Quantitative analysis of solid dosage forms of cefixime using Raman spectroscopy

被引：25

作者：

Bajwa, Jawad ^{[1
]}

Nawaz, Haq ^{[2
]}

Majeed, Muhammad Irfan ^{[2
]}

Hussain, Abdullah Ijaz ^{[1
]}

Farooq, Sidra ^{[2
]}

Rashid, Nosheen ^{[3
]}

Abu Bakkar, Muhammad ^{[2
]}

Ahmad, Shamsheer ^{[2
]}

Hyat, Hamza ^{[2
]}

Bashir, Saba ^{[2
]}

Ali, Saqib ^{[2
]}

Kashif, Muhammad ^{[2
]}

机构：

[1] Govt Coll Univ, Dept Chem, Faisalabad, Pakistan

[2] Univ Agr Faisalabad, Dept Chem, Faisalabad, Pakistan

[3] Univ Cent Punjab, Dept Chem, Faisalabad Campus, Faisalabad, Pakistan

来源：

SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY | 2020年 / 238卷

关键词：

Cefixime; Solid dosage forms; Raman spectroscopy; PCA; PLSR; 8 CEPHALOSPORIN ANTIBIOTICS; SPECTROPHOTOMETRIC METHOD; MULTIVARIATE METHODS; HEPATITIS-C; SPECTRA; SERS; IDENTIFICATION; TRIHYDRATE; REGRESSION; HPLC;

D O I：

10.1016/j.saa.2020.118446

中图分类号：

O433 [光谱学];

学科分类号：

0703 ; 070302 ;

摘要：

Quantification of antibiotics is of significant importance because of their use in the prevention and treatment of different diseases. Cefixime (CEF) is a cephalosporin antibiotic that is used against bacterial infections. In the present study, Raman spectroscopy has been applied for the identification and quantification of Raman spectral features of cefixime with different concentrations of Active Pharmaceutical Ingredient (API) and excipients in solid dosage forms. The changes in Raman spectral features of API and excipients in the solid dosage forms of cefixime were studied and Raman peaks were assigned based on the literature. Multivariate data analysis techniques including the Principal Component Analysis (PCA) and Partial Least Squares Regression analysis (PLSR) have been performed for the qualitative and quantitative analysis of solid dosage forms of cefixime. PCA was found helpful in differentiating all the Raman spectral data associated with the different solid dosage forms of cefixime. The coefficient of determination (R-2), mean absolute error (MAE), and mean relative error (MRE) for the calibration data-set were 0.99, 0.72, and 0.01 respectively and for the validation data-set were 0.99, 3.15, and 0.02 respectively, that shows the performance of the model. The root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were found to be 0.56 mg and 3.13 mg respectively. (C) 2020 Elsevier B.V. All rights reserved.

引用

页数：7

共 52 条

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