Qualitative and quantitative analysis of therapeutic solutions using Raman and infrared spectroscopy

Rapid Identification and Quantification of Adulteration in Methyl Eugenol using Raman Spectroscopy Coupled with Multivariate Data Analysis

Identification of adulterants in commercial samples of methyl eugenol is necessary because it is a botanical insecticide, a tephritid male attractant lure that is used to attract and kill invasive pests such as oriental fruit flies and melon flies on crops. In this study, Raman spectroscopy was used to qualitatively and quantitatively assess commercial methyl eugenol along with adulterants. For this purpose, commercial methyl eugenol was adulterated with different concentrations of xylene. The Raman spectral features of methyl eugenol and xylene in liquid formulations were examined, and Raman peaks were identified as associated with the methyl eugenol and adulterant. Principal component analysis (PCA) and partial least-squares regression analysis (PLSR) have been used to qualitatively and quantitatively analyze the Raman spectral features. PCA was applied to differentiate Raman spectral data for various concentrations of methyl eugenol and xylene. Additionally, PLSR has been used to develop a predictive model to observe a quantitative relationship between various concentrations of adulterated methyl eugenol and their Raman spectral data sets. The root-mean-square errors of calibration and prediction were calculated using this model, and the results were found to be 1.90 and 3.86, respectively. The goodness of fit of the PLSR model is found to be 0.99. The proposed approach showed excellent potential for the rapid, quantitative detection of adulterants in methyl eugenol, and it may be applied to the analysis of a range of pesticide products.

Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy

Raman spectroscopy is a well-established technique for the molecular characterisation of samples and does not require extensive pre-analytical processing for complex cosmetic products. As an illustration of its potential, this study investigates the quantitative performance of Raman spectroscopy coupled with partial least squares regression (PLSR) for the analysis of Alginate nanoencapsulated Piperonyl Esters (ANC-PE) incorporated into a hydrogel. A total of 96 ANC-PE samples covering a 0.4% w/w-8.3% w/w PE concentration range have been prepared and analysed. Despite the complex formulation of the sample, the spectral features of the PE can be detected and used to quantify the concentrations. Using a leave-K-out cross-validation approach, samples were divided into a training set (n = 64) and a test set, samples that were previously unknown to the PLSR model (n = 32). The root mean square error of cross-validation (RMSECV) and prediction (RMSEP) was evaluated to be 0.142% (w/w PE) and 0.148% (w/w PE), respectively. The accuracy of the prediction model was further evaluated by the percent relative error calculated from the predicted concentration compared to the true value, yielding values of 3.58% for the training set and 3.67% for the test set. The outcome of the analysis demonstrated the analytical power of Raman to obtain label-free, non-destructive quantification of the active cosmetic ingredient, presently PE, in complex formulations, holding promise for future analytical quality control (AQC) applications in the cosmetics industry with rapid and consumable-free analysis.

Comparison of Vibrational Spectroscopic Techniques for Quantification of Water in Natural Deep Eutectic Solvents

