Simultaneous spectrophotometric determination of drugs in pharmaceutical preparations using multiple linear regression and partial least-squares regression, calibration and prediction methods

Two new methods for the simultaneous determination of acetylsalicylic acid, acetaminophen and caffeine based on total absorbance measurements and their processing by multiple linear regession and partial least-squares regression are proposed. The concentration ranges used to construct the calibration matrix were 4.0-12.0, 2.0-10.0 and 0.9-6.0 μg ml⁻¹ for acetylsalicylic acid, acetaminophen and caffeine respectively. The proposed methods were validated by using a set of synthetic sample mixtures and subsequently applied to the determination of the three active principles in three different pharmaceutical preparations.     

Kinetic-spectrophotometric determination of theophylline,dyphylline, and proxyphylline by use of partial least-squares regression

A kinetic-spectrophotometric method for the determination of theophylline, dyphylline and proxyphylline, based on their azo coupling reaction with the diazonium ion of sulfanilic acid after a treatment with alkali, is proposed. The absorbance is recorded from 340 to 600 nm every second during reaction for 90 s, and calibration is performed by partial least-squares regression, using first derivative spectra values. Mixtures containing 2.5-13 micro g mL(-1) dyphylline and proxyphylline, and 2-9 micro g mL(-1) theophylline were successfully resolved with root mean squared errors of prediction (RMSEP) of 0.4, 0.3, and 0.2 for dyphylline, proxyphylline, and theophylline, respectively. The proposed method was satisfactorily applied to the determination of the three compounds in a commercially available pharmaceutical preparation and provided results similar to those obtained by HPLC.     

Comparison of mathemical methods for the calculation of retention indices at high temperature in gas chromatography

The retention indices of three homologous series (2-alkanones, 1-alkanols, cycloalksanones) have been determined at high temperature by the application of two new adaptation methods: A multiparametric least-squares regressions iterative method based on the dertermination of the adjusted retention times and a cubic interpolation directly using the uncorrected retention times without dead time correction. The two methods were applied to two types of columns. The first group includes eight packed columns (seven OV polymethylphenylsiloxane and Apolane-87 stationary phases), while the second includes five glass capillary columns (four methyl-silicons with different film thicknesses and Apolane-87 stationary phases). The retention indices obtained with a multiparametric and a cubic interpolation methods were compared with each other and with those calculated by Grobler's, Guardino's, Kaiser's and Kovàts' methods. The influence of coating, film thickness, and temperature on them was investigated.     

Three-way partial least-squares regression for the simultaneous kinetic-enzymatic determination of xanthine and hypoxanthine in human urine

The performance of three-way principal component analysis and three-way partial least-squares regression when applied to a complex kinetic-enzymatic system is studied, in order to investigate the analytical potential of the combined use of these chemometric technologies for non-selective enzymatic systems. A enzymatic-kinetic procedure for the simultaneous determination of hypoxanthine and xanthine in spiked samples of human urine is proposed. The chemical system involves two consecutive reactions catalyzed by xanthine oxidase (EC 1.17.3.2). This enzyme catalyzes the oxidation of hypoxanthine, first to xanthine and then to uric acid, a competitive inhibitor of the reactions. The influence of uric acid during quantitative determination was considered in the design of the calibration set. The sample and enzyme solution were mixed in a stopped-flow module and the reaction was monitored using a diode array spectrophotometer. The recorded data have an intrinsical three-component structure (samples, time and wavelength). This data array was studied via three-way principal component analysis and was modeled for quantitative purposes using a three-way partial least-squares calibration procedure. Results are compared with those obtained by applying classical bilinear PLS to the previously unfolded data matrix.     

Mass spectrometry and partial least-squares regression: a tool for identification of wheat variety and end-use quality

Rapid methods for the identification of wheat varieties and their end-use quality have been developed. The methods combine the analysis of wheat protein extracts by mass spectrometry with partial least-squares regression in order to predict the variety or end-use quality of unknown wheat samples. The whole process takes approximately 30 min. Extracts of alcohol-soluble storage proteins (gliadins) from wheat were analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Partial least-squares regression was subsequently applied using these mass spectra for making models that could predict the wheat variety or end-use quality. Previously, an artificial neural network was used to identify wheat varieties based on their protein mass spectra profiles. The present study showed that partial least-squares regression is at least as useful as neural networks for this identification. Furthermore, it was demonstrated that partial least-squares regression could be used to predict wheat end-use quality, which has not been possible using neural networks.     

