SERS-Based Diagnostic Systems: Innovation and Precision Biomedical Applications

Dear Colleagues,

Over the past decades, Surface-Enhanced Raman Spectroscopy (SERS) has emerged as a transformative analytical technique due to its exceptional sensitivity, molecular specificity, and multiplexing capability. Enabled by the localized surface plasmon resonance generated on noble metal nanostructures, SERS can amplify Raman signals by factors of millions to billions, allowing the detection of single molecules and trace-level biomarkers with high precision. These advantages have positioned SERS as a powerful platform for early disease diagnosis, real-time biomedical monitoring, and precision clinical decision-making.

Recent advances in nanomaterials engineering, microfluidic integration, and artificial intelligence have further accelerated the development of SERS-based diagnostic systems. Innovations in substrate design, portable analytical platforms, and machine-learning-assisted spectral interpretation are driving the transition of SERS from laboratory research toward practical biomedical and clinical applications. Despite these promising advancements, challenges such as signal reproducibility, substrate standardization, and performance stability under complex biological conditions remain critical barriers that require sustained multidisciplinary efforts.

This Special Issue aims to provide a comprehensive overview of the latest innovations, analytical strategies, and biomedical applications of SERS-based diagnostic systems. We seek contributions that advance fundamental understanding, technological development, system integration, and translational potential of SERS in precision medicine. Original research articles and authoritative reviews are warmly welcomed. Topics of interest include, but are not limited to, the following:

• Development of innovative, low-cost, and portable SERS-based diagnostic systems (including microfluidic and integrated platforms);
• SERS-enabled noninvasive or minimally invasive early detection of cancers and other diseases;
• Machine Learning Combined with SERS technology for disease diagnosis;
• Design of highly sensitive, reproducible, and multifunctional SERS nanoprobes for biomedical applications;
• Hybrid diagnostic strategies integrating SERS with colorimetric, electrochemical, or other analytical techniques;
• State-of-the-art progress, critical evaluations, technical challenges, and future perspectives of SERS biosensing technologies

Dr. Xiaowei Cao
Guest Editor

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