Vibrational spectroscopic techniques, i.e., attenuated total reflectance infrared (ATR-IR), near infrared spectroscopy (NIRS) and Raman spectroscopy (RS), coupled with Partial Least Squares Regression (PLSR), were evaluated as cost-effective label-free and reagent-free tools to monitor water content in Levulinic Acid/L-Proline (LALP) (2:1, mol/mol) Natural Deep Eutectic Solvent (NADES). ATR-IR delivered the best outcome of Root Mean Squared Error (RMSE) of Cross-Validation (CV) = 0.27% added water concentration, RMSE of Prediction (P) = 0.27% added water concentration and mean % relative error = 2.59%. Two NIRS instruments (benchtop and handheld) were also compared during the study, respectively yielding RMSECV = 0.35% added water concentration, RMSEP = 0.56% added water concentration and mean % relative error = 5.13% added water concentration, and RMECV = 0.36% added water concentration, RMSEP = 0.68% added water concentration and mean % relative error = 6.23%. RS analysis performed in quartz cuvettes enabled accurate water quantification with RMECV = 0.43% added water concentration, RMSEP = 0.67% added water concentration and mean % relative error = 6.75%. While the vibrational spectroscopic techniques studied have shown high performance in relation to reliable determination of water concentration, their accuracy is most likely related to their sensitivity to detect the LALP compounds in the NADES. For instance, whereas ATR-IR spectra display strong features from water, Levulinic Acid and L-Proline that contribute to the PLSR predictive models constructed, NIRS and RS spectra are respectively dominated by either water or LALP compounds, representing partial molecular information and moderate accuracy compared to ATR-IR. However, while ATR-IR instruments are common in chemistry and physics laboratories, making the technique readily transferable to water quantification in NADES, Raman spectroscopy offers promising potential for future development for in situ, sample withdrawal-free analysis for high throughput and online monitoring.

Quantification of clinical mAb solutions using Raman spectroscopy: Macroscopic vs microscopic analysis

Raman Spectroscopy is well emerged in the field of Analytical Quality Control (AQC) as a rapid and cost-effective technique useful in many applications. The advantage of Raman spectroscopy is the non-invasiveness of measurements that enablesto analyse samples directly in its container. In this study, the potential of Raman spectroscopy was investigated for analysis of clinical preparations of mAbs. Three commercial formulations of monoclonal antibodies (mAbs) Avastin®, Ontruzant® and Tecentriq® corresponding to Bevacizumab (BVC), Trastuzumab (TRS) and Atezolizumab (ATZ) respectively, were analysed in quartz cuvette in macroscopic analysis and through the wall of perfusion bags in microscopic analysis. The spectra have been compared to those of excipients (trehalose and sucrose) and of γ-Globulin, in order to investigate the origin of Raman bands. As expected, Raman spectra were a combination of bands from monoclonal antibodies and correspoding excipients found in formulas. For quantitative analysis of the solutions, models have been constructed using Partial Least Square Regression (PLSR) with Leave K-Out Cross Validation (LKOCV). The quantification performance was comparable for both macroscopic and microscopic analysis, in terms of error and linearity. The results are thus promising for future AQC in situ, in perfusion bags.

The Mechanism of Dynamic Interaction between Doxorubicin and Calf Thymus DNA at the Single-Molecule Level Based on Confocal Raman Spectroscopy

It is of great fundamental significance and practical application to understand the binding sites and dynamic process of the interaction between doxorubicin (DOX) and DNA molecules. Based on the Confocal Raman spectroscopy, the interaction between DOX and calf thymus DNA has been systemically investigated, and some meaningful findings have been found. DOX molecules can not only interact with all four bases of DNA molecules, i.e., adenine, thymine, cytosine, guanine, and phosphate, but also affect the DNA conformation. Meanwhile, the binding site of DOX and its derivatives such as daunorubicin and epirubicin is certain. Furthermore, the interaction between DOX and DNA molecules is a dynamic process since the intensities of each characteristic peaks of the base, e.g., adenine, cytosine, and phosphate, are all regularly changed with the interaction time. Finally, a dynamic mechanism model of the interaction between DOX and DNA molecules is proposed; that is, there are two kinds of interaction between DOX and DNA molecules: DOX-DNA acts to form a complex, and DOX-DOX acts to form a multimer. The two effects are competitive, as the former compresses DNA molecules, and the latter decompresses these DNA molecules. This work is helpful for accurately understanding and developing new drugs and pathways to improve and treat DOX-induced cytotoxicity and cardiotoxicity.

Surface-enhanced Raman spectroscopic analysis of the centrifugally filtered blood serum samples of the hepatitis C patients

BACKGROUND

Previously Raman spectroscopy technique is a use to analyze non-invasive disease related to body fluids.

