scholarly journals Eco-Friendly Pharmaceutical Analysis of Multicomponent Drugs Coformulated in Different Dosage Forms Using Multivariate Curve Resolution and Partial Least Squares: A Comparative Study

2019 ◽  
Vol 102 (2) ◽  
pp. 465-472 ◽  
Author(s):  
Ahmed Mostafa ◽  
Heba Shaaban ◽  
Mishal Almousa ◽  
Mishal Al Sheqawi ◽  
Muntdher Almousa
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Dosage Forms ◽  
Multivariate Curve Resolution ◽  
Control Analysis ◽  
Least Squares Regression ◽  
Pharmaceutical Dosage Forms ◽  
Curve Resolution ◽  
Target Analytes ◽  
Significant Difference

Abstract Background: Considering the environmental impact of analytical procedures necessitates replacing the polluting analytical methods with green alternatives. Objective: This study aims to develop and validate a multivariate curve resolution–alternating least-squares (MCR-ALS) method with correlation constraint for the simultaneous determination of theophylline, ambroxol, and guaifenesin as target analytes in the presence of methylparaben and propylparaben as interfering components. In addition, a partial least-squares regression (PLSR) method was also developed andoptimized. Method: The developed methods were validated according to International Conference on Harmonization guidelines and successfully applied for the quantification of the target analytes in different pharmaceutical dosage forms. Results: Figures of merit such as root mean square error of prediction, bias, standard error of prediction, and relative error of prediction for both models were calculated, and they showedsimilar and satisfactory results. Correlation coefficients ranged between 0.9988 and 0.9992, reflectinghigh predictive ability. The optimized methods werecompared with a reported HPLC method using one-wayanalysis of variance and showed no significant difference regarding accuracy and precision. Conclusions: The proposed chemometrics methods can be used as an eco-friendly alternative for chromatographic techniques for the quality control analysis of the studied mixture in different pharmaceutical dosage forms. Highlights: An MCR-ALS model was developed. The developed model was compared with a PLSR model. Both models were validated and successfully used for the determinationof a multicomponent pharmaceutical mixture. The developed method is eco-friendly, fast, reliable, and cost-effective.

scholarly journals Quantitative analysis and resolution of pharmaceuticals in the environment using multivariate curve resolution-alternating least squares (MCR-ALS)

2019 ◽  
Vol 69 (2) ◽  
pp. 217-231 ◽  
Author(s):  
Ahmed Mostafa ◽  
Heba Shaaban
Keyword(s):  
Least Squares ◽  
Water Samples ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Least Squares Regression ◽  
Environmental Matrices ◽  
Curve Resolution ◽  
Real Water Samples ◽  
Target Analytes ◽  
Spectrophotometric Data

Abstract The study presents the application of multivariate curve resolution alternating least squares (MCR-ALS) with a correlation constraint for simultaneous resolution and quantification of ketoprofen, naproxen, paracetamol and caffeine as target analytes and triclosan as an interfering component in different water samples using UV-Vis spectrophotometric data. A multivariate regression model using the partial least squares regression (PLSR) algorithm was developed and calculated. The MCR-ALS results were compared with the PLSR obtained results. Both models were validated on external sample sets and were applied to the analysis of real water samples. Both models showed comparable and satisfactory results with the relative error of prediction of real water samples in the range of 1.70–9.75 % and 1.64–9.43 % for MCR-ALS and PLSR, resp. The obtained results show the potential of MCR-ALS with correlation constraint to be applied for the determination of different pharmaceuticals in complex environmental matrices.

