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Raman spectroscopy for the quantitative analysis of Lornoxicam in solid dosage forms
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AbstractIn this study, Raman spectroscopy is used to characterize different formulations of active pharmaceutical ingredient (API) of Lornoxicam, a nonsteroidal anti‐inflammatory drug for qualitative and quantitative analyses. The Raman spectral characteristic peaks associated with API and excipients are identified, which increase or decrease as their concentrations change in different formulations. The spectral response was analyzed qualitatively and quantitatively by using chemometrics tools such as principal component analysis (PCA) model and partial least squares regression (PLSR) analysis model, respectively. The characteristic Raman spectral features associated with the different formulations of API of Lornoxicam were used to differentiate different groups of Raman spectral data using PCA. By using PLSR model, root mean square error of cross validation (RMSECV) was found to be 0.76 mg during the development of prediction model and according to the (R2) value, the goodness of the model was found to be 0.99. Furthermore, the concentration of API in the blind sample was measured. In comparison to the 15/35 mg (w/w), this concentration was projected to be 14.13/35 mg (w/w). Raman spectroscopy along with PCA and PLSR analyses is a useful tool for determining the concentration of Lornoxicam in pharmaceutical samples, both qualitatively and quantitatively.
Title: Raman spectroscopy for the quantitative analysis of Lornoxicam in solid dosage forms
Description:
AbstractIn this study, Raman spectroscopy is used to characterize different formulations of active pharmaceutical ingredient (API) of Lornoxicam, a nonsteroidal anti‐inflammatory drug for qualitative and quantitative analyses.
The Raman spectral characteristic peaks associated with API and excipients are identified, which increase or decrease as their concentrations change in different formulations.
The spectral response was analyzed qualitatively and quantitatively by using chemometrics tools such as principal component analysis (PCA) model and partial least squares regression (PLSR) analysis model, respectively.
The characteristic Raman spectral features associated with the different formulations of API of Lornoxicam were used to differentiate different groups of Raman spectral data using PCA.
By using PLSR model, root mean square error of cross validation (RMSECV) was found to be 0.
76 mg during the development of prediction model and according to the (R2) value, the goodness of the model was found to be 0.
99.
Furthermore, the concentration of API in the blind sample was measured.
In comparison to the 15/35 mg (w/w), this concentration was projected to be 14.
13/35 mg (w/w).
Raman spectroscopy along with PCA and PLSR analyses is a useful tool for determining the concentration of Lornoxicam in pharmaceutical samples, both qualitatively and quantitatively.
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