Nanopillar-Assisted SERS Chromatography

Improving Meropenem Quantification in a Compact SERS-Based Centrifugal Microfluidic Platform: Toward TDM of Antibiotics in ICU

Infections are the leading causes of death, especially in intensive care units (ICUs), necessitating immediate and optimal antibiotic treatment with proper monitoring of the drug dosage. Present analytical techniques measuring antibiotic levels result in a long lag time for dose adjustments. Therefore, introducing versatile techniques that quickly quantify antibiotic levels in a patient's blood is essential. We developed a novel approach to advance the automation of label-free surface-enhanced Raman spectroscopy (SERS) in a centrifugal microfluidic setting (D-SERS device) to improve the quantification of meropenem (MER) in serum samples. The D-SERS device consists of a microfluidic disc cartridge, a spin motor, and an integrated Raman spectrometer module. In our assay method, we implemented a serum cleanup step, employing a monospin solid-phase extraction (ms-SPE) column, which was coupled with the D-SERS device. The MER label-free detection was performed on-disc by SERS scanning of a Ag nanopillar substrate integrated into the disc cartridge. We identified that coupling ms-SPE to the D-SERS device led to significant improvement in a signal-to-noise ratio and sensitivity. Chemometrics algorithms, such as partial least squares regression (PLSR), were implemented on a large data set for SERS analysis, allowing LoD and LoQ values of 12.12 and 36.37 μM, respectively. We compared the performance of our D-SERS device to that of a commercial Raman system, demonstrating its efficiency and reliability. Moreover, the D-SERS device was validated against HPLC employing samples from ICU patients, showing a good correlation (R2 = 0.8, p < 0.05) with a bias of 14.3 μM overestimation. The whole D-SERS system is compact and easy to operate, and results are obtained within 15-20 min, supporting its clinical feasibility for point-of-care therapeutic drug monitoring of antibiotics.

Factors that Affect Quantification in Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) is an analytical technique capable of detecting trace amounts of specific species. The uniqueness of vibrational signatures is a major advantage of SERS. This combination of sensitivity and specificity has motivated researchers to develop diverse analytical methodologies leveraging SERS. However, even 50 years after its first observation, SERS is still perceived as an unreliable technique for quantification. This perception has precluded the application of SERS in laboratories that rely on consistent quantification (for regulatory purposes, for instance). In this review, we describe some of the aspects that lead to SERS intensity variations and how those challenges were addressed in the 50 years of the technique. The goal is to identify the sources of variations in SERS intensities and then demonstrate that, even with these pitfalls, the technique can be used for quantification when factors such as nature of the substrate, experimental conditions, sample preparation, surface chemistry, and data analysis are carefully considered and tailored for a particular application.

Solid-phase extraction coupled to automated centrifugal microfluidics SERS: Improving quantification of therapeutic drugs in human serum

Surface-enhanced Raman spectroscopy (SERS) is a powerful method in analytical chemistry, but its application in real-life medical settings has been limited due to technical challenges. In this work, we introduce an innovative approach that is meant to advance the automation of microfluidics SERS to improve reproducibility and label-free quantification of two widely used therapeutic drugs, methotrexate (MTX) and lamotrigine (LTG), in human serum. Our methodology involves a miniaturized solid-phase extraction (μ-SPE) method coupled to a centrifugal microfluidics disc with incorporated SERS substrates (CD-SERS). The CD-SERS platform enables simultaneous controlled sample wetting and accurate SERS mapping. Together with the assay we implemented a machine learning method based on Partial Least Squares Regression (PLSR) for robust data analysis and drug quantification. The results indicate that combining μ-SPE with CD-SERS (μ-SPE to CD-SERS) led to a substantial improvement in the signal-to-noise ratio compared to combining CD-SERS with ultrafiltration or protein precipitation. The PLSR model enabled us to obtain the limit of detection and quantification for MTX as 2.90 and 8.92 μM, respectively, and for LTG as 10.76 and 32.29 μM. We also validated our μ-SPE to CD-SERS method for MTX against HPLC and immunoassay (p-value <0.05), using patient samples undergoing MTX therapy. In addition, we achieved a satisfactory recovery rate (80%) for LTG when quantifying it in patient samples. Our results show the potential of this newly developed approach as a strategy for therapeutic drugs in point-of-care clinical settings and highlight the benefits of automating label-free SERS assays.

