Multicomponent kinetic spectrophotometric determination of pefloxacin and norfloxacin in pharmaceutical preparations and human plasma samples with the aid of chemometrics

A spectrophotometric method for the simultaneous determination of the important pharmaceuticals, pefloxacin and its structurally similar metabolite, norfloxacin, is described for the first time. The analysis is based on the monitoring of a kinetic spectrophotometric reaction of the two analytes with potassium permanganate as the oxidant. The measurement of the reaction process followed the absorbance decrease of potassium permanganate at 526nm, and the accompanying increase of the product, potassium manganate, at 608nm. It was essential to use multivariate calibrations to overcome severe spectral overlaps and similarities in reaction kinetics. Calibration curves for the individual analytes showed linear relationships over the concentration ranges of 1.0-11.5mgL(-1) at 526 and 608nm for pefloxacin, and 0.15-1.8mgL(-1) at 526 and 608nm for norfloxacin. Various multivariate calibration models were applied, at the two analytical wavelengths, for the simultaneous prediction of the two analytes including classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), radial basis function-artificial neural network (RBF-ANN) and principal component-radial basis function-artificial neural network (PC-RBF-ANN). PLS and PC-RBF-ANN calibrations with the data collected at 526nm, were the preferred methods-%RPE(T) approximately 5, and LODs for pefloxacin and norfloxacin of 0.36 and 0.06mgL(-1), respectively. Then, the proposed method was applied successfully for the simultaneous determination of pefloxacin and norfloxacin present in pharmaceutical and human plasma samples. The results compared well with those from the alternative analysis by HPLC.     

偏最小二乘法及主组分回归法用于药物组分的测定

本文研究了多元校准方法——偏最小二乘法(PLS)和主组份回归法(PCR)在药物多组份光度分析中的应用,获得了较满意的结果。而且在系列校准样品的实验设计、交叉证实法确定最佳因子数以及空缺组份体系的分析等方面进行了探讨。     

微分脉冲溶出伏安法结合化学计量学测定醚类除草剂

在pH=6.82的Britton-Robinson缓冲溶液中,采用循环伏安法和微分脉冲溶出伏安法对醚类除草剂甲羧除草醚(Bifenox)和三氟羧草醚(Acifluofen)的伏安行为进行了研究,发现吸附时间为50 s时此电化学体系达到平衡,而且微分脉冲溶出伏安法能给出较高的灵敏度,甲羧除草醚和三氟羧草醚分别在-685 mV和-700 mV处具有良好还原峰,但由于峰电位接近而谱峰重叠,很难分别测定.本文采用化学计量学方法来解析重叠峰并完成这两种除草剂的定量分析.甲羧除草醚和三氟羧草醚的测定线性范围分别为0.02～0.18 μg·5mL~(-1)和0.02～0.16 μg·5mL~(-1),检出限分别为0.0073 μg·5mL~(-1)和0.0068 μg·5mL~(-1).利用该方法对水样中的甲羧除草醚和三氟羧草醚进行直接测定,获得了较好的定量分析结果.     

Chemometric determination of naproxen sodium and pseudoephedrine hydrochloride in tablets by HPLC

A new chemometric determination by high-performance liquid chromatography (HPLC) with photodiode array (PDA) detection was implemented for the simultaneous determination of naproxen sodium and pseudoephedrine hydrochloride in tablets. Three chemometric calibration techniques, classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS) were applied to the peak area at multiwavelength PDA detector responses. The combinations of HPLC with chemometric calibration techniques were called HPLC-CLS, HPLC-PCR and HPLC-PLS. For comparison purposes the HPLC method called the classic HPLC method was used to confirm the results obtained from combined HPLC-chemometric calibration techniques. A good chromatographic separation between two drugs with losartan potassium as an internal standard was achieved using a Waters Symmetry C18 Column 5 microm 4.6+/-250 mm and a mobile phase containing 0.2 M acetate buffer and acetonitrile (v/v, 40:60). The multiwavelength PDA detection was measured at five different wavelengths. The chromatograms were recorded as a training set in the mobile phase. Three HPLC-chemometric calibrations and the classic-HPLC method were used to test the synthetic mixtures of naproxen sodium and pseudoephedrine hydrochloride in the presence of the internal standard. The HPLC-chemometric approaches were applied to real samples containing drugs of interest. The experimental results obtained from HPLC-chemometric calibrations were compared with those obtained by a classic HPLC method.     

