scholarly journals The Determination of Parkinson’s Drugs in Human Urine by Applying Chemometric Methods

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Guzide Pekcan Ertokus
Keyword(s):  
Urine Sample ◽  
Human Urine ◽  
Principal Component Regression ◽  
Principal Component ◽  
Healthy Person ◽  
Drug Analysis ◽  
Uv Spectrophotometry ◽  
Least Squares Regression ◽  
Chemometric Methods

The spectrophotometric-chemometric analysis of levodopa and carbidopa that are used for Parkinson’s disease was analyzed without any prior reservation. Parkinson’s drugs in the urine sample of a healthy person (never used drugs in his life) were analyzed at the same time spectrophotometrically. The chemometric methods used were partial least squares regression (PLS) and principal component regression (PCR). PLS and PCR were successfully applied as chemometric determination of levodopa and carbidopa in human urine samples. A concentration set including binary mixtures of levodopa and carbidopa in 15 different combinations was randomly prepared in acetate buffer (pH 3.5).). UV spectrophotometry is a relatively inexpensive, reliable, and less time-consuming method. Minitab program was used for absorbance and concentration values. The normalization values for each active substance were good (r2>0.9997). Additionally, experimental data were validated statistically. The results of the analyses of the results revealed high recoveries and low standard deviations. Hence, the results encouraged us to apply the method to drug analysis. The proposed methods are highly sensitive and precise, and therefore they were implemented for the determination of the active substances in the urine sample of a healthy person in triumph.

scholarly journals Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form

2021 ◽  
Vol 19 (1) ◽  
pp. 205-213
Author(s):  
Hany W. Darwish ◽  
Abdulrahman A. Al Majed ◽  
Ibrahim A. Al-Suwaidan ◽  
Ibrahim A. Darwish ◽  
Ahmed H. Bakheit ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simultaneous Determination ◽  
Predictive Power ◽  
Principal Component Regression ◽  
Selection Procedure ◽  
Principal Component ◽  
Chemometric Methods ◽  
Full Spectrum ◽  
Azilsartan Medoxomil

Abstract Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal component regression, and artificial neural networks (ANN), were among the applied methods. Besides, the ANN and PLS were the other two methods that were extended by genetic algorithm procedure (GA-PLS and GA-ANN) as a wavelength selection procedure. The models were developed by applying a multilevel multifactor experimental design. The predictive power of the suggested models was evaluated through a validation set containing nine mixtures with different ratios of the three analytes. For the analysis of Edarbyclor® tablets, all the proposed procedures were applied and the best results were achieved in the case of ANN, GA-ANN, and GA-PLS methods. The findings of the three methods were revealed as the quantitative tool for the analysis of the three components without any intrusion from the co-formulated excipient and without prior separation procedures. Moreover, the GA impact on strengthening the predictive power of ANN- and PLS-based models was also highlighted.

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.

Spectrophotometric Simultaneous Determination of Levamisole and Triclabendazole in Tablets by Principal Component Regression and Partial Least Squares Chemometric Methods

2008 ◽  
Vol 59 (2) ◽  
pp. 154-158 ◽  
Author(s):  
Gozde Pektas ◽  
Erdal Dinc ◽  
Dumitru Baleanu
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Principal Component Regression ◽  
Principal Component ◽  
Standard Addition ◽  
Chemometric Methods ◽  
Preliminary Separation ◽  
Absorbance Data ◽  
Good Agreement

Principal component regression (PCR) and partial least squares (PLS) chemometric methods were applied to the simultaneous quantitative analysis of levamisole (LVM) and triclabendazole (TCB) in tablets without using a preliminary separation, even in presence of the overlapping spectra of the above compounds. For both PCR and PLS, a concentration set containing 25 different mixtures of LVM and TCB in the linear concentration range was symmetrically prepared and then the absorbance values of the concentration set were measured at the wavelength set with Dl=0.1 nm in the spectral region of 225-322.3 nm. PCR and PLS calibrations were obtained by applying the PCR and PLS algorithms to the concentration set data (y-block) and their corresponding absorbance data (x-block). The validity of PCR and PLS chemometric methods was performed by using the independent synthetic mixtures and the standard addition technique. Then, these analytical methods were applied to the commercial tablets and a good agreement was obtained between experimental results provided by the application of the PCR and PLS to the synthetic and real samples.

scholarly journals Simultaneous Determination of Caffeine, 8-Chlorotheophylline, and Chlorphenoxamine Hydrochloride in Ternary Mixtures by Ratio-Spectra Zero-Crossing First-Derivative Spectrophotometric and Chemometric Methods

2005 ◽  
Vol 88 (4) ◽  
pp. 1126-1134 ◽  
Author(s):  
Khadiga M Kelani
Keyword(s):  
Simultaneous Determination ◽  
Principal Component Regression ◽  
Detection Limits ◽  
Principal Component ◽  
Ternary Mixtures ◽  
Chemometric Methods ◽  
Zero Crossing ◽  
First Derivative ◽  
Preliminary Separation

Abstract A ratio-spectra zero-crossing first-derivative spectrophotometric method and 2 chemometric methods have been used for the simultaneous determination of ternary mixtures of caffeine (A), 8-chlorotheophylline (B), and chlorphenoxamine hydrochloride (C) in bulk powder and dosage forms. In the ratio-spectra zero-crossing first-derivative spectrophotometric technique (1DD), calibration curves were linear in the range of 4–20 μg/mL for A, B, and C (r = 0.9992, 0.9994, and 0.9976, respectively). The measurements were carried out at 212, 209.2, and 231.4 nm for A, B, and C, respectively. The detection limits for A, B, and C were calculated to be 0.24, 0.34, and 0.13 μg/mL, and the percentage recoveries were 99.1 ± 0.89, 100.1 ± 0.95, and 100.1 ± 1.0, respectively. Two chemometric methods, namely, the partial least-squares (PLS) model and the principal component regression (PCR) model, were also used for the simultaneous determination of the 3 drugs in the ternary mixture. A training set consisting of 15 mixtures containing different ratios of A, B, and C was used. The concentration used for the construction of the PLS and PCR models varied between 4 and 25 μg/mL for each drug. These models were used after their validation for the prediction of the concentrations of A, B, and C in mixtures. The detection limits for A, B, and C were calculated to be 0.13, 0.15, and 0.14 μg/mL, respectively, and the percent recoveries were found to be 99.8 ± 0.96, 99.9 ± 0.94, and 99.9 ± 1.18, respectively, for both methods. The 3 proposed procedures are rapid, simple, sensitive, and accurate. No preliminary separation steps or resolution equations are required; thus, they can be applied to the simultaneous determination of the 3 drugs in commercial tablets and suppositories or in quality-control laboratories.

Application of independent component analysis, principal component regression and partial least squares methodologies for the simultaneous potentiometric titration of some amino acids

RSC Advances ◽  
2016 ◽  
Vol 6 (74) ◽  
pp. 69902-69908 ◽  
Author(s):  
A. Hakan Aktaş ◽  
Sermin Göksu Karagöz
Keyword(s):  
Amino Acids ◽  
Independent Component Analysis ◽  
Least Squares ◽  
Simultaneous Determination ◽  
Partial Least Squares ◽  
Potentiometric Titration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Chemometric Methods

Potentiometric titration and chemometric methods were applied to the simultaneous determination of the four amino acids, alanine (ALA), phenylalanine (PHE), leucine (LEU) and lysine (LYS).

scholarly journals Application of Derivative, Derivative Ratio, and Multivariate Spectral Analysis and Thin-Layer Chomatography-Densitometry for Determination of a Ternary Mixture Containing Drotaverine Hydrochloride, Caffeine, and Paracetamol

2007 ◽  
Vol 90 (2) ◽  
pp. 391-404 ◽  
Author(s):  
Fadia H Metwally ◽  
Yasser S El-Saharty ◽  
Mohamed Refaat ◽  
Sonia Z El-Khateeb
Keyword(s):  
Thin Layer ◽  
Least Squares ◽  
Ternary Mixture ◽  
Principal Component Regression ◽  
Pharmaceutical Preparations ◽  
Principal Component ◽  
Standard Addition ◽  
Drotaverine Hydrochloride ◽  
Assay Precision

Abstract New selective, precise, and accurate methods are described for the determination of a ternary mixture containing drotaverine hydrochloride (I), caffeine (II), and paracetamol (III). The first method uses the first (D1) and third (D3) derivative spectrophotometry at 331 and 315 nm for the determination of (I) and (III), respectively, without interference from (II). The second method depends on the simultaneous use of the first derivative of the ratio spectra (DD1) with measurement at 312.4 nm for determination of (I) using the spectrum of 40 μg/mL (III) as a divisor or measurement at 286.4 and 304 nm after using the spectrum of 4 μg/mL (I) as a divisor for the determination of (II) and (III), respectively. In the third method, the predictive abilities of the classical least-squares, principal component regression, and partial least-squares were examined for the simultaneous determination of the ternary mixture. The last method depends on thin-layer chromatography-densitometry after separation of the mixture on silica gel plates using ethyl acetatechloroformmethanol (16 + 3 + 1, v/v/v) as the mobile phase. The spots were scanned at 281, 272, and 248 nm for the determination of (I), (II), and (III), respectively. Regression analysis showed good correlation in the selected ranges with excellent percentage recoveries. The chemical variables affecting the analytical performance of the methodology were studied and optimized. The methods showed no significant interferences from excipients. Intraday and interday assay precision and accuracy values were within regulatory limits. The suggested procedures were checked using laboratory-prepared mixtures and were successfully applied for the analysis of their pharmaceutical preparations. The validity of the proposed methods was further assessed by applying a standard addition technique. The results obtained by applying the proposed methods were statistically analyzed and compared with those obtained by the manufacturer's method.

Multivariate Analysis Aided Surface-Enhanced Raman Spectroscopy (MVA-SERS) Multiplex Quantitative Detection of Trace Fentanyl in Illicit Drug Mixtures Using a Handheld Raman Spectrometer

2021 ◽  
pp. 000370282110329
Author(s):  
Ling Wang ◽  
Mario O. Vendrell-Dones ◽  
Chiara Deriu ◽  
Sevde Doğruer ◽  
Peter de B. Harrington ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Principal Component ◽  
Surface Enhanced Raman Spectroscopy ◽  
Quantitative Detection ◽  
Least Squares Regression ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Sers Detection ◽  
Current Screening

Recently there has been upsurge in reports that illicit seizures of cocaine and heroin have been adulterated with fentanyl. Surface-enhanced Raman spectroscopy (SERS) provides a useful alternative to current screening procedures that permits detection of trace levels of fentanyl in mixtures. Samples are solubilized and allowed to interact with aggregated colloidal nanostars to produce a rapid and sensitive assay. In this study, we present the quantitative determination of fentanyl in heroin and cocaine using SERS, using a point-and-shoot handheld Raman system. Our protocol is optimized to detect pure fentanyl down to 0.20 ± 0.06 ng/mL and can also distinguish pure cocaine and heroin at ng/mL levels. Multiplex analysis of mixtures is enabled by combining SERS detection with principal component analysis and super partial least squares regression discriminate analysis (SPLS-DA), which allow for the determination of fentanyl as low as 0.05% in simulated seized heroin and 0.10% in simulated seized cocaine samples.

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.

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