Preparation of carboxymethyl cellulose membrane flexible SERS substrate and its application in the detection of metabolites and pH in urine

Uric acid, urea, and other metabolites in urine after exercise often reflect chronic injury syndrome in athletes. However, traditional urine detection methods have issues such as high costs and low detection sensitivity. SERS can rapidly, continuously, and sensitively monitor metabolites in human urine. In this research, a combined SERS substrate (CMBCM@Ag NPs@PGA) was developed based on the carboxymethyl modification of the bacterial cellulose membrane (BCM) surface. The numerous carboxyl groups on the CMBCM surface made it easier for silver ions to be adsorbed, leading to their conversion into silver nanoparticles (Ag NPs) when a reducing agent was introduced. This process allowed the nanoparticles to firmly adhere to the CMBCM surface, forming a uniform and stable "hot spot." "The CMBCM@Ag NPs@PGA substrate maintains excellent stability and sensitivity in the assay." It can detect very small amounts of urea and uric acid in urine with high sensitivity, with LOD of 1.05 μM for urea and 0.0075 μM for uric acid. Additionally, it exhibits good stability, antibacterial properties, and cell compatibility. In addition, the substrate can be used as a sensor to monitor pH in real-time. This expands the use of cellulose in flexible SERS sensing and detecting human exercise metabolic health.

Development of a paper-based transcription aptasensor for convenient urinary uric acid self-testing

The abnormal uric acid (UA) level in urine can serve as warning signals of many diseases, such as gout and metabolic cardiovascular diseases. The current methods for detecting UA face limitations of instrument dependence and the requirement for non-invasiveness, making it challenging to fulfill the need for home-based application. In this study, we designed an aptasensor that combined UA-specific transcriptional regulation and a fluorescent RNA aptamer for convenient urinary UA testing. The concentration of UA can be translated into the intensity of fluorescent signals. The aptasensor showed higher sensitivity and more robust anti-interference performance. UA levels in the urine of different volunteers could be accurately tested using this method. In addition, a paper-based aptasensor for UA self-testing was manufactured, in which the urinary UA levels could be determined using a smartphone-based colorimetric approach. This work not only demonstrates a new approach for the design of disease-associated aptasensor, but also offers promising ideas for home-based detection of UA.

SERS mapping combined with chemometrics, for accurate quantification of methotrexate from patient samples

Despite the technological development in Raman instrumentation that has democratized access to 2D sample scanning capabilities, most quantitative surface-enhanced Raman scattering (SERS) analyses are still performed by only acquiring a single or a few spectra per sample and performing univariate data analysis on those. This strategy can however reach its limit when analytes need to be detected and quantified in complex matrices. In that case, surface fouling and competition between the target analyte and interfering compounds can impair univariate SERS data analysis, underlining the need for a more in-depth data analysis strategy based on exploiting of full-spectrum information. In this paper, a multivariate data analysis strategy was developed, for analyzing SERS maps of methotrexate (MTX) from patient samples, including all steps from baseline correction, selection of wavelength, and the relevant pixels in the map (image threshold segmentation), as well as quantitative model construction based on partial-least squares regression. Among the different baseline correction methods evaluated, standard normal variable transformation and Savitzky-Golay smoothing proved to be more suitable, while the genetic algorithm wavelength screening method was able to screen out MTX-related SERS spectral regions more efficiently. Importantly, with the here-developed process, it was sufficient to use MTX-spiked commercial serum when building quantitative models, removing the need to work with MTX-spiked patient samples, and consequently enabling time- and resource-saving quantitative analyses. Besides, the developed multivariate data analysis approach showed superior performances compared with univariate analysis, with 30 % improved sensitivity (detection limit of 5.7 µM), 25 % higher reproducibility (average relative standard variation of 15.6 %), and 110 % better accuracy (average prediction error of -10.5 %).

