Deep Learning-Assisted SERS for Therapeutic Drug Monitoring of Clozapine in Serum on Plasmonic Metasurfaces

Published

March 20, 2025

Author(s)

Peng Zheng, Stephen Semancik, Ishan Barman

Abstract

Clozapine is widely regarded as one of the most effective therapeutics for treatment-resistant schizophrenia. Despite its proven efficacy, the therapeutic use of clozapine is complicated by its narrow therapeutic index, which necessitates rapid and precise therapeutic drug monitoring (TDM) to optimize patient outcomes and minimize adverse effects. However, conventional techniques, such as high-performance liquid chromatography and liquid chromatography-tandem mass spectrometry, are limited by their high costs, complex instrumentation, and long turnaround times. Herein, we propose a novel approach that integrates artificial neural networks (ANNs)-based deep learning with surface-enhanced Raman spectroscopy (SERS) on a plasmonic metasurface for rapid TDM of clozapine and its two primary metabolites, norclozapine and clozapine-N-oxide, in human serum. The presented ANN-SERS strategy enables a high level of classification accuracy for the three analytes. Furthermore, the ANN-SERS regression model also offers a robust approach for predicting the concentration of each of the three analytes. We envision that the integrated ANN-SERS framework could deliver a scalable biomedical diagnostic and therapeutic tool for studying a wide variety of chemical and biological molecules in clinical settings.

Citation

Nano Letters

Pub Type

Journals

Download Paper

https://doi.org/10.1021/acs.nanolett.5c00391

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Keywords

Plasmonic Metasurface, Raman Spectroscopy, SERS, Deep Learning, Clozapine

Citation

Zheng, P. , Semancik, S. and Barman, I. (2025), Deep Learning-Assisted SERS for Therapeutic Drug Monitoring of Clozapine in Serum on Plasmonic Metasurfaces, Nano Letters, [online], https://doi.org/10.1021/acs.nanolett.5c00391, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959013 (Accessed October 8, 2025)