OBJECTIVES

For the qualitative and quantitative analysis of HCV serum samples surface-enhanced Raman spectroscopy (SERS) based method is developed.

METHOD

Surface-enhanced Raman spectroscopy (SERS) technique is employed for analysis of filtrate portions of blood serum samples of hepatitis C virus (HCV) infected patients and healthy ones by using 50 kDa centrifugal filter device. The filtrate portions of the serum obtained in this way contain proteins smaller than 50 kDa and removal of bigger size protein which allows to acquire SERS spectral features of smaller proteins more effectively which are probably associated with Hepatitis C infection. Moreover, SERS spectral features of the filtrates of different level of viral load including low, medium and high viral loads are compared with SERS spectral features of the filtrate portions of healthy/control serum samples. SERS spectral data sets of different samples are further analyzed by using multivariate data analysis techniques such as principal component analysis (PCA) and partial least square regression (PLSR). Some SERS spectral features are solely observed in the filtrate portions of the serum samples of hepatitis C and their intensities are increased as the level of viral load increases and might be used for HCV diagnosis.

RESULTS

PCA was found helpful for differentiation of SERS spectral data sets of filtrate portions of the serum samples of hepatitis C and healthy persons. The PLSR model helped for the quantification of viral loads in the unknown serum samples with 99 % accuracy.

Monitoring the water content in NADES extracts from spirulina biomass by means of ATR-IR spectroscopy

Attenuated total reflectance-infrared spectroscopy (ATR-IR) coupled with partial least squares regression (PLSR) was evaluated as a rapid, label free and cost-effective tool to quantify water content in extracts obtained from spirulina wet biomass using a glucose glycerol natural deep eutectic solvent (NADES). NADESs are green, renewable and biodegradable solvents with unique properties outcompeting existing organic solvents, for instance, for plant or biomass extraction. The properties of NADESs depend critically on their water concentration, and therefore, it is essential to develop methods to monitor it, to ensure optimal extraction efficiency and experimental repeatability to achieve a better standardization of extraction protocols. First, Karl Fischer titration was performed on a set of 20 NADES extracts in order to obtain reference water concentrations. Secondly, ATR-IR spectra were collected and subjected to datamining to construct PLSR predictive models. An R² value of 0.9996, a mean root mean square error of cross validation of 0.136% w/w and a root mean square error of prediction of 0.130% w/w highlight the feasibility and reliability to perform quantitative analysis using ATR-IR. Moreover, the mean relative error percentage achieved, ∼0.5%, confirms the high accuracy of water concentration determination in NADES extracts. This work demonstrates that powerful alternatives are available to provide more environmentally responsible analytical protocols. ATR-IR spectroscopy applied to NADES extracts does not require any sample preparation, reagents or solvents and has minimal requirements for single use consumables. The technique is consistent with current concerns to develop greener chemistry, especially in the field of extraction of natural compounds from plants which currently represents a major focus of interest in both research and industry.

Quantitative analysis of solid dosage forms of Losartan potassium by Raman spectroscopy

Raman spectroscopy is an outstanding analytical tool increasingly utilized in the pharmaceutical field for the solid-state pharmaceutical drug analysis. In current study, the potential of Raman spectroscopy has been investigated for qualitative and quantitative analysis of solid dosage form of Losartan potassium. For this purpose, different solid dosage forms/concentrations of losartan potassium were prepared to compensate the commercially available pharmaceutical drug formulations and their Raman spectral data showed a gradual change in the specific Raman spectral features associated with the active pharmaceutical ingredient (API) of Losartan potassium as a function of change in the concentration. The Raman spectral data was analyzed by using Principal Component Analysis (PCA) for the classification of different spectral data sets of different concentrations of drug. Moreover, partial least square regression (PLSR) analysis was performed for monitoring the quantitative relation among different concentrations of Losartan potassium API and spectral data by constructing a predictive model. From the model, the value of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were observed to be 0.38 and 2.98 respectively and the value of goodness of fit was found to be 0.99. Furthermore, the quantity of unknown/blind sample of Losartan potassium formulation was also estimated by using PLSR model. From these results, it is demonstrated that Raman spectroscopy can be considered to be used for quick and reliable quantitative analysis of pharmaceutical solids.