Comparative study of partial least squares and multivariate curve resolution for simultaneous spectrophotometric determination of pharmaceuticals in environmental samples

RSC Advances ◽  
2015 ◽  
Vol 5 (86) ◽  
pp. 70017-70024 ◽  
Author(s):  
Hadi Parastar ◽  
Hamidreza Shaye
Keyword(s):  
Comparative Study ◽  
Least Squares ◽  
Simultaneous Determination ◽  
Partial Least Squares ◽  
Mefenamic Acid ◽  
Environmental Samples ◽  
Multivariate Curve Resolution ◽  
Curve Resolution ◽  
Target Analytes

The potentials of PLSR and MCR-ALS are evaluated for the simultaneous determination of diclofenac, naproxen, mefenamic acid and carbamazepine as target analytes and gemfibrozil as interference in synthetic and real environmental samples.

scholarly journals Simultaneous Determination of Drugs Affecting Central Nervous System (CNS) in Bulk and Pharmaceutical Formulations Using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS)

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Heba Shaaban ◽  
Ahmed Mostafa ◽  
Bushra Al-Zahrani ◽  
Bushra Al-Jasser ◽  
Raghad Al-Ghamdi
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Least Squares ◽  
Pharmaceutical Formulations ◽  
Pharmaceutical Products ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Pharmaceutical Dosage Forms ◽  
Curve Resolution ◽  
Significant Difference

The quality of medications is important to maintain the overall health care of patients. This study aims to develop and validate a spectrophotometric method using multivariate curve resolution-alternating least squares (MCR-ALS) with correlation constraint for simultaneous resolution and quantification of selected drugs affecting the central nervous system (imipramine, carbamazepine, chlorpromazine, haloperidol, and phenytoin) in different pharmaceutical dosage forms. Figures of merit such as root-mean-square error of prediction, bias, standard error of prediction, and relative error of prediction for the developed method were calculated. High values of correlation coefficients ranged between 0.9993 and 0.9998 reflected high predictive ability of the developed method. The results are linear in the concentration range of 0.3–5 μg/mL for carbamazepine, 0.3–15 μg/mL for chlorpromazine, 0.5–10 μg/mL for haloperidol, 0.5–10 μg/mL for imipramine, and 3–20 μg/mL for phenytoin. The optimized method was successfully applied for the analysis of the studied drugs in their pharmaceutical products without any separation step. The optimized method was also compared with a reported HPLC method using Student’s t test and F ratio at 95% confidence level, and the results showed no significant difference regarding accuracy and precision. The proposed chemometric method is fast, reliable, and cost-effective and can be used as an eco-friendly alternative to chromatographic techniques for the analysis of the studied drugs in commercial pharmaceutical products.

scholarly journals Determination of Cefoperazone Sodium in Presence of Related Impurities by Linear Support Vector Regression and Partial Least Squares Chemometric Models

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Ibrahim A. Naguib ◽  
Eglal A. Abdelaleem ◽  
Hala E. Zaazaa ◽  
Essraa A. Hussein
Keyword(s):  
Least Squares ◽  
Support Vector Regression ◽  
Partial Least Squares ◽  
Multivariate Calibration ◽  
Drug Product ◽  
Support Vector ◽  
Control Analysis ◽  
Least Squares Regression ◽  
Significant Difference ◽  
Cefoperazone Sodium

A comparison between partial least squares regression and support vector regression chemometric models is introduced in this study. The two models are implemented to analyze cefoperazone sodium in presence of its reported impurities, 7-aminocephalosporanic acid and 5-mercapto-1-methyl-tetrazole, in pure powders and in pharmaceutical formulations through processing UV spectroscopic data. For best results, a 3-factor 4-level experimental design was used, resulting in a training set of 16 mixtures containing different ratios of interfering moieties. For method validation, an independent test set consisting of 9 mixtures was used to test predictive ability of established models. The introduced results show the capability of the two proposed models to analyze cefoperazone in presence of its impurities 7-aminocephalosporanic acid and 5-mercapto-1-methyl-tetrazole with high trueness and selectivity (101.87 ± 0.708 and 101.43 ± 0.536 for PLSR and linear SVR, resp.). Analysis results of drug products were statistically compared to a reported HPLC method showing no significant difference in trueness and precision, indicating the capability of the suggested multivariate calibration models to be reliable and adequate for routine quality control analysis of drug product. SVR offers more accurate results with lower prediction error compared to PLSR model; however, PLSR is easy to handle and fast to optimize.

scholarly journals Simultaneous Determination of Over-the-Counter Pain Relievers in Commercial Pharmaceutical Products Utilizing Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) Multivariate Calibration Model

