Application of multivariate curve resolution alternating least squares (MCR-ALS) to the quantitative analysis of pharmaceutical and agricultural samples

Application of multivariate curve resolution alternating least squares (MCR-ALS), for the resolution and quantification of different analytes in different type of pharmaceutical and agricultural samples is shown. In particular, MCR-ALS is applied first to the UV spectrophotometric quantitative analysis of mixtures of commercial steroid drugs, and second to the near-infrared (NIR) spectrophotometric quantitative analysis of humidity and protein contents in forage cereal samples. Quantitative results obtained by MCR-ALS are compared to those obtained using the well established partial least squares regression (PLSR) multivariate calibration method.     

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 acidity and tautomeric constants and hydrogen bonding strength for a new Schiff base using hard modeling and multivariate curve resolution alternative least squares methods

The equilibria of a new Schiff base derived from 3,6-bis((aminoethyl)thio)pyridazine were studied spectrophotometrically with the aid of factor-analytical methods. Hard modeling program was used for determination of the acidity constants of the Schiff base in dimethylformamide (DMF)/water mixture (30:70 v/v). In this method acidity constant equations act as hard models and the score vectors obtained by decomposing of absorbance data matrix will be linear combinations of equilibrium concentrations of species that exist in the absorption matrix. Two rank annihilation factor analysis (TRAFA) was used as a standard method to investigate the accuracy of the method. The tautomerization constant, K_t, of the Schiff base solution in various DMF/water mixtures has also been determined using spectral variations of the Schiff base solutions in various volume ratios of water with the aid of evolving factor analysis (EFA) and multivariate curve resolution alternative least squares (MCR-ALS) methods. In addition the intramolecular hydrogen bonding strength and its related thermodynamic parameters have been determined using MCR-ALS and spectral variation of the Schiff base solutions in different temperatures.     

Comparison of voltammetric detection assisted by multivariate curve resolution with amperometric detection in liquid chromatographic analysis of cysteine-containing compounds

A voltammetric detection mode (VD) in conjunction with multivariate curve resolution with alternating least squares (MCR-ALS) method is applied to the analysis of cysteine-containing compounds and compared with a well established amperometric detection (AD) mode in a thin-layer dual Hg/Au cell. VD-MCR-ALS provides an increase in selectivity for cases where satisfactory separation of electroactive compounds is not allowed. However, concentrations needed for a good quantification in VD are higher than in AD due to much large contribution of background in VD.     

PARAFAC and MCR-ALS applied to the quantitative monitoring of the photodegradation process of polycyclic aromatic hydrocarbons using three-dimensional excitation emission fluorescent spectra: Comparative results with HPLC

Two methods were developed for the simultaneous quantitative monitoring of photodegradation process of dibenz[a,h]anthracene (DibA), benz[a]anthracene (BaA), benz[a]pyrene (BaP) and benz[k]fluorantene (BkF) using excitation-emission fluorescence spectroscopy. Parallel factor analysis (PARAFAC) and multivariate curve resolution-alternating least squares (MCR-ALS) were satisfactory applied to the data obtained during this process. The results achieved were statistically compared by means of the joint interval test of slope and intercept, with the data obtained using the reference methodology, high performance liquid chromatography (HPLC) method. There are not significant differences between the methodologies proposed and the standard one, and may be a good alternative to the traditional methods of analysis for monitoring the degradation of these pollutants.     

多元曲线分辨-交替最小二乘方法在联用数据分辨中的应用

通过对模拟数据和高效毛细管电泳实验数据的分析,讨论了多元曲线分辨-交替最小二乘方法(MCR-ALS)在毛细管电泳-二极管阵列检测(CE-DAD)联用数据分辨中的应用.讨论了几种因素对MCR-ALS单个数据矩阵分辨结果的影响,包括待分析物光谱间的相似程度、浓度曲线的重叠程度以及由渐进因子分析(EFA)所得到的浓度初始值等.MCR-ALS还可用于多个数据矩阵的同时分析,即二阶MCR-ALS.结果表明,与一阶MCR-ALS相比,二阶MCR-ALS方法能够更好地解决各种分辨问题,得到合理和满意的分辨结果.     

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.     

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.     

Chemometric methods for the simultaneous determination of some water-soluble vitamins

Two spectrophotometric methods, derivative and multivariate methods, were applied for the determination of binary, ternary, and quaternary mixtures of the water-soluble vitamins thiamine HCI (I), pyridoxine HCI (II), riboflavin (III), and cyanocobalamin (IV). The first method is divided into first derivative and first derivative of ratio spectra methods, and the second into classical least squares and principal components regression methods. Both methods are based on spectrophotometric measurements of the studied vitamins in 0.1 M HCl solution in the range of 200-500 nm for all components. The linear calibration curves were obtained from 2.5-90 microg/mL, and the correlation coefficients ranged from 0.9991 to 0.9999. These methods were applied for the analysis of the following mixtures: (I) and (II); (I), (II), and (III); (I), (II), and (IV); and (I), (II), (III), and (IV). The described methods were successfully applied for the determination of vitamin combinations in synthetic mixtures and dosage forms from different manufacturers. The recovery ranged from 96.1 +/- 1.2 to 101.2 +/- 1.0% for derivative methods and 97.0 +/- 0.5 to 101.9 +/- 1.3% for multivariate methods. The results of the developed methods were compared with those of reported methods, and gave good accuracy and precision.     