Influence of lipophilicity of anthracyclines on the interactions with cholesterol in the model cell membranes - Langmuir monolayer and SEIRAS studies

The interactions of anthracyclines with biological membranes strongly depend on the drug lipophilicity, which might also determine the specific affinity to cholesterol molecules. Therefore, in this work we show the studies concerning the effect of two selected anthracyclines, daunorubicin (DNR) and idarubicin (IDA) on simple models of healthy (DMPC:Chol 7:3) and cancer cells membranes with increased level of cholesterol (DMPC:Chol 3:7) as well as pure cholesterol monolayers prepared at the air-water interface and supported on gold surface. It has been shown that more lipophilic IDA is able to penetrate cholesterol monolayers more effectively than DNR due to the formation of IDA-cholesterol arrangements at the interface, as proved by the thermodynamic analysis of compression-expansion cycles. The increased interactions of IDA were also confirmed by the time measurements of pre-compressed monolayers exposed to drug solutions as well as grazing incidence X-ray diffraction studies demonstrating differences in the 2D organization of cholesterol monolayers. Langmuir studies of mixed DMPC:Chol membranes revealed the reorganization of molecules in the cancer cell models at the air-water interface at higher surface pressures due to the removal of DNR, while increased affinity of IDA towards cholesterol allowed this drug to penetrate the layer more efficiently without its removal. The SEIRAS spectra obtained for supported DMPC:Chol bilayers proved that IDA locates both in the ester group and in the acyl chain region of the bilayer, while DNR does not penetrate the membranes as deeply as IDA. The increased penetration of the mixed phospholipid layers by idarubicin might be attributed to the higher lipophilicity caused by the lack of methoxy group and resulting in a specific affinity towards cholesterol.

Epirubicin: Biological Properties, Analytical Methods, and Drug Delivery Nanosystems

Epirubicin (EPI) is a chemotherapeutic agent belonging to the anthracycline drug class indicated for treating several tumors. It acts by suppressing the DNA and RNA synthesis by intercalating between their base pair. However, several side effects are associated with this therapy, including cardiotoxicity and myelosuppression. Therefore, EPI delivery in nanosystems has been an interesting strategy to overcome these limitations and improve the safety and efficacy of EPI. Thus, analytical methods have been used to understand and characterize these nanosystems, including spectrophotometric, spectrofluorimetric, and chromatography. Spectrophotometric and spectrofluorimetric methods have been used to quantify EPI in less complex matrices due to their efficiency, low cost, and green chemistry character. By contrast, high-performance liquid chromatography is a suitable method for detecting EPI in more complex matrices (e.g., plasm and urine) owing to its high sensitivity. This review summarizes physicochemical and pharmacokinetic properties of EPI, its application in drug delivery nanosystems, and the analytical methods employed in its quantification in different matrices, including blood, plasm, urine, and drug delivery nanosystems.

Surface-enhanced Raman spectroscopy for analysis of PCR products of viral RNA of hepatitis C patients

In the current study, for a qualitative and quantitative study of Polymerase Chain Reaction (PCR) products of viral RNA of Hepatitis C virus (HCV) infection, surface-enhanced Raman spectroscopy (SERS) methodology has been developed. SERS was used to identify the spectral features associated with the PCR products of viral RNA of Hepatitis C in various samples of HCV-infected patients with predetermined viral loads. The measurements for SERS were performed on 30 samples of PCR products, which included three PCR products of RNA of healthy individuals, six negative controls, and twenty-one HCV positive samples of varying viral loads (VLs) using Silver nanoparticles (Ag NPs) as a SERS substrates. Additionally, on SERS spectral data, the multivariate data analysis methods including Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR) were also carried out which help to illustrate the diagnostic capabilities of this method. The PLSR model is designed to predict HCV viral loads based on biochemical changes observed as SERS spectral features which can be associated directly with HCV RNA. Several SERS characteristic features are observed in the RNA of HCV which are not detected in the spectra of healthy RNA/controls. PCA is found helpful to differentiate the SERS spectral data sets of HCV RNA samples from healthy and negative controls. The PLSR model is found to be 99% accurate in predicting VLs of HCV RNA samples of unknown samples based on SERS spectral changes associated with the Hepatitis C development.