Application of Multivariate Calibration Techniques to HPLC Data for Quantitative Analysis of a Binary Mixture of Hydrochlorathiazide and Losartan in Tablets

New multivariate approaches have been applied to high-performance liquid chromatography (HPLC) with multiwavelength photodiode-array (PDA) detection. Multivariate calibration techniques such as partial least squares (PLS), principal component regression (PCR), classical least squares (CLS), and inverse least squares (ILS) was subjected to HPLC data for simultaneous quantitative analysis of synthetic binary mixtures and a commercial tablet formulation containing hydrochlorothiazide (HCT) and losartan potassium (LST). The combined use of HPLC and multivariate calibrations has been denoted HPLC–CLS, HPLC–ILS, HPLC–PCR, and HPLC–PLS. Successful chromatographic separation of the two active compounds and enalapril maleate, used as internal standard (IS), was accomplished by means of a 4.6 mm i.d. × 250 mm, 5 m particle, Waters Symmetry C₁₈ reversed-phase column and a mobile phase consisting of 60:40 acetate buffer (0.2 M, pH 4.8)–acetonitrile (v/v, 60:40). HPLC data based on the ratio of analyte peak areas to IS peak area were obtained by PDA detection at five-wavelengths (250, 255, 260, 265, and 270 nm). The HPLC–CLS, HPLC–ILS, HPLC–PCR, and HPLC–PLS calibration plots for hydrochlorothiazide and losartan potassium were constructed separately by using the peak-area ratios corresponding to the concentrations of each active compound. The HPLC multivariate calibrations obtained were tested for different synthetic mixtures containing HCT and LST in the presence of the IS. These multivariate chromatographic methods were also applied to a commercial pharmaceutical dosage form containing HCT and LST. The results obtained from the multivariate calibrations were compared with those obtained by use of another, classical HPLC method using single-wavelength detection.Revised: 29 September 2004 and 4 January 2005     

Spectrophotometric determination of metal ions in electroplating solutions in the presence of EDTA with the aid of multivariate calibration and artificial neural networks

Metal ions such as Co(II), Ni(II), Cu(II), Fe(III) and Cr(III), which are commonly present in electroplating baths at high concentrations, were analysed simultaneously by a spectrophotometric method modified by the inclusion of the ethylenediaminetetraacetate (EDTA) solution as a chromogenic reagent. The prediction of the metal ion concentrations was facilitated by the use of an orthogonal array design to build a calibration data set consisting of absorption spectra collected in the 370-760 nm range from solution mixtures containing the five metal ions earlier. With the aid of this data set, calibration models were built based on 10 different chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), artificial neural networks (ANN) and others. These were tested with the use of a validation data set constructed from synthetic solutions of the five metal ions. The analytical performance of these chemometrics methods were characterized by relative prediction errors and recoveries (%). On the basis of these results, the computational methods were ranked according to their performances using the multi-criteria decision making procedures preference ranking organization method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA). PLS and PCR models applied to the spectral data matrix that used the first derivative pre-treatment were the preferred methods. They together with ANN-radial basis function (RBF) and PLS were applied for analysis of results from some typical industrial samples analysed by the EDTA-spectrophotometric method described. DPLS, DPCR and the ANN-RBF chemometrics methods performed particularly well especially when compared with some target values provided by industry.     

Simultaneous Polarographic Determination of Lead (II) and TIN (II) by Multivariate Calibration

ABSTRACT

The polarographic waves of lead (II) and tin (II) overlap due to their similar reductive potentials and it is difficult to determine these two components simultaneously without a pre-separation. In this paper, differential pulse polarography (DPP) combined with multivariate calibration approaches, such as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS), were successfully applied to the resolution of overlapping polarographic waves of these two components in the concentration range of 0.05-3.50 mg 1^?1. Satisfactory quantitative results were obtained.     

Solving matrix effect,spectral overlapping and nonlinearity by generalized standard addition method coupled with radial basis functions–partial least squares: simultaneous determination of atorvastatin and amlodipine in urine

For simultaneous determination in conditions with spectral overlap and variation of matrix effects, coupling of the generalized standard addition method (GSAM) with the multivariate nonlinear method of radial basis function–partial least squares (RBF–PLS) was proposed. The nonlinearity caused by the GSAM used to correct matrix effects was studied, and principal component analysis was proposed for identifying it. In the method introduced, the whole sensor range can be used without the collinearity problem encountered in the application of GSAM with classical least squares (CLS), and calibration can be made for each analyte, separately. The introduced method was applied to determine amlodipine and atorvastatin in urine samples. The mean of the percent recoveries was between 95 and 101.12. The percent relative standard deviation values of the method were in most cases below 5%. The results of GSAM–RBF–PLS were compared with those obtained by GSAM–CLS and GSAM–PLS. Copyright © 2013 John Wiley & Sons, Ltd.     