Kinetic approach for the enzymatic determination of levodopa and carbidopa assisted by multivariate curve resolution-alternating least squares

A combination of kinetic spectroscopic monitoring and multivariate curve resolution-alternating least squares (MCR-ALS) was proposed for the enzymatic determination of levodopa (LVD) and carbidopa (CBD) in pharmaceuticals. The enzymatic reaction process was carried out in a reverse stopped-flow injection system and monitored by UV-vis spectroscopy. The spectra (292-600 nm) were recorded throughout the reaction and were analyzed by multivariate curve resolution-alternating least squares. A small calibration matrix containing nine mixtures was used in the model construction. Additionally, to evaluate the prediction ability of the model, a set with six validation mixtures was used. The lack of fit obtained was 4.3%, the explained variance 99.8% and the overall prediction error 5.5%. Tablets of commercial samples were analyzed and the results were validated by pharmacopeia method (high performance liquid chromatography). No significant differences were found (α = 0.05) between the reference values and the ones obtained with the proposed method. It is important to note that a unique chemometric model made it possible to determine both analytes simultaneously.     

Application of Multivariate Calibration Methods for the Simultaneous Multiwavelength Spectrophotometric Determination of Fe(II), Cu(II), Zn(II), and Mn(II) in Mixtures

Abstract

A sensitive method for the simultaneous spectrophotometric determination of Fe(II), Cu(II), Zn(II), and Mn(II) in mixtures has been developed with the aid of multivariate calibration methods, such as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS). The method is based on the spectral differences of the analytes in their complexation reaction with 4‐(2‐pyridylazo)‐resorcinol (PAR) and the use of full spectra with wavelengths in the range of 300–600 nm. It was found that both the spectral positive and negative bands obtained against the PAR blank, are proportional to the concentration for each metal complex. The obtained linear calibration concentration ranges are 0.025–0.6, 0.05–0.8, 0.025–0.8, and 0.05–0.8 µg ml^?1 for Fe(II), Cu(II), Zn(II), and Mn(II), respectively, and the LODs for the four metal ions were found to be approximately 1–3×10^?2 µg ml^?1. The proposed method was applied to a verification set of synthetic mixtures of these four metal ions, with models built in three different wavelength ranges, i.e., 300–450, 450–600, and 300–600 nm, corresponding to the positive, negative bands and their combinations, respectively. It was shown that the PLS model for the 300–600 nm range gave the best results (RPE_T=6.9% and average recovery ～100%; cf. PCR: RPE_T=9.5% and average Recovery ～110%). This method was also successfully applied for the determination of the four metal ions in pharmaceutical preparations, chicken feedstuff, and water samples.     

New strategy to identify radicals in a time evolving EPR data set by multivariate curve resolution-alternating least squares

Electron paramagnetic resonance (EPR) spectroscopy is a powerful technique that is able to characterize radicals formed in kinetic reactions. However, spectral characterization of individual chemical species is often limited or even unmanageable due to the severe kinetic and spectral overlap among species in kinetic processes. Therefore, we applied, for the first time, multivariate curve resolution-alternating least squares (MCR-ALS) method to EPR time evolving data sets to model and characterize the different constituents in a kinetic reaction. Here we demonstrate the advantage of multivariate analysis in the investigation of radicals formed along the kinetic process of hydroxycoumarin in alkaline medium. Multiset analysis of several EPR-monitored kinetic experiments performed in different conditions revealed the individual paramagnetic centres as well as their kinetic profiles. The results obtained by MCR-ALS method demonstrate its prominent potential in analysis of EPR time evolved spectra.     

Application of multivariate curve resolution-alternating least squares for the determination of boron isotope ratios by inductively coupled plasma-optical emission spectrometry

Multivariate curve resolution-alternating least squares (MCR-ALS) was applied to atomic emission data obtained from inductively coupled plasma-optical emission spectrometry analysis of boron for the quantification of ¹⁰B/¹¹B ratios. The determination of isotopic composition of boron is based on the isotopic shift of ¹⁰B and ¹¹B in the emission line of 208.957 nm. After recording of the emission spectra in the range of 208.940–208.970 nm, evaluation of isotopic composition of boron containing samples was performed with MCR-ALS algorithm. MCR-ALS was able to resolve the emission spectra of ¹⁰B and ¹¹B mixtures. The performance of the proposed methods was tested by determination of ¹⁰B/¹¹B ratios in synthetic mixtures and also water samples.     