Label-free SERS assay combined with multivariate spectral data analysis for lamotrigine quantification in human serum

Considering the need for a more time and cost-effective method for lamotrigine (LTG) detection in clinics we developed a fast and robust label-free assay based on surface-enhanced Raman scattering (SERS) for LTG quantification from human serum. The optimization and application of the developed assay is presented  showing the: (i) exploration of different methods for LTG separation from human serum; (ii) implementation of a molecular adsorption step on an ordered Au nanopillar SERS substrate; (iii) adaptation of a fast scanning of the SERS substrate, performed with a custom-built compact Raman spectrometer; and (iv) development of LTG quantification methods with univariate and multivariate spectral data analysis. Our results showed, for the first time, the SERS-based characterization of LTG and its label-free identification in human serum. We found that combining a miniaturized solid phase extraction, as sample pre-treatment with the SERS assay, and using a multivariate model is an optimal strategy for LTG quantification in human serum in a linear range from 9.5 to 75 μM, with LoD and LoQ of 3.2 μM and 9.5 μM, respectively, covering the suggested clinical therapeutic window. We also showed that the developed assay allowed for quantifying LTG from human serum in the presence of other drugs, thereby demonstrating the robustness of label-free SERS. The sensing approach and instrumentation can be further automated and integrated in devices that can advance the drug monitoring in real clinical settings.

Synthesis of a capillary surface-enhanced Raman scattering substrate integrating sampling and detection based on meniscus self-assembled technology

A method is proposed to fabricate a novel capillary surface-enhanced Raman scattering (SERS) substrate integrating sampling and detection based on meniscus evaporation self-assembled technology, named Meniscus@AgNPs@Capillary substrate. Ag nanoparticles (AgNPs) were arranged in the inner wall of the capillary through meniscus evaporation. The parameters which might affect the deposition of AgNPs during evaporation were investigated, including the evaporation temperature, self-assembly time, the ratio of silver sol to ethanol, and capillary length. The enhancement effect of SERS under different fabrication conditions was investigated using rhodamine 6G (R6G) as a Raman probe. Moreover, the optimal fabricated Meniscus@AgNPs@Capillary substrate was applied to the detection of several environmental pollutants such as polystyrene nanoplastics (PSNPs) and various antibiotics, with limits of detection (LOD) of 10 µg/L and 1 µg/L, respectively. The Meniscus@AgNPs@Capillary substrate presented the advantages of time and effort saving, high sensitivity, and on-site sampling and testing.

Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends

Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, and microbiology. Although SERS is often limited by the lack of selectivity in the analysis of samples with complex matrices, the use of multivariate statistics and mathematical tools has been demonstrated to be an efficient strategy to circumvent this issue. Importantly, since the rapid development of artificial intelligence has been promoting the implementation of a wide variety of advanced multivariate methods in SERS, a discussion about the extent of their synergy and possible standardization becomes necessary. This critical review comprises the principles, advantages, and limitations of coupling SERS with chemometrics and machine learning for both qualitative and quantitative analytical applications. Recent advances and trends in combining SERS with uncommonly used but powerful data analysis tools are also discussed. Finally, a section on benchmarking and tips for selecting the suitable chemometric/machine learning method is included. We believe this will help to move SERS from an alternative detection strategy to a general analytical technique for real-life applications.

3D plasmonic coral nanoarchitecture paper for label-free human urine sensing and deep learning-assisted cancer screening

Practical human biofluid sensing requires a sensor device to differentiate patients from the normal group with high sensitivity and specificity. Label-free molecular identification from human biofluids allows direct classification of abnormal samples, providing insights for disease diagnosis and finding of new biomarkers. Here, we introduce a label-free surface-enhanced Raman scattering sensor based on a three-dimensional plasmonic coral nanoarchitecture (3D-PCN), which has strong electromagnetic field enhancement through multiple hot spots. The 3D-PCN was synthesized on a paper substrate via direct one-step gold reduction, forming a coral-like nanoarchitecture with high absorption property for biofluids. This was fabricated as a urine test strip and then integrated with a handheld Raman system to develop an on-site urine diagnostic platform. The developed platform successfully classified the human prostate and pancreatic cancer urines in a label-free method supported by two types of deep learning networks, with high clinical sensitivity and specificity. Our technology has the potential to be utilized not only for urinary cancer diagnosis but also for various human biofluid sensing systems as a future point-of-care testing platform.

