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

BACKGROUND: Raman spectroscopy is able to analyze non-invasively, 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.

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.