Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Author:

Beeram Reshma1,Vepa Kameswara Rao1,Soma Venugopal Rao1ORCID

Affiliation:

1. Advanced Centre of Research in High Energy Materials (ACRHEM), DRDO Industry Academia—Centre of Excellence (DIA-COE), University of Hyderabad, Hyderabad 500046, Telangana, India

Abstract

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS’s full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

Funder

Defence Research and Development Organisation

Publisher

MDPI AG

Subject

Clinical Biochemistry,General Medicine,Analytical Chemistry,Biotechnology,Instrumentation,Biomedical Engineering,Engineering (miscellaneous)

Reference409 articles.

1. Nanostructured Plasmonic Sensors;Stewart;Chem. Rev.,2008

2. Nanomaterials for Optical Biosensors in Forensic Analysis;Costanzo;Talanta,2023

3. Chen, G., Chen, Y., Huang, W., and Shi, Y. (2022, January 25–27). Plasmonic Nanobiosensors for Detection of Different Targets. Proceedings of the Second International Conference on Medical Imaging and Additive Manufacturing (ICMIAM 2022), Xiamen, China.

4. Enzymatic Optical Biosensors for Healthcare Applications;Sadani;Biosens. Bioelectron. X,2022

5. Layer-by-Layer Modification Strategies for Electrochemical Detection of Biomarkers;Erkmen;Biosens. Bioelectron. X,2022

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