Review of Thin-Layer Chromatography Tandem with Surface-Enhanced Raman Spectroscopy for Detection of Analytes in Mixture Samples

In the real world, analytes usually exist in complex systems, and this makes direct detection by surface-enhanced Raman spectroscopy (SERS) difficult. Thin layer chromatography tandem with SERS (TLC-SERS) has many advantages in analysis such as separation effect, instant speed, simple process, and low cost. Therefore, the TLC-SERS has great potential for detecting analytes in mixtures without sample pretreatment. The review demonstrates TLC-SERS applications in diverse analytical relevant topics such as environmental pollutants, illegal additives, pesticide residues, toxic ingredients, biological molecules, and chemical substances. Important properties such as stationary phase, separation efficiency, and sensitivity are discussed. In addition, future perspectives for improving the efficiency of TLC-SERS in real sample detecting are outlined.

Methotrexate Detection in Serum at Clinically Relevant Levels with Electrochemically Assisted SERS on a Benchtop, Custom Built Raman Spectrometer

Therapeutic drug monitoring (TDM) is an essential clinical practice for optimizing drug dosing, thereby preventing adverse effects of drugs with a narrow therapeutic window, slow clearance, or high interperson pharmacokinetic variability. Monitoring methotrexate (MTX) during high-dose MTX (HD-MTX) therapy is necessary to avoid potentially fatal side effects caused by delayed elimination. Despite the efficacy of HD-MTX treatment, its clinical application in resource-limited settings is constrained due to the relatively high cost and time of analysis with conventional analysis methods. In this work, we developed (i) an electrochemically assisted surface-enhanced Raman spectroscopy (SERS) method for detecting MTX in human serum at a clinically relevant concentration range and (ii) a benchtop, Raman detection system with an integrated potentiostat, software, and data analysis unit that enables mapping of small areas of SERS substrates and quantitative SERS-based analysis. In the assay, by promoting electrostatic attraction between gold-coated nanopillar SERS substrates and MTX molecules in aqueous samples, a detection limit of 0.13 μM with a linear range of 0.43-2 μM was achieved in PBS. The implemented sample cleanup through gel filtration proved to be highly effective, resulting in a similar detection limit (0.55 μM) and linear range (1.81-5 μM) for both PBS and serum. The developed and optimized assay could also be used on the in-house built, Raman device. We showed that MTX detection can be carried out in less than 30 min with the Raman device, paving the way toward the TDM of MTX at the point-of-need and in resource-limited environments.

Dual-functional SERRS and fluorescent aptamer sensor for abscisic acid detection via charged gold nanorods

Abscisic acid (ABA) is a plant hormone, which plays an important role in plant growth, crop cultivation and modern agricultural engineering management. Accordingly, the detection of ABA content combined with new techniques and methods has become a more and more popular problem in the field of agricultural engineering. In this work, a SERRS and fluorescence dual-function sensor based on the fluorescence quenching and Raman enhancement properties of gold nanorods (AuNRs) was developed, and applied to the detection of plant hormone ABA. The dual-function reporter molecule Rhodamine isothiocyanate (RBITC) and complementary DNA (cDNA) were modified on AuNRs (AuNRs@RBITC@cDNA) as signal probes and aptamer modified magnetic nanoparticles (Fe3O4MNPs@Apt) as capture probes. Through the specific recognition of ABA aptamer and its complementary chains, an dual-function aptamer sensor based on SERRS and fluorescence was constructed. When ABA molecules were present in the detection system, the signal probes were detached from the capture probes due to the preferential binding between aptamer and ABA molecules. SERS signal of the reporter molecules appeared in the supernatant after magnetic separation, and it increased with the increase of ABA concentration. If the etching agent that can etch AuNRs was added to the supernatant, the AuNRs was etching disappeared, then the signal molecules fall off from the AuNRs, and the fluorescence signal intensity would recovered. The intensity of fluorescence signal also increased with the increase of ABA concentration. Thus, the quantitative relationship between ABA concentration and SERRS intensity and fluorescence intensity of signal molecules was established. The linear range of SERRS detection was 100 fM–0.1 nM, the detection limit was 38 fM; The linear range of fluorescence detection was 1 pM–100 nM, the detection limit is 0.33 p.m. The constructed dual-effect sensor was used in the recovery laboratory of real ABA samples, the recovery rate was up to 85–108%.

Microfluidics and surface-enhanced Raman spectroscopy, a win-win combination?