Analysis of IV Drugs in the Hospital Workflow by Raman Spectroscopy: The Case of Piperacillin and Tazobactam

Medical errors associated with IV preparation and administration procedures in a hospital workflow can even cost human lives due to the direct effect they have on patients. A large number of such incidents, which have been reported in bibliography up to date, indicate the urgent need for their prevention. This study aims at proposing an analytical methodology for identifying and quantifying IV drugs before their administration, which has the potential to be fully harmonized with clinical practices. More specifically, it reports on the analysis of a piperacillin (PIP) and tazobactam (TAZ) IV formulation, using Raman spectroscopy. The simultaneous analysis of the two APIs in the same formulation was performed in three stages: before reconstitution in the form of powder without removing the substance out of the commercial glass bottle (non-invasively), directly after reconstitution in the same way, and just before administration, either the liquid drug is placed in the infusion set (on-line analysis) or a minimal amount of it is transferred from the IV bag to a Raman optic cell (at-line analysis). Except for the successful identification of the APIs in all cases, their quantification was also achieved through calibration curves with correlation coefficients ranging from 0.953 to 0.999 for PIP and from 0.965 to 0.997 for TAZ. In any case, the whole procedure does not need more than 10 min to be completed. The current methodology, based on Raman spectroscopy, outweighs other spectroscopic (UV/Vis, FT-IR/ATR) or chromatographic (HPLC, UHPLC) protocols, already applied, which are invasive, costly, time-consuming, not environmentally friendly, and require specialized staff and more complex sample preparation procedures, thus exposing the staff to hazardous materials, especially in cases of cytotoxic drugs. Such an approach has the potential to bridge the gap between experimental setup and clinical implementation through exploitation of already developed handheld devices, along with the presence of digital spectral libraries.

In situ Analytical Quality Control of chemotherapeutic solutions in infusion bags by Raman spectroscopy

Analytical Quality Control (AQC) in centralised preparation units of oncology centers is a common procedure relying on the identification and quantification of the prepared chemotherapeutic solutions for safe intravenous administration to patients. Although the use of Raman spectroscopy for AQC has gained much interest, in most applications it remains coupled to a flow injection analyser (FIA) requiring withdrawal of the solution for analysis. In addition to current needs for more rapid and cost-effective analysis, the risk of exposure of clinical staff to the toxic molecules during daily handling is a serious concern to address. Raman spectroscopic analysis, for instance by Confocal Raman Microscopy (CRM), could enable direct analysis (non-invasive) for AQC directly in infusion bags. In this study, 3 anticancer drugs, methotrexate (MTX), 5-fluorouracil (5-FU) and gemcitabine (GEM) have been selected to highlight the potential of CRM for withdrawal free analysis. Solutions corresponding to the clinical range of each drug were prepared in 5% glucose and data was collected from infusion bags placed under the Raman microscope. Firstly, 100% discrimination has been obtained by Partial Least Squares Discriminant Analysis (PLS-DA) confirming that the identification of drugs can be performed. Secondly, using Partial Least Squares Regression (PLSR), quantitative analysis was performed with mean % error of predicted concentrations of respectively 3.31%, 5.54% and 8.60% for MTX, 5-FU and GEM. These results are in accordance with the 15% acceptance criteria used for the current clinical standard technique, FIA, and the Limits of Detection for all drugs were determined to be substantially lower than the administered range, thus highlighting the potential of confocal Raman spectroscopy for direct analysis of chemotherapeutic solutions.

