medicine.