Hybrid Linear Analysis Research Articles

Spectrophotometric resolution of ternary mixtures of pseudoephedrine hydrochloride, dextromethorphan hydrobromide, and sodium benzoate in syrups using wavelength selection by net analyte signals calculated with hybrid linear analysis

Hybrid linear analysis (HLA), as a recent factor-based multivariate calibration technique, was applied for the spectrophotometric determination of ternary mixtures of pseudoephedrine hydrochloride (PSU), dextromethorphan hydrobromide (DXT), and sodium benzoate (BNZ). The utilized HLA was assisted by a wavelength selection procedure which was based on the calculation of the net analyte signal (NAS) regression plot in any considered wavelengths window for each test sample, in addition to a moving window strategy for searching the region with maximum linearity of NAS regression plot (minimum error indicator (EI)). HLA was applied because it was simpler to adapt to the NAS regression plot methodology, and also used less factors than partial least squares (PLS). An orthogonal array design was applied for formation of calibration and prediction sets in the concentration ranges 0–7500 μmol L −1 for PSU, 0–300 μmol L −1 for DXT, and 0–1400 μmol L −1 for BNZ. The method had the ability to select wavelength regions that minimize the effect of non-linearity of the spectral data, in addition to that of non-modeled interferences. The application of the selected wavelength regions improved the obtained relative standard error of predictions for PSU, DXT, and BNZ, respectively, from 5.24, 8.67, and 5.48% to 2.19, 5.21, and 3.62% (using lower number of factors). To check the ability of the proposed method in selection of linear regions of spectra, a test for detecting non-linear regions of spectral data in multivariate spectroscopic assays was also described. Additives in the commercial syrup samples did not interfere with their determinations. The method was successfully applied for the determination of pseudoephedrine HCl, dextromethorphan HBr, and sodium benzoate in cough suppressant syrup samples.

Spectrophotometric determination of sorbic and benzoic acids in fruit juices by a net analyte signal-based method with selection of the wavelength range to avoid non-modelled interferences.

Sorbic (SOR) and benzoic (BEN) acids were determined in fruit juice samples by using a net analyte signal-based methodology named HLA/GO (an hybrid linear analysis presented by Goicoechea and Olivieri) applied to spectroscopic signals. The calibration set was built with several fruit juices in order to take into account the natural variability and concentrations of both analytes covering the range usually present in commercial samples. Relative errors of prediction (REP %) of 3.6 and 5.2% were calculated for SOR and BEN respectively. Several figures of merit were calculated-sensitivity, selectivity, analytical sensitivity, and limit of detection. The method is quantitative, with reasonably good recoveries and excellent precision (less than 1%). Wavelength selection was applied, based on the concept of net analyte signal regression, and it allowed us to improve the method performance in samples containing non-modelled interferences, e.g. fruit juices different to those used to build the calibration model.

Determination of carbendazim, thiabendazole and fuberidazole using a net analyte signal-based method

The net analyte signal (NAS)-based method HLA/GO, modification of the original hybrid linear analysis (HLA) method, has been used to determine carbendazim, fuberidazole and thiabendazole in water samples. This approach was used after a solid-phase extraction (SPE) step, using the native fluorescence emission spectra of real samples, previously standardized by piecewise direct standardization (PDS). The results obtained show that the modification of HLA performs in a similar way that partial least-squares method (PLS-1). The NAS concept was also used to calculate multivariate analytical figures of merit such as limit of detection, selectivity, sensitivity and analytical sensitivity ( γ −1). With this purpose, blanks of methanol and ternary mixtures, with the target analyte at low concentration and the other two ranging according to the calibration matrix, were used, with different results. Detection limits calculated in the last way are more realistic and show the influence of the other components in the sample. Selectivity for carbendazim is higher than the corresponding values for fuberidazole and thiabendazole, whereas sensitivity, as well as the values obtained for their detection limits, are lower for carbendazim, followed by thiabendazole and fuberidazole. Results obtained by modification of HLA vary in the same way that the ones obtained by PLS-1.

Selection of the wavelength range and spectrophotometric determination of leucovorin and methotrexate in human serum by a net analyte signal based method

Leucovorin (LV) and methotrexate (MTX) were determined in human blood serum samples by using a model based in the net analytical signal concept. The calibration method used is a variation of the original hybrid linear analysis (HLA) method, developed by Goicoechea and Olivieri (HLA/GO). The calibration set was composed by nine serum samples with different amounts of LV and MTX in the range of 0–10 μg ml −1. The selection of the optimum wavelength range involved the calculation of the net analyte signal regression plot for each test sample, in conjunction with the calculation of the minimum error indicator. Relative errors of prediction (REP, %) of 3.0 and 5.3% were calculated for LV and MTX, respectively. Only two factors were necessary to optimize the proposed HLA/GO model. Sensitivity, selectivity, analytical sensitivity and limit of detection of the proposed procedure were calculated. Detection limits of 0.34 and 0.93 μg ml −1 for LV and MTX were determined. The proposed model was tested in the analysis of serum samples, without previous separation steps, obtaining recovery values between 96 and 99%, and between 92 and 103% for LV and MTX, respectively.

Comparative study of net analyte signal-based methods and partial least squares for the simultaneous determination of amoxycillin and clavulanic acid by stopped-flow kinetic analysis

A comparative study about advantages and limitations of net analyte signal (NAS)-based methods (NBMs) and partial least squares (PLS) calibration in kinetic analysis has been performed. The different multivariate calibration methods were applied to the determination of binary mixtures of amoxycillin and clavulanic acid, by stopped-flow