Structural characterization and prediction of Kovats retention indices (RI) for alkylbenzene compounds

A new molecular structural characterization (MSC) method called the molecular vertex eigenvalue correlative index (MVECI) is constructed and used to describe the structures of 122 alkylbenzene compounds. Through multiple linear regression (MLR) and stepwise multiple regression (SMR), a quantitative structure-retention relationship (QSRR) model with correlation coefficient (R) of 0.995 is obtained. Through partial least-square regression (PLS), another QSRR model with correlation coefficient (R) of 0.991 is obtained. The estimation stability and prediction ability of the two models are strictly analyzed by both internal and external validations. For the internal validation, the cross-validation (CV) correlation coefficients (R _CV) of the two models are 0.993 and 0.988. For the external validation, the correlation coefficients (R _test) of the two models are 0.996 and 0.995, respectively. The results show that the stability and predictability of the models are good, and the molecular vertex eigenvalue correlative index can successfully describe the structures of alkylbenzene compounds.     

UV partial least-squares calibration and liquid chromatographic methods for direct quantitation of levofloxacin in urine

Levofloxacin was determined in human urine samples by application of a spectrophotometric multivariate calibration partial least-squares (PLS-1) method. A calibration set consisting of standards was prepared by using a multilevel multifactor experimental design. In order to ensure accurate results, the calibration matrix included a urine sample free of levofloxacin (i.e., urine blank). The components of the calibration matrix were levofloxacin and urine. The concentration of levofloxacin ranged from 0.5 to 16.5 microg/mL. Different urine concentrations were used as the second component of the calibration matrix in order to include the information inherent in the changes in the UV spectrum for urine upon dilution. In addition, a high-performance liquid chromatographic method was proposed. In this method, a Shim-pack amino column was used at ambient temperature with a mobile phase of 25 mM potassium dihydrogen phosphate (pH adjusted to 3.1 with phosphoric acid)-acetonitrile (70 + 30, v/v), and the flow rate was 1 mL/min. UV detection at 293 nm was used for quantitation. The proposed methods were applied to the determination of the dissolution rate for tablets containing levofloxacin. The urinary excretion pattern for the cumulative amount of levoflacin excreted was also calculated.     

Comparison of localization and delocalization indices obtained with Hartree-Fock and conventional correlated methods: effect of Coulomb correlation

Atomic populations and localization [lambda(A)] and delocalization [delta(A,B)] indices (LIs and DIs) are calculated for a large set of molecules at the Hartree-Fock (HF), MP2, MP4(SDQ), CISD, and QCISD levels with the 6-311++G(2d,2p) basis set. The HF method and the conventional correlation methods [MP2, MP4(SDQ), CISD, and QCISD] yield distinct sets of LIs and DIs. Yet, within the four conventional correlation methods the differences in atomic populations and LIs and DIs are small. Relative to HF, the conventional correlation methods [MP2, MP4(SDQ), CISD, QCISD] yield virtually the same LIs and DIs for molecules with large charge separations while LIs and DIs that differ significantly from the HF values--the LIs are increased and DIs decreased--are obtained for bonds with no or small charge separations. Such is the case in the archetypal homopolar molecules HC(triple bond)CH, H2C=CH2, CH3-CH3, and "protonated cyclopropane" C(3)H(7) (+), in which case the bonding may be atypical. Relative to HF, the typical effect of the conventional correlation methods is to decrease the DI between atoms.     

Comparison between different data pre-treatment methods in the analysis of forage samples using near-infrared diffuse reflectance spectroscopy and partial least-squares multivariate calibration method

Moisture and protein content of alfalfa samples from Catalonia (Spain) have been analyzed by near-infrared (NIR) diffuse reflectance spectroscopy and multivariate calibration methods. In order to remove systematic variation in experimental data, such as base-line and multiplicative scatter effects, the evaluation of different data pre-processing methods is performed. Different figures of merit are used for quality assessment and comparison of these pre-treatment methods.     

Use of partial least-squares regression for multicomponent determinations based on kinetic spectrofluorimetric data. Simultaneous determination of canrenone and spironolactone in urine

A new spectrofluorimetric method for the simultaneous determination of canrenone and spironolactone in urine is proposed. The method is based on the different rates at which the two analytes react with hot sulfuric acid to form a trienone. The kinetic spectrofluorimetric data are processed by partial least-squares regression. The effects of sulfuric acid concentration and temperature on the system under study were also evaluated and the optimum values for carring out the reaction were 50% and 50 degrees C, respectively. The method was checked by analyzing urine samples that they contained both diuretics. The accuracy and the precision of the method were tested. The relative standard errors in the quantification of each analyte in all tested samples were 3.69 and 3.59%. The proposed method was validated by comparison with a high performance liquid chromatographic method for urine samples.     