荧光光谱结合多元曲线分辨-交替最小二乘法研究十二烷基三甲基溴化铵与牛血清白蛋白的相互作用

模拟pH=7.4的人体生理条件,用荧光光谱法结合多元曲线分辨-交替最小二乘法(MCR-ALS),研究表面活性剂十二烷基三甲基溴化铵(CTAB)与牛血清白蛋白(BSA)的相互作用。为增加实验数据的信息量,本实验采用顺序不同的两种滴加方式得到扩展的荧光光谱数据矩阵;进而采用渐进因子分析法(EFA)得到作用体系中各组分浓度变化曲线的初值,再应用MCR-ALS对该扩展荧光光谱矩阵进行迭代计算,较好地分辨出动态作用中各种物质的浓度变化趋势图,并由此曲线推断出CTAB与BSA的表观结合常数和结合比。     

Resolution of overlapping capillary electrophoresis peaks by using chemometric analysis: quantification of the components in compound reserpine tablets

The application of multivariate curve resolution with alternating least squares (MCR-ALS) methods to second-order data from capillary electrophoresis with diode array detector (CE-DAD) is reported. Initial qualitative solutions obtained by evolving factor analysis (EFA) and pure-variable detection method can be further optimized by a simultaneous analysis of multiple electrophoresis run data with ALS regression. While unknown samples are analyzed simultaneously against the corresponding standards in different composition ratios, the exact amounts of common components in different CE runs can be determined by the traditional calibration curve method, and quantification can thus be achieved. The above methods are applied to the determination of the components in compound reserpine tablets in overlapping peaks from CE. The quantification results are compared with those of the first derivative of the electropherogram method and artificial neural network (ANN) 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     

Rank analysis and simultaneous determination of acetylsalicylic acid,paracetamol, and caffeine in pharmaceuticals using second-order data and multivariate curve resolution-alternating least squares (MCR-ALS)

Mixtures of acetylsalicylic acid (ASA), paracetamol (PAR), and caffeine (CAF) have been successfully analyzed by constrained multivariate curve resolution-alternating least squares (MCR-ALS). The MCR-ALS methodology adequately exploits the second-order advantage which enables quantitation of analyte in the presence of unknown and uncalibrated interferences. The procedure simultaneously takes into account the spectroscopic and pH-dependent properties of the compounds, which leads to a higher selectivity. Specially, for CAF determination fully protonated or deprotonated forms of CAF are not dominant in the pH range of data acquisition but spectral changes with pH were recorded and used for accurate determination of CAF. Furthermore, quantitative determination of an analyte in a complex mixture is performed using a synthetic solution as standard containing only the analyte of interest. Even in the presence of the rank deficiencies, in most cases accurate quantitation with relative errors in prediction lower than 5 % was obtained. The procedure was successfully applied to the analysis of real samples (pharmaceuticals) using synthetic external standards. Percent relative errors of 4.03, 3.26, and 5.85 were obtained for ASA, PAR, and CAF, respectively, in A.C.A tablets and 4.49 and 2.75 for PAR and CAF, respectively in Novafen capsules.     

多元曲线分辨-交替最小二乘法应用于延胡索药材指纹图谱中重叠峰分辨及延胡索乙素的含量测定

采用光谱相关色谱法对延胡索药材指纹图谱中的有效组分延胡索乙素峰进行确认;利用多元曲线分辨 交替最小二乘法（MCR-ALS）对延胡索乙素重叠峰簇进行解析,得到延胡索乙素的真实色谱峰,其光谱还原率大于0.999,并对其进行准确定量,该方法可作为指纹图谱的辅助方法,为中药的真伪鉴定和质量客观评价提供可靠依据;最后讨论了药材的炮制对延胡索乙素含量的影响。     

Solving liquid chromatography mass spectrometry coelution problems in the analysis of environmental samples by multivariate curve resolution

Multivariate curve resolution-alternating least squares (MCR-ALS) is shown to be a powerful tool to resolve coelution problems in liquid chromatograpy-mass spectrometry (LC-MS) in scan mode. This investigation was performed using two types of LC columns, one traditional LC column of 25 cm length with a slow gradient and a shorter LC column of 7.5 cm with a rapid gradient which allowed much faster analysis and save of reagents and solvents. Mixtures of multiple biocide compounds were simultaneously analyzed in standard mixtures and in environmental samples (sediment and wastewater samples) with little sample pretreatment. Using the more traditional LC 25 cm column, all biocide compounds were properly resolved by MCR-ALS and quantitatively analyzed with estimated errors always below 20%. When fast chromatography (LC column of 7.5 cm) was used, MCR-ALS resolution of the more strongly coeluted compounds was also achieved but limitations were found in their simultaneous quantitative determination, specially for environmental samples.     

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.