Comparative Study of Univariate Spectrophotometry and Multivariate Calibration for the Determination of Levamisole Hydrochloride and Closantel Sodium in a Binary Mixture

2016 ◽  
Vol 99 (4) ◽  
pp. 941-947
Author(s):  
Omar Abdel-Aziz ◽  
Emad M Hussien ◽  
Amira M El Kosasy ◽  
Neven Ahmed
Keyword(s):  
Binary Mixture ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
High Accuracy ◽  
Pharmaceutical Dosage Form ◽  
First Derivative ◽  
Accuracy And Precision ◽  
Mean Centering

Abstract Six simple, accurate, reproducible, and selective derivative spectrophotometric and chemometric methods have been developed and validated for the determination of levamisole HCl (Lev) either alone or in combination with closantel sodium (Clo) in the pharmaceutical dosage form. Lev was determined by first-derivative, first-derivative ratio, and mean-centering methods by measuring the peak amplitude at 220.8, 243.8, and 210.4 nm, respectively. The methods were linear over the concentration range 2.0–10.0 μg/mL Lev. The methods exhibited a high accuracy, with recovery data within ±1.9% and RSD <1.3% (n = 9) for the determination of Lev in the presence of Clo. Fortunately, Lev showed no significant UV absorbance at 370.6 nm, which allowed the determination of Clo over the concentration range 16.0–80.0 μg/mL using zero-order spectra, with a high precision (RSD <1.5%, n = 9). Furthermore, principal component regression and partial least-squares with optimized parameters were used for the determination of Lev in the presence of Clo. The recovery was within ±1%, with RSD <1.0% (n = 9) and root mean square error of prediction ≤1.0. The proposed methods were validated according to the International Conference on Harmonization guidelines. The proposed methods were used in the determination of Lev and Clo in a binary mixture and a pharmaceutical formulation, with high accuracy and precision.

Nondestructive NIR and NIT Determination of Protein, Fat, and Water in Plastic-Wrapped, Homogenized Meat

1992 ◽  
Vol 46 (11) ◽  
pp. 1685-1694 ◽  
Author(s):  
Tomas Isaksson ◽  
Charles E. Miller ◽  
Tormod Næs
Keyword(s):  
Diffuse Reflectance ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Errors ◽  
Optimal Test ◽  
Meat Samples ◽  
Water Contents

In this work, the abilities of near-infrared diffuse reflectance (NIR) and transmittance (NIT) spectroscopy to noninvasively determine the protein, fat, and water contents of plastic-wrapped homogenized meat are evaluated. One hundred homogenized beef samples, ranging from 1 to 23% fat, wrapped in polyamide/polyethylene laminates, were used. Results of multivariate calibration and prediction for protein, fat, and water contents are presented. The optimal test set prediction errors (root mean square error of prediction, RMSEP), obtained with the use of the principal component regression method with NIR data, were 0.45, 0.29 and 0.50 weight % for protein, fat, and water, respectively, for plastic-wrapped meat (compared to 0.40, 0.28 and 0.45 wt % for unwrapped meat). The optimal prediction errors for the NIT method were 0.31, 0.52 and 0.42 wt % for protein, fat, and water, respectively, for plastic-wrapped meat samples (compared to 0.27, 0.38, and 0.37 wt % for unwrapped meat). We can conclude that the addition of the laminate only slightly reduced the abilities of the NIR and NIT method to predict protein, fat, and water contents in homogenized meat.

scholarly journals Liquid Chromatographic and Spectrophotometric Determination of Diflucortolone Valerate and Isoconazole Nitrate in Creams

2011 ◽  
Vol 94 (1) ◽  
pp. 128-135 ◽  
Author(s):  
Elif Karacan ◽  
Mehmet Gokhan Çaġlayan ◽  
İsmail Murat Palabiyik ◽  
Feyyaz Onur
Keyword(s):  
Principal Component Regression ◽  
Principal Component ◽  
Derivative Spectrophotometry ◽  
Data Matrix ◽  
Concentration Data ◽  
Spectrophotometric Methods ◽  
First Derivative ◽  
First Derivative Spectrophotometry ◽  
Liquid Chromatographic

Abstract A new RP-LC method and two new spectrophotometric methods, principal component regression (PCR) and first derivative spectrophotometry, are proposed for simultaneous determination of diflucortolone valerate (DIF) and isoconazole nitrate (ISO) in cream formulations. An isocratic system consisting of an ACE® C18 column and a mobile phase composed of methanol–water (95+5, v/v) was used for the optimal chromatographic separation. In PCR, the concentration data matrix was prepared by using synthetic mixtures containing these drugs in methanol–water (3+1, v/v). The absorbance data matrix corresponding to the concentration data matrix was obtained by measuring the absorbances at 29 wavelengths in the range of 242–298 nm for DIF and ISO in the zero-order spectra of their combinations. In first derivative spectrophotometry, dA/dλ values were measured at 247.8 nm for DIF and at 240.2 nm for ISO in first derivative spectra of the solution of DIF and ISO in methanol–water (3+1, v/v). The linear ranges were 4.00–48.0 μg/mL for DIF and 50.0–400 μg/mL for ISO in the LC method, and 2.40–40.0 μg/mL for DIF and 60.0–260 μg/mL for ISO in the PCR and first derivative spectrophotometric methods. These methods were validated by analyzing synthetic mixtures. These three methods were successfully applied to two pharmaceutical cream preparations.

Spectrophotometric determination of mixtures of iron(III) and manganese(II) by complexation with 3-indolylacetohydroxamic acid and principal component regression multivariate calibration

The Analyst ◽  
1994 ◽  
Vol 119 (7) ◽  
pp. 1537-1540 ◽  
Author(s):  
Mercedes Jiménez Arrabal ◽  
Pablo Valiente González ◽  
Concepción Caro Gámez ◽  
Antonio Sánchez Misiego ◽  
Arsenio Muñoz de la Peña
Keyword(s):  
Spectrophotometric Determination ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component

scholarly journals Comparative Study of Novel Ratio Spectra and Isoabsorptive Point Based Spectrophotometric Methods: Application on a Binary Mixture of Ascorbic Acid and Rutin

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Hany W. Darwish ◽  
Ahmed H. Bakheit ◽  
Ibrahim A. Naguib
Keyword(s):  
Ascorbic Acid ◽  
Binary Mixture ◽  
High Performance ◽  
Pharmaceutical Tablets ◽  
Spectrophotometric Methods ◽  
First Derivative ◽  
Ratio Difference ◽  
Mean Centering ◽  
Assay Conditions

This paper presents novel methods for spectrophotometric determination of ascorbic acid (AA) in presence of rutin (RU) (coformulated drug) in their combined pharmaceutical formulation. The seven methods are ratio difference (RD), isoabsorptive_RD (Iso_RD), amplitude summation (A_Sum), isoabsorptive point, first derivative of the ratio spectra (1DD), mean centering (MCN), and ratio subtraction (RS). On the other hand, RU was determined directly by measuring the absorbance at 358 nm in addition to the two novel Iso_RD and A_Sum methods. The work introduced in this paper aims to compare these different methods, showing the advantages for each and making a comparison of analysis results. The calibration curve is linear over the concentration range of 4–50 μg/mL for AA and RU. The results show the high performance of proposed methods for the analysis of the binary mixture. The optimum assay conditions were established and the proposed methods were successfully applied for the assay of the two drugs in laboratory prepared mixtures and combined pharmaceutical tablets with excellent recoveries. No interference was observed from common pharmaceutical additives.

APPLICATION OF CHEMOMETRIC METHODS FOR DETERMINATION OF CLOTRIMAZOLE AND BECLOMETHASONE DIPROPIONATE IN PHARMACEUTICAL DOSAGE FORM

INDIAN DRUGS ◽  
2020 ◽  
Vol 57 (02) ◽  
pp. 45-50
Author(s):  
Umang Shah ◽  
Bhumika Desai ◽  
Vyomesh Nandrubarkar
Keyword(s):  
Beclomethasone Dipropionate ◽  
Principal Component Regression ◽  
Principal Component ◽  
Quality Parameters ◽  
Uv Spectra ◽  
Chemical Information ◽  
Chemometric Methods ◽  
Validation Data ◽  
Pharmaceutical Dosage Form

Chemometry is the use of mathematical and statistical methods to improve the understanding of chemical information and to correlate quality parameters or physical properties to analytical instrument data. In the present work, two chemometric methods, named as principal component regression (PCR) and (PLS) based on the use of spectrophotometric data, were developed for simultaneous determination of clotrimazole (CLO) and beclomethasone dipropionate (BE C) in bulk and cream form. The absorbance of zero order UV spectra of CLO and BE C in the range of 80-400 μg/mL and 2-10 μg/mL, respectively were recorded in the wavelength range 230-272 nm at 3 nm wavelength intervals. Twenty-five (25) mixed solutions were prepared for the chemometric calibration as training set and sixteen varied solutions were prepared as a validation set. The suitability of the models was decided based on the RMSECV, RMSEP and PRESS values of calibration and validation data. The % recovery study of both the methods was compared, and it was found near each other. The assay of CLO and BE C for both the methods was found to be in the range of 99.78 to 101.20%. Hence, the proposed methods can be used for simultaneous analysis of the mixture of the drugs, without chemical pre-treatment, with good speed of analysis.

scholarly journals Multivariate Validated Models for Simultaneous Determination of Ibuprofen and Famotidine in the Presence of Related Substances

2018 ◽  
Vol 101 (4) ◽  
pp. 1001-1007
Author(s):  
Eman S Elzanfaly ◽  
Hala E Zaazaa ◽  
Aya T Soudi ◽  
Maissa Y Salem
Keyword(s):  
Simultaneous Determination ◽  
Multivariate Calibration ◽  
Degradation Products ◽  
Principal Component Regression ◽  
Principal Component ◽  
Standard Addition ◽  
Spectrophotometric Methods ◽  
Related Substances ◽  
Calibration Methods

Abstract Two multivariate validated spectrophotometric methods, namely partial least-squares (PLS) and principal component regression (PCR), were developed and validated for the determination of ibuprofen and famotidine in presence of famotidine degradation products and ibuprofen impurity (4-isobutylacetophenone). A calibration set was prepared in which the two drugs together with the degradation products and impurity were modeled using a multilevel multifactor design. This calibration set was used to build the PLS and PCR models. The proposed models successfully predicted the concentrations of both drugs in validation samples, with low root mean square error of cross validation (RMSECV) percentage. The method was validated by the estimate of the figures of merit depending on the net analyte signal. The results of the two models showed that the simultaneous determination of both drugs could be performed in the concentration ranges of 100–500 µg/mL for ibuprofen and 5–25 µg/mL for famotidine. The proposed multivariate calibration methods were applied for the determination of ibuprofen and famotidine in their pharmaceutical formulation, and the results were verified by the standard addition technique.

Chemometrics-assisted spectrophotometric method for simultaneous estimation of antipsychotic drugs in biological fluid

2020 ◽  
Vol 16 ◽  
Author(s):  
Mojdeh Alibakhshi ◽  
Mahmoud Reza Sohrabi ◽  
Mehran Davallo
Keyword(s):  
Simultaneous Determination ◽  
Antipsychotic Drugs ◽  
Multivariate Calibration ◽  
Biological Fluid ◽  
Principal Component Regression ◽  
Reference Method ◽  
Principal Component ◽  
Simultaneous Estimation ◽  
Calibration Methods

Background: Haloperidol (HP) and Risperidone (RIS) are antipsychotic drugs and the simultaneous determination of these drugs is important. Estimation of HP and RIS alone or in combination with other drugs has been performed in a variety of ways. Objective: The aim of this paper was to propose a rapid, simple, accurate, and robust method for the simultaneous determination of HP and RIS using artificial neural networks (ANNs), partial least squares (PLS), and principal component regression (PCR) methods along with spectrophotometry technique. Methods: The simultaneous spectrophotometric determination of HP and RIS in synthetic mixtures and biological fluid was performed by applying ANNs containing feed forward backpropagation (FFBP) and radial basis function (RBF) networks as intelligent methods, as well as PLS, and principal component regression PCR as multivariate calibration methods. The Levenberg–Marquardt (LM), Scaled conjugate gradient (SCG), and Resilient Back-propagation (RP) algorithms with different layers and neurons were used in FFBP network and obtained results were compared with each other. Results: Among various algorithms of the FFBP network, the LM algorithm was selected as the best model with a lower mean square error (MSE). MSE of the RBF model was 1.46×10-25 and 1.62×10-23 for HP and RIS, respectively. On the other hand, the mean recovery of PLS and PCR was 99.91%, 100.01% and 98.60%, 101.90% for HP and RIS, respectively. Conclusion: The proposed models and high-performance liquid chromatography (HPLC) as a reference method were compared with each other by one-way analysis of variance (ANOVA) test at the 95 % confidence level for the urine sample. It was observed that the developed methods presented comparable results for the simultaneous determination of HP and RIS.

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