Simultaneous determination of human serum albumin, gamma-globulin, and glucose in a phosphate buffer solution by near-infrared spectroscopy with moving window partial least-squares regression

Near-infrared (NIR) spectra in the 12,000-4,000 cm(-1) region were measured for phosphate buffer solutions containing human serum albumin (HSA), gamma-globulin, and glucose with various concentrations at 37 degrees C. Five levels of full factorial design were used to prepare a sample set consisting of 125 samples of three component mixtures. The concentration ranges of HSA, gamma-globulin and glucose were 0.00-6.00 g dl(-1), 0.00-4.00 g dl(-1) and 0.00-2.00 g dl(-1), respectively. The 125 sample data were split into two sets, the calibration set with 95 data and the prediction set with 30 data. The most informative spectral ranges of 4648-4323, 4647-4255 and 4912-4304 cm(-1) were selected by moving window partial least-squares regression (MWPLSR) for HSA, [gamma]-globulin, and glucose in the mixtures, respectively. For HSA, the correlation coefficient (R) of 0.9998 and the root mean square error of prediction (RMSEP) of 0.0289 g dl(-1) were obtained. For [gamma]-globulin, R of 0.9997 and RMSEP of 0.0252 g dl(-1) were obtained. The corresponding statistic values of glucose were 0.9997 and 0.0156 g dl(-1), respectively. These statistical values obtained by MWPLSR are highly significant and better than those calculated by using the regions reported in the literature. The results presented here show that MWPLSR can select the informative regions with a simple procedure and increase the power of NIR spectroscopy for simultaneous determination of the concentrations of HSA, [gamma]-globulin and glucose in the mixture systems.     

Comparison of prediction methods for the uptake of As,Cd and Pb in carrot and lettuce

The New Model Framework (NMF) for uptake into crops is based on particle deposition and Transfer factors from soil to plant calculated from the BAse de données sur les teneurs en Eléments Traces métalliques de Plantes Potagères (BAPPET) database. Besides NMF, approaches developed by the National Institute of Public Health and the Environment (RIVM), Hough, and the United States Environmental Protection Agency (US EPA), and the Contaminated Land Exposure Assessment (CLEA) approach were tested. Experimental data were assembled from the BAPPET database and Danish background data of As, Cd and Pb in soil, air and crops was collected. None of the models proved able to estimate the measured concentrations in plants from the BAPPET database with an absolute normalized error smaller than 70%. On average, the predictions had an error of 80–250%. However, when applying the models to the rural Danish background scenario, the NMF and other models predicted the concentrations in carrot and lettuce within the range of measured values. Regressions considering soil pH, organic matter and clay content were not superior to simple transfer factors. The transfer from air to plant is significant, at least under background conditions, and should be considered in the prediction methods.     

Comparison of UV derivative-spectrophotometry and partial least-squares (PLS-1) calibration for determination of methotrexate and leucovorin in biological fluids

Binary mixtures of methotrexate (MTX) and leucovorin (LV) have been resolved by application of first-derivative spectrophotometry and partial least squares calibration (PLS-1). By measuring the first-derivative signals of MTX and LV at 354 and 300 nm, respectively, simultaneous determination was possible. The mean recoveries for urine samples were 91 and 96% for MTX and LV, respectively. Partial least squares (PLS-1) multivariate calibration has been applied to the determination of these compounds in serum and in urine without pretreatment of the samples. The absorption spectra of serum or urine samples spiked with methotrexate and/or leucovorin, were used to optimize the calibration matrixes by the PLS-1 method. The sensitivity and selectivity of the proposed procedures were calculated. Mean recoveries were 101 and 97% for MTX and LV, respectively, for serum samples, and 101 and 98% for MTX and LV, respectively, for urine samples.     

Comparison of HPLC and multivariate regression methods for hydrocortisone and lidocaine analysis of pharmaceutical preparations

A reverse-phase high-performance liquid chromatographic (HPLC) method to determine hydrocortisone acetate, hydrocortisone hemisuccinate and lidocaine is described in this paper. The separation was made in a LichrCART C(18) column using a methanol-NaH(2)PO(4)/Na(2)HPO(4) (0.1 mol L(-1)) (pH=4.5) buffer solution as a mobile phase in isocratic mode (60:40 (v/v)). The mobile phase flow rate and the sample volume injected were 1 mL min(-1) and 20 micro L, respectively. The detection was made with a diode-array detector measuring at the maximum for each compound. Quantification limits ranging from 0.18 to 0.84 micro g L(-1) were obtained when the peak area was measured. The method was applied in pharmaceutical formulations that were compared with those obtained by through multivariate regression spectrophotometry and micellar capillary electrophoresis (MEKC). HPLC results are in accordance with the results obtained by MEKC. The spectrophotometric method was suitable only for synthetic samples.