Comparison of Raman and attenuated total reflectance (ATR) infrared spectroscopy for water quantification in natural deep eutectic solvent

Natural deep eutectic solvents (NADES) are ionic solutions, of great interest for extraction from biomass, biocatalysis, and nanoparticle synthesis. They are easily synthesised and eco-friendly, have low volatility and high dissolution power, and are biodegradable. However, water content in NADES is a critical parameter, affecting their optimal use and extraction efficiency. Vibrational spectroscopic techniques are rapid, label-free, non-destructive, non-invasive, and cost-effective analytical tools that can probe the molecular composition of samples. A direct comparison between a previous study using attenuated total reflectance infrared (ATR-IR) spectroscopy for water quantification in NADES and the same investigation performed with Raman spectroscopy is presently reported. Three NADES systems, namely betaine-glycerol (BG), choline chloride-glycerol (CCG), and glucose-glycerol (GG), containing a range of water concentrations between 0% (w/w) and 40% (w/w), have been analysed with Raman spectroscopy coupled to partial least squares regression multivariate analysis. The values of root mean square error of cross-validation (RMSECV) obtained from analysis performed on the pre-processed spectra over the full spectral range (150-3750 cm^-1) are respectively 0.2966% (w/w), 0.4703% (w/w), and 0.2351% (w/w) for BG, GG, and CCG. While the direct comparison to previous ATR-IR results shows essentially similar outcomes for BG, the RMSECV is 33.14% lower and 65.84% lower for CG and CCG. Furthermore, mean relative errors obtained with Raman spectroscopy, and calculated from a set of samples used as independent samples, were 1.452% (w/w), 1.175% (w/w), and 1.188% (w/w). Ultimately, Raman spectroscopy delivered performances for quantification of water in NADES with similar accuracy to ATR-IR. The present demonstration clearly highlights the potential of Raman spectroscopy to support the development of new analytical protocols in the field of green chemistry.

Chemometric Analysis of UV-Visible Spectral Fingerprints for the Discrimination and Quantification of Clinical Anthracycline Drug Preparation Used in Oncology

In clinical treatment, the analytical quality assessment of the delivery of chemotherapeutic preparations is required to guarantee the patient's safety regarding the dose and most importantly the appropriate anticancer drug. On its own, the development of rapid analytical methods allowing both qualitative and quantitative control of the formulation of prepared solutions could significantly enhance the hospital's workflow, reducing costs, and potentially providing optimal patient care. UV-visible spectroscopy is a nondestructive, fast, and economical technique for molecular characterization of samples. A discrimination and quantification study of three chemotherapeutic drugs doxorubicin, daunorubicin, and epirubicin was conducted, using clinically relevant concentration ranges prepared in 0.9% NaCl solutions. The application of the partial least square discriminant analysis PLS-DA method on the UV-visible spectral data shows a perfect discrimination of the three drugs with a sensitivity and specificity of 100%. The use of partial least square regression PLS shows high quantification performance of these molecules in solution represented by the low value of root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSCECV) on the one hand and the high value of R-square on the other hand. This study demonstrated the viability of UV-visible fingerprinting (routine approach) coupled with chemometric tools for the classification and quantification of chemotherapeutic drugs during clinical preparation.

How to draw the line - Raman spectroscopy as a tool for the assessment of biomedicines

Biomedicines are complex biochemical formulations with multiple components that require extensive quality control during manufacturing and in subsequent batch testing. A proof-of-concept study has shown that an application of Raman spectroscopy can be beneficial for a classification of vaccines. However, the complexity of biomedicines introduces new challenges to spectroscopic methodology that require advanced experimental protocols. We further show the impact of analytical protocols on vaccine classification using R as an Open Source data analysis platform. In conclusion, we advocate for standardized and transparent experimental and analytical procedures and discuss current findings and open challenges.