With the continuous development in nanoscience and nanotechnology, analytical techniques like surface-enhanced Raman spectroscopy (SERS) render structural and chemical information of a variety of analyte molecules in ultra-low concentration. Although this technique is making significant progress in various fields, the reproducibility of SERS measurements and sensitivity towards small molecules are still daunting challenges. In this regard, microfluidic surface-enhanced Raman spectroscopy (MF-SERS) is well on its way to join the toolbox of analytical chemists. This review article explains how MF-SERS is becoming a powerful tool in analytical chemistry. We critically present the developments in SERS substrates for microfluidic devices and how these substrates in microfluidic channels can improve the SERS sensitivity, reproducibility, and detection limit. We then introduce the building materials for microfluidic platforms and their types such as droplet, centrifugal, and digital microfluidics. Finally, we enumerate some challenges and future directions in microfluidic SERS. Overall, this article showcases the potential and versatility of microfluidic SERS in overcoming the inherent issues in the SERS technique and also discusses the advantage of adding SERS to the arsenal of microfluidics.

Quantification of Methotrexate in Human Serum Using Surface-Enhanced Raman Scattering-Toward Therapeutic Drug Monitoring

Therapeutic drug monitoring (TDM) can improve clinical care when using drugs with pharmacokinetic variability and a narrow therapeutic window. Rapid, reliable, and easy-to-use detection methods are required in order to decrease the time of analysis and can also enable TDM in resource-limited settings or even at bedside. Monitoring methotrexate (MTX), an anticancer drug, is critical since it is needed to follow the drug clearance rate and decide how to administer the rescue drug, leucovorin (LV), in order to avoid toxicity and even death. We show that with the optimized nanopillar-assisted separation (NPAS) method using surface-enhanced Raman scattering, we were able to measure MTX in PBS and serum in the linear range of 5-150 μM and confirmed that MTX detection can be carried out even in the presence of LV. Additionally, when NPAS was combined with centrifugal filtration, a quantification limit of 2.1 μM for MTX in human serum sample was achieved. The developed detection method enables fast detection (10 min) and quantification of MTX from human serum (>90% accuracy). Furthermore, we show the potential of the developed method for TDM, when quantifying MTX from clinical samples, collected from patients who are undergoing high-dose MTX therapy.

Detection of trace amounts of insoluble pharmaceuticals in water by extraction and SERS measurements in a microfluidic flow regime

Detection of trace amounts of poorly water-soluble pharmaceuticals or related (bio)solutions represents a key challenge in environment protection and clinical diagnostics. However, this task is complicated by low concentrations of pharmaceuticals, complex sample matrices, and sophisticated sample preparative routes. In this work, we present an alternative approach on the basis of an on-line flow extraction procedure and SERS measurements performed in a microfluidic regime. The advantages of our approach were demonstrated using ibuprofen (Ibu), which is considered as a common pharmaceutical contaminant in wastewater and should be monitored in various bioliquids. The extraction of Ibu from water to the dichloromethane phase was performed with an optimized microfluidic mixer architecture. As SERS tags, lipophilic functionalized gold multibranched nanoparticles (AuMs) were added to the organic phase. After microfluidic extraction, Ibu was captured by the functionalized AuM surface and recognized by on-line SERS measurements with up to 10-8 M detection limit. The main advantages of the proposed approach can be regarded as its simplicity, lack of need for preliminary sample preparation, high reliability, the absence of sample pretreatment, and low detection limits.

Recent progress of microfluidics in surface-enhanced Raman spectroscopic analysis

Surface-enhanced Raman spectroscopy is a significant analytical tool capable of fingerprint identification of molecule in a rapid and ultrasensitive manner. However, it is still hard to meet the requirements of practical sample analysis. The introduction of microfluidics can effectively enhance the performance of surface-enhanced Raman spectroscopy in complex sample analysis including reproducibility, selectivity, sensitivity, and speed. This review summarizes the recent progress of microfluidics in surface-enhanced Raman spectroscopic analysis through four combination approaches. First, microfluidic synthetic techniques offer uniform nano-/microparticle fabrication approaches for reproductive surface-enhanced Raman spectroscopic analysis. Second, the integration of microchip and surface-enhanced Raman spectroscopic substrate provides advanced devices for sensitive and efficient detection. Third, microfluidic sample preparations enable rapid separation and preconcentration of analyte prior to surface-enhanced Raman spectroscopic detection. Fourth, highly integrated microfluidic devices can be employed to realize multistep surface-enhanced Raman spectroscopic analysis containing material fabrication, sample preparation, and detection processes. Furthermore, the challenges and outlooks of the application of microfluidics in surface-enhanced Raman spectroscopic analysis are discussed.

