Low-Cost, User-Friendly SERS Technology for Rapid Detection of Emerging Drug Threats

About This Grant

Project Summary: The rising incidences of synthetic opioids misuse and emerging psychoactive substances pose significant challenges for public health and forensic toxicology. Conventional detection methods such as liquid chromatography-mass spectrometry (LC-MS) offer high sensitivity and specificity but are costly, require skilled operators, and are not feasible for rapid, point-of-care applications. To address these limitations, this project aims to develop a Surface-Enhanced Raman Spectroscopy (SERS)-based lateral flow assay for the rapid detection and quantification of existing and emerging illicit drugs in urine samples. This platform is designed to provide comparable analytical performance of LC-MS while reducing costs, increasing portability, and enabling drug testing in resource-limited settings such as rural health clinics, emergency departments and harm reduction centers. The proposed approach integrates three key innovations: (1) a SERS-active lateral flow cartridge that processes the urine sample – removing potential interferents while simultaneously separating drug mixtures and metabolites by Thin Layer Chromatography (TLC). Raman signals are enhanced via embedded nanoparticles in the TLC material for high-sensitivity detection. The SERS approach is a label-free technique that directly measures the unique vibrational modes of drug molecules, eliminating the need for biological elements like antibodies or aptamers. Unlike labeled methods, it has no strict shelf-life or storage requirements and can rapidly adapt to emerging drugs, for which specific biological recognition elements are unavailable; (2) a low-cost, Fourier Transform Raman (FT-Raman) instrument engineered for portability. The FT-Raman system offers several advantages over typical dispersive Raman systems: It provides higher spectral accuracy through interferometer-based calibration. Additionally, FT-Raman system uses a NIR excitation source to reduce fluorescence from biological samples. With fewer moving parts, the FT-Raman system offers more stability and requires less maintenance; (3) advanced chemometrics / machine learning algorithms for spectral analysis, enabling precise identification and quantification of drug compounds and their metabolites. Future phases will focus on prototype refinement and commercialization, targeting a per-test cost below $10 to enhance accessibility. Successful development of this technology has the potential to transform drug testing by enabling real-time, reliable, highly sensitive detection in decentralized settings, improving clinical decision- making and public health interventions.