Comparison of Surface-Enhanced Raman Scattering Properties of Serum and Urine for the Detection of Chronic Kidney Disease in Patients

Chronic kidney disease (CKD) affects more than 10% of the global population and is associated with significant morbidity and mortality. In most cases, this disease is developed silently, and it can progress to the end-stage renal failure. Therefore, early detection becomes critical for initiating effective interventions. Routine diagnosis of CKD requires both blood test and urinalyses in a clinical laboratory, which are time-consuming and have low sensitivity and specificity. Surface-enhanced Raman scattering (SERS) is an emerging method for rapidly assessing kidney function or injury. This study was designed to compare the differences between the SERS properties of the serum and urine for easy and simple detection of CKD. Enrolled for this study were 126 CKD patients (Stages 2-5) and 97 healthy individuals. SERS spectra of both the serum and urine samples were acquired using a Raman spectrometer (785 nm excitation). The correlation of chemical parameters of kidney function with the spectra was examined using prinicpal component analysis (PCA) combined with linear discriminant analysis (LDA) and partial least squares (PLS) analysis. Here, we showed that CKD was discriminated from non-CKD controls using PCA-LDA with a sensitivity of 74.6% and a specificity of 93.8% for the serum spectra, and 78.0% and 86.0 % for the urine spectra. The integration area under the receiver operating characteristic curve was 0.937 ± 0.015 (p < 0.0001) for the serum and 0.886 ± 0.025 (p < 0.0001) for the urine. The different stages of CKD were separated with the accuracy of 78.0% and 75.4% by the serum and urine spectra, respectively. PLS prediction (R²) of the serum spectra was 0.8540 for the serum urea (p < 0.001), 0.8536 for the serum creatinine (p < 0.001), 0.7500 for the estimated glomerular filtration rate (eGFR) (p < 0.001), whereas the prediction (R²) of urine spectra was 0.7335 for the urine urea (p < 0.001), 0.7901 for the urine creatinine (p < 0.001), 0.4644 for the eGFR (p < 0.001) and 0.6579 for the urine microalbumin (p < 0.001). In conclusion, the accuracy of associations between SERS findings of the serum and urine samples with clinical conclusions of CKD diagnosis in this limited number of patients is similar, suggesting that SERS may be used as a rapid and easy-to-use method for early screening of CKD, which however needs further evaluation in a large cohort study.

Raman spectroscopy for the qualitative and quantitative analysis of solid dosage forms of Sitagliptin

To demonstrate the potential of Raman spectroscopy for the qualitative and quantitative analysis of solid dosage pharmacological formulations, different concentrations of Sitagliptin, an Active Pharmaceutical Ingredient (API) currently prescribed as an anti-diabetic drug, are characterised. Increase of the API concentrations induces changes in the Raman spectral features specifically associated with the drug and excipients. Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR), were used for the qualitative and quantitative analysis of the spectral responses. A PLSR model is constructed which enables the prediction of different concentrations of drug in the complex excipient matrices. During the development of the prediction model, the Root Mean Square Error of Cross Validation (RMSECV) was found to be 0.36 mg and the variability explained by the model, according to the (R²) value, was found to be 0.99. Moreover, the concentration of the API in the unknown sample was determined. This concentration was predicted to be 64.28/180 mg (w/w), compared to the 65/180 mg (w/w). These findings demonstrate Raman spectroscopy coupled to PLSR analysis to be a reliable tool to verify Sitagliptin contents in the pharmaceutical samples based on calibration models prepared under laboratory conditions.

Surface enhanced Raman spectroscopy of RNA samples extracted from blood of hepatitis C patients for quantification of viral loads

BACKGROUND

Raman spectroscopy is a promising technique to analyze the body fluids for the purpose of non-invasive disease diagnosis.

OBJECTIVES

To develop a surface-enhanced Raman spectroscopy (SERS) based method for qualitative and quantitative analysis of HCV from blood samples.

METHODS

SERS was employed to characterize the Hepatitis C viral RNA extracted from different blood samples of hepatitis C virus (HCV) infected patients with predetermined viral loads in comparison with total RNA of healthy individuals. The SERS measurements were performed on 27 extracted RNA samples including low viral loads, medium viral loads, high viral loads and healthy/negative viral load samples. For this purpose, silver nanoparticles (Ag NPs) were used as SERS substrates. Furthermore, multivariate data analysis technique, Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR) were also performed on SERS spectral data.

RESULTS

The SERS spectral features due to biochemical changes in the extracted RNA samples associated with the increasing viral loads were established which could be employed for HCV diagnostic purpose. PCA was found helpful for the differentiation between Raman spectral data of RNA extracted from hepatitis infected and healthy blood samples. PLSR model is established for the determination of viral loads in HCV positive RNA samples with 99 % accuracy.

CONCLUSION

SERS can be employed for qualitative and quantitative analysis of HCV from blood samples.

FT-IR/ATR Solid Film Formation: Qualitative and Quantitative Analysis of a Piperacillin-Tazobactam Formulation

FT-IR/ATR analytical technique is one of the most applicable techniques worldwide. It is closely associated with easy-to-use equipment, rapid analysis, and reliable results. This study reports the simultaneous qualitative and quantitative analysis of two active pharmaceutical ingredients (APIs), of a piperacillin and tazobactam formulation using a film formation method. This method requires film formation on the ATR crystal, resulting from solvent evaporation of a small amount of liquid sample. Good contact between the film and the crystal led to the identification of both APIs, although tazobactam was of low content in the formulation mixture. The quantification of the APIs in the commercial mixture was also achieved, using a single calibration line with a correlation coefficient equal to 0.999, not only after film formation but also in the initial dry formulation before reconstitution. The present spectroscopic technique combined with the proposed relatively simple sample treatment outweighs chromatographic protocols already applied, which require specialized staff and are costly, time-consuming, and not environmentally friendly. Taking all the above into consideration, it turns out that such an approach has the potential to be used for off-line quality control procedures in manufacture or, in terms of portable equipment and automated software, anywhere for on-site analysis, even in a hospital workflow.

Understanding the discrimination and quantification of monoclonal antibodies preparations using Raman spectroscopy

The use of Raman spectroscopy for analytical quality control of anticancer drug preparations in clinical pharmaceutical dispensing units is increasing in popularity, notably supported by commercially available, purpose designed instruments. Although not legislatively compulsory, analytical methods are frequently used post-preparation to verify the accuracy of a preparation in terms of identity and quantity of the drug in solution. However, while the rapid, cost effective and label free analysis achieved with Raman spectroscopy is appealing, it is important to understand the molecular origin of the spectral contributions collected from the solution of actives and excipients, to evaluate the strength and limitation for the technique, which can be used to identify and quantify either the prescribed commercial formulation, and/or the active drug itself, in personalised solutions. In the current study, four commercial formulations, Erbitux®, Truxima®, Ontruzant® and Avastin® of monoclonal antibodies (mAbs), corresponding respectively to cetuximab, rituximab, trastuzumab and bevacizumab have been used to highlight the key role of excipients in discrimination and quantification of the formulations. It is demonstrated that protein based anticancer drugs such as mAbs have a relatively weak Raman response, while excipients such as glycine, trehalose or histidine contribute significantly to the spectra. Multivariate analysis (partial least square regression and partial least square discriminant analysis) further demonstrates that the signatures of the mAbs themselves are not prominent in mathematical models and that those of the excipients are solely responsible for the differentiation of formulation and accurate determination of concentrations. While Raman spectroscopy can successfully validate the conformity of mAbs intravenous infusion solutions, the basis for the analysis should be considered, and special caution should be given to excipient compositions in commercial formulations to ensure reliability and reproducibility of the analysis.