Towards a point-of-care SERS sensor for biomedical and agri-food analysis applications: a review of recent advancements

The growing demand for reliable and robust methodology in bio-chemical sensing calls for the continuous advancement of sensor technologies. Over the last two decades, surface-enhanced Raman spectroscopy (SERS) has emerged as one of the most promising analytical techniques for sensitive and trace analysis or detection in biomedical and agri-food applications. SERS overcomes the inherent sensitivity limitation associated with Raman spectroscopy, which provides vibrational "fingerprint" spectra of molecules that makes it unique and versatile among other spectroscopy techniques. This paper comprehensively reviews the recent advancements of SERS for biomedical, food and agricultural applications over the last 6 years, and we envision that, in the near future, some of these platforms have the potential to be translated as a point-of-care and rapid sensor for real-life end-user applications. The merits and limitations of various SERS sensor designs are analysed and discussed based on critical features such as sensitivity, specificity, usability, repeatability and reproducibility. We conclude by highlighting the opportunities and challenges in the field while stressing the technological gaps to be addressed in realizing commercially viable point-of-care SERS sensors for practical biomedical and agri-food technological applications.

Lab-On-Capillary Platform for On-Site Quantitative SERS Analysis of Surface Contaminants Based on Au@4-MBA@Ag Core-Shell Nanorods

A portable and highly reproducible lab-on-capillary surface-enhanced Raman scattering (SERS) platform was developed using a specially designed homemade device for rapid on-site SERS measurement. In particular, this platform was composed of a capillary with a tiny orifice, which allows an effective and lossless sample extraction, resulting in high SERS performance. The capillary-based plasmonic substrate was prepared by compactly assembling Au@Ag core-shell nanorods (NRs) embedded with the 4-mercaptobenzoic acid (4-MBA) molecule as an internal standard onto the inner wall of a capillary tube. The fabrication process is facile and convenient with no requirement for complicated procedures. The exclusively prepared nanoparticles were able to significantly improve the signal consistency and overcome the limitations of reliable quantitative SERS analysis compared with conventional methods. Importantly, it was found that this capillary-based substrate with higher sensitivity was essentially attributed to more valid nanoparticles in the effective laser excitation region derived from the unique structure of the capillary. Furthermore, the applicability of the Au@4-MBA@Ag nanorod-decorated capillary for the quantitative identification of fungicides (malachite green and crystal violet) on the shell was demonstrated. As a result, this proposed lab-on-capillary sensor holds promising practical potential for rapid on-site analysis, especially for various contaminants on an uneven surface.

Nanosilicon-Based Composites for (Bio)sensing Applications: Current Status, Advantages, and Perspectives

This review highlights the application of different types of nanosilicon (nano-Si) materials and nano-Si-based composites for (bio)sensing applications. Different detection approaches and (bio)functionalization protocols were found for certain types of transducers suitable for the detection of biological compounds and gas molecules. The importance of the immobilization process that is responsible for biosensor performance (biomolecule adsorption, surface properties, surface functionalization, etc.) along with the interaction mechanism between biomolecules and nano-Si are disclosed. Current trends in the fabrication of nano-Si-based composites, basic gas detection mechanisms, and the advantages of nano-Si/metal nanoparticles for surface enhanced Raman spectroscopy (SERS)-based detection are proposed.

Determination of uric acid in synthetic urine by using electrochemical surface oxidation enhanced Raman scattering

In this work, a new and easy methodology to determine uric acid in relevant samples using Raman spectroelectrochemistry is presented. The spectroelectrochemistry experiment is based on the in-situ formation of a suitable substrate that enables the enhancement of the Raman signal of an analyte during the oxidation stage of a silver electrode. This phenomenon is known as electrochemical surface oxidation enhanced Raman scattering (EC-SOERS) and has proved to be useful in quantitative analysis using disposable screen printed electrodes. The successful combination of EC-SOERS with PARAFAC analysis allows the determination of uric acid in a relevant complex sample avoiding the use of standard addition method and without using a baseline correction, which simplifies the application of such methodology in routine analysis.