| Literature DB >> 32920444 |
Muhammad Abu Bakkar1, Haq Nawaz2, Muhammad Irfan Majeed3, Ammara Naseem1, Allah Ditta1, Nosheen Rashid4, Saqib Ali1, Jawad Bajwa5, Saba Bashir1, Shamsheer Ahmad1, Hamza Hyat1, Kareem Shah Bukhari1, Franck Bonnier6.
Abstract
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.Entities:
Keywords: Partial Least Squares Regression; Raman spectroscopy; Sitagliptin; Solid dosage forms
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Year: 2020 PMID: 32920444 DOI: 10.1016/j.saa.2020.118900
Source DB: PubMed Journal: Spectrochim Acta A Mol Biomol Spectrosc ISSN: 1386-1425 Impact factor: 4.098