Spectrophotometric determination of hydrocortisone, nystatin and oxytetracycline in synthetic and pharmaceutical preparations based on various univariate and multivariate methods

Two spectrophotometric methods are described and applied to resolve ternary mixtures of the corticosteroid hydrocortisone (HYD) and the antibiotics nystatin (NYS) and oxytetracycline (OXY). The simultaneous determination of these three compounds was firstly accomplished by a derivative method using the “ratio spectrum-zero crossing derivative” and then by multivariate methods partial least squares (PLS)-1, -2 and principal component regression (PCR). Multivariate calibration methods provide, specially PLS-2 in this case, a clear example of the high resolving powder of these techniques. The two described procedures do not require any separation step. Repeatability and reproducibility studies were achieved over two series of 10 standards for each compound showing no significant differences at 95% confidence level in the four spectrophotometric methods. A comparison of the derivative and multivariate calibration results obtained in pharmaceutical formulations was performed resulting in agreement of the values obtained and the results was confirm by a high-pressure liquid chromatography (HPLC) method.     

Simultaneous quantitative resolution of atorvastatin calcium and fenofibrate in pharmaceutical preparation by using derivative ratio spectrophotometry and chemometric calibrations.

In the present work, five different spectrophotometric techniques for simultaneous determination of formulations containing atorvastatin calcium (ATOR) and fenofibrate (FENO) in various combinations are described. In ratio spectra derivative spectrophotometry, analytical signals were measured at wavelengths corresponding to either maximums or minimums for both drugs in first derivative spectra of ratio spectra obtained by using either spectrum as divisor. For the remaining four methods using chemometric techniques, namely, classical least squares (CLS), inverse least squares (ILS), principal component regression (PCR) and partial least squares (PLS), the calibrations were constructed by using the absorption data matrix corresponding to the concentration data matrix, with measurements in the range of 231 - 310 nm (Deltalambda = 1 nm) in their zero-order spectra. The linearity range was found to be 4 - 22 and 2 - 20 microg/ml for ATOR and FENO, respectively. The validity of the proposed methods was successfully assessed for analyses of both drugs in laboratory-prepared mixtures and in commercial tablet formulations.     

Improving the performance of hollow waveguide-based infrared gas sensors via tailored chemometrics

The use of chemometrics in order to improve the molecular selectivity of infrared (IR) spectra has been evaluated using classic least squares (CLS), partial least squares (PLS), science-based calibration (SBC), and multivariate curve resolution-alternate least squares (MCR-ALS) techniques for improving the discriminatory and quantitative performance of infrared hollow waveguide gas sensors. Spectra of mixtures of isobutylene, methane, carbon dioxide, butane, and cyclopropane were recorded, analyzed, and validated for optimizing the prediction of associated concentrations. PLS, CLS, and SBC provided equivalent results in the absence of interferences. After addition of the spectral characteristics of water by humidifying the sample mixtures, CLS and SBC results were similar to those obtained by PLS only if the water spectrum was included in the calibration model. In the presence of an unknown interferant, CLS revealed errors up to six times higher than those obtained by PLS. However, SBC provided similar results compared to PLS by adding a measured noise matrix to the model. Using MCR-ALS provided an excellent estimation of the spectra of the unknown interference. Furthermore, this method also provided a qualitative and quantitative estimation of the components of an unknown set of samples. In summary, using the most suitable chemometrics approach could improve the selectivity and quality of the calibration model derived for a sensor system, and may avoid the need to analyze expensive calibration data sets. The results obtained in the present study demonstrated that (1) if all sample components of the system are known, CLS provides a sufficiently accurate solution; (2) the selection between PLS and SBC methods depends on whether it is easier to measure a calibration data set or a noise matrix; and (3) MCR-ALS appears to be the most suitable method for detecting interferences within a sample. However, the latter approach requires the most extensive calculations and may thus result in limited temporal resolution, if the concentration of a component should be continuously monitored.     

Spectrophotometric determination of ternary mixtures of thiamin, riboflavin and pyridoxal in pharmaceutical and human plasma by least-squares support vector machines.

Ternary mixtures of thiamin, riboflavin and pyridoxal have been simultaneously determined in synthetic and real samples by applications of spectrophotometric and least-squares support vector machines. The calibration graphs were linear in the ranges of 1.0 - 20.0, 1.0 - 10.0 and 1.0 - 20.0 microg ml(-1) with detection limits of 0.6, 0.5 and 0.7 microg ml(-1) for thiamin, riboflavin and pyridoxal, respectively. The experimental calibration matrix was designed with 21 mixtures of these chemicals. The concentrations were varied between calibration graph concentrations of vitamins. The simultaneous determination of these vitamin mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares (PLS) modeling and least-squares support vector machines were used for the multivariate calibration of the spectrophotometric data. An excellent model was built using LS-SVM, with low prediction errors and superior performance in relation to PLS. The root mean square errors of prediction (RMSEP) for thiamin, riboflavin and pyridoxal with PLS and LS-SVM were 0.6926, 0.3755, 0.4322 and 0.0421, 0.0318, 0.0457, respectively. The proposed method was satisfactorily applied to the rapid simultaneous determination of thiamin, riboflavin and pyridoxal in commercial pharmaceutical preparations and human plasma samples.     

Simultaneous spectrophotometric determination of p-benzoquinone and chloranil after microcrystalline naphthalene extraction by using genetic algorithm-based wavelength selection-partial least squares regression.

Microcrystalline naphthalene extraction has been used for the preconcentration of p-benzoquinone and tetrachloro-p-benzoquinone (chloranil), after their reaction by aniline, and later simultaneous spectrophotometric analysis by genetic algorithm-partial least squares (GA-PLS) calibration. The chemical variables affecting the analytical performance of the methodology were studied and optimized. Under the optimum conditions i.e., [aniline] = 0.05 M and [naphthalene] = 2.2% (w/v), preconcentration of 25 ml of sample solution permitted the detection of 0.32 and 0.23 microg ml(-1) for p-benzoquinone and chloranil, respectively. The predictive abilities of partial least squares regression (PLS) and genetic algorithm-partial least squares regression (GA-PLS) were examined for simultaneous determination of two quinones. The GA-PLS shows superiority over other PLS methods due to the wavelength selection in PLS calibration using a genetic algorithm without loss of prediction capacity, provides useful information about the chemical system.     

HPLC and chemometrics-assisted UV-spectroscopy methods for the simultaneous determination of ambroxol and doxycycline in capsule

High-performance liquid chromatography (HPLC) and multivariate spectrophotometric methods are described for the simultaneous determination of ambroxol hydrochloride (AM) and doxycycline (DX) in combined pharmaceutical capsules. The chromatographic separation was achieved on reversed-phase C(18) analytical column with a mobile phase consisting of a mixture of 20mM potassium dihydrogen phosphate, pH 6-acetonitrile in ratio of (1:1, v/v) and UV detection at 245 nm. Also, the resolution has been accomplished by using numerical spectrophotometric methods as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS-1) applied to the UV spectra of the mixture and graphical spectrophotometric method as first derivative of the ratio spectra ((1)DD) method. Analytical figures of merit (FOM), such as sensitivity, selectivity, analytical sensitivity, limit of quantitation and limit of detection were determined for CLS, PLS-1 and PCR methods. The proposed methods were validated and successfully applied for the analysis of pharmaceutical formulation and laboratory-prepared mixtures containing the two component combination.     

Orthogonal signal correction-partial least squares method for simultaneous spectrophotometric determination of cypermethrin and tetramethrin

The simultaneous determination of cypermethrin and tetramethrin mixtures by using spectrophotometric method is a difficult problem in analytical chemistry, due to spectral interferences. By multivariate calibration methods, such as partial least squares (PLS) regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction (OSC) is a preprocessing technique used for removing the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 200-350 nm range for 25 different mixtures of cypermethrin and tetramethrin. Calibration matrices were containing 0.1-12.9 and 0.1-13.8 microg mL(-1) for cypermethrin and tetramethrin, respectively. The RMSEP for cypermethrin and tetramethrin with OSC and without OSC were 0.0884, 0.0614 and 0.2915, 0.2309, respectively. This procedure allows the simultaneous determination of cypermethrin and tetramethrin in synthetic and real samples good reliability of the determination was proved.     

Net analyte signal-based simultaneous determination of antazoline and naphazoline using wavelength region selection by experimental design-neural networks

Net analyte signal (NAS)-based multivariate calibration methods were employed for simultaneous determination of anthazoline and naphazoline. The NAS vectors calculated from the absorbance data of the drugs mixture were used as input for classical least squares (CLS), principal component and partial least squares regression PCR and PLS methods. A wavelength selection strategy was used to find the best wavelength region for each drug separately. As a new procedure, we proposed an experimental design-neural network strategy for wavelength region optimization. By use of a full factorial design method, some different wavelength regions were selected by taking into account different spectral parameters including the starting wavelength, the ending wavelength and the wavelength interval. The performance of all the multivariate calibration methods, in all selected wavelength regions for both drugs, was evaluated by calculating a fitness function based on the root mean square error of calibration and validation. A three-layered feed-forward artificial neural network (ANN) model with back-propagation learning algorithm was employed to model the nonlinear relationship between the spectral parameters and fitness of each regression method. From the resulted ANN models, the spectral regions in which lowest fitness could be obtained were chosen. Comparison of the results revealed that the net NAS-PLS resulted in lower prediction error than the other models. The proposed NAS-based calibration method was successfully applied to the simultaneous analyses of anthazoline and naphazoline in a commercial eye drop sample.     

Simultaneous determination of three fluoroquinolones by linear sweep stripping voltammetry with the aid of chemometrics

A linear sweep stripping voltammetric (LSSV) method has been researched and developed for simultaneous quantitative determination of mixtures of three antibiotic drugs, ofloxacin, norfloxacin and ciprofloxacin. It relies on reductive reaction of the antibiotics at a mercury electrode in a Britton-Robinson buffer (pH 3.78). The voltammograms of these three compounds overlap strongly, and show non-linear character. Thus, it is difficult to analyse the compounds individually in their mixtures. In this work, chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN) were applied for the simultaneous determination of these compounds. The prediction performance of the calibration models constructed on the basis of these methods was compared. It was shown that satisfactory quantitative results were obtained with the use of the RBF-ANN calibration model relative prediction error (RPE_T) of 8.1% and an average recovery of 101%. This method is able to accommodate non-linear data quite well. The proposed analytical method based on LSSV was applied for the analysis of ofloxacin, norfloxacin and ciprofloxacin antibiotics in bird feedstuffs and their spiked samples, as well as in eye drops with satisfactory results.     

Simultaneous determination of phenobarbital and phenytoin in tablet preparations by multivariate spectrophotometric calibration

The use of multivariate spectrophotometric calibration for the simultaneous determination of the active components of antiepileptic tablets is presented. The resolution of binary mixtures of phenobarbital and phenytoin has been accomplished by using partial least squares (PLS-1) regression analysis. Although the components show an important degree of spectral overlap, they have been simultaneously determined with high accuracy, with no interference from tablet excipients. A comparison is presented with the related multivariate method of classical least squares (CLS) analysis, which is shown to yield less reliable results due to the severe spectral overlap presented by the studied compounds. A statistical measure for the spectral overlap is proposed.     

Simultaneous spectrophotometric determination of mercury and palladium with Thio-Michler's Ketone using partial least squares regression and orthogonal signal correction

A simple, novel and sensitive spectrophotometric method was described for simultaneous determination of mercury and palladium. The method is based on the complex formation of mercury and palladium with Thio-Michler's Ketone (TMK) at pH 3.5. All factors affecting on the sensitivity were optimized and the linear dynamic range for determination of mercury and palladium found. The simultaneous determination of mercury and palladium mixtures by using spectrophotometric method is a difficult problem, due to spectral interferences. By multivariate calibration methods such as partial least squares (PLS), it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction (OSC) is a preprocessing technique used for removing the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for PLS calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 360-660 nm range for 25 different mixtures of mercury and palladium. Calibration matrices were containing 0.025-1.60 and 0.05-0.50 microg mL(-1) of mercury and palladium, respectively. The RMSEP for mercury and palladium with OSC and without OSC were 0.013, 0.006 and 0.048, 0.030, respectively. This procedure allows the simultaneous determination of mercury and palladium in synthetic and real matrix samples good reliability of the determination.     

Spectrophotometric simultaneous determination of manganese(II) and iron(II) in pharmaceutical by orthogonal signal correction-partial least squares

The simultaneous determination of manganese(II) and iron(II) mixtures by using spectrophotometric methods is a difficult problem in analytical chemistry, due to spectral interferences. By multivariate calibration methods, such as partial least squares (PLS), it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction (OSC) is a preprocessing technique used to remove the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 450-600 nm range for 21 different mixtures of manganese(II) and iron(II). Calibration matrices were containing 0.05-1.2 and 0.1-2.3 microg mL(-1) Mn(II) and Fe(II), respectively. The RMSEP for manganese(II) and iron(II) with OSC and without OSC were 0.0316, 0.0291, and 0.0907, 0.115, respectively. This procedure allows the simultaneous determination of manganese(II) and iron(II) in synthetic and real matrix samples with good reliability of the determination.