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Heba Shaaban ◽  
Ahmed Mostafa ◽  
Zahra Almatar ◽  
Reem Alsheef ◽  
Safia Alrubh
Keyword(s):  
Least Squares ◽  
Multivariate Calibration ◽  
Pharmaceutical Products ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Calibration Model ◽  
Over The Counter ◽  
Curve Resolution ◽  
Relative Standard ◽  
Significant Difference

The quality of over-the-counter (OTC) pain relievers is important to ensure the safety of the marketed products in order to maintain the overall health care of patients. In this study, the multivariate curve resolution-alternating least squares (MCR-ALS) chemometric method was developed and validated for the resolution and quantification of the most commonly consumed OTC pain relievers (acetaminophen, acetylsalicylic acid, ibuprofen, naproxen, and caffeine) in commercial drug formulations. The analytical performance of the developed chemometric methods such as root mean square error of prediction, bias, standard error of prediction, relative error of prediction, and coefficients of determination was calculated for the developed model. The obtained results are linear with concentration in the range of 0.5–7 μg/mL for acetaminophen and 0.5–3.5 and 0.5–3 μg/mL for naproxen and caffeine, respectively, while the linearity ranges for acetyl salicylic acid and ibuprofen were 1–15 μg/mL. High values of coefficients of determination ≥0.9995 reflected high predictive ability of the developed model. Good recoveries ranging from 98.0% to 99.7% were obtained for all analytes with relative standard deviations (RSDs) not higher than 1.62%. The optimized method was successfully applied for the analysis of the studied drugs either in their single or coformulated pharmaceutical products without any separation step. The optimized method was also compared with a reported HPLC method using paired t-test and F-ratio at 95% confidence level, and the results showed no significant difference regarding accuracy and precision. The developed method is eco-friendly, simple, fast, and amenable for routine analysis. It could be used as a cost-effective alternative to chromatographic techniques for the analysis of the studied drugs in commercial formulations.

A Comparative Chemometric Study for Quantitative Determination of Duloxetine Hydrochloride in the Presence of its Toxic Impurity 1-Naphthol

2020 ◽  
Vol 16 (8) ◽  
pp. 1030-1036 ◽  
Author(s):  
Basma H. Anwar ◽  
Nessreen S. Abdelhamid ◽  
Maimana A. Magdy ◽  
Ibrahim A. Naguib
Keyword(s):  
Least Squares ◽  
Multivariate Calibration ◽  
Dosage Forms ◽  
Hplc Method ◽  
Raw Material ◽  
Support Vector ◽  
Pharmaceutical Dosage Forms ◽  
Advantages And Disadvantages ◽  
Duloxetine Hydrochloride ◽  
Significant Difference

Background: Duloxetine hydrochloride (DUL) is a serotonin-norepinephrine reuptake inhibitor. It is used for treating depression and anxiety. It is available in the market as a capsule called Cymbatex®, which is used for the treatment of depression. 1-naphthol is a potential impurity of DUL. It is hepatotoxic to humans and has potential toxicity to freshwater fish. Objective: Duloxetine hydrochloride was determined in the presence of its toxic impurity 1-naphthol in raw material and in pharmaceutical dosage forms using three multivariate calibration chemometric methods. Methods: Classical Least Squares (CLS), Partial Least-Squares (PLS) and linear support vector regression (SVR) were developed using UV spectral data. The three methods were compared among each other and the advantages and disadvantages were discussed. For good results, a two-factor four-level experimental design was used, resulting in a training set of 16 mixtures containing different ratios of each component. The test set consisting of nine mixtures was necessary to test the ability of the proposed methods to predict DUL in the presence of its impurity, 1-naphthol. Results: The results show the success of the three developed methods to determine DUL in the presence of small levels of its toxic impurity with good accuracy and selectivity. The results of the dosage form were compared statistically to that of the reported HPLC method, with no significant difference in accuracy and precision. Conclusion: The suggested calibration models are suitable for routine analysis of the drug in bulk and pharmaceutical dosage forms. Compared to the CLS and PLS models, the SVR model gives the best results regarding the accuracy with a lower prediction error and better generalization ability. However, the CLS and PLS models are found to be simpler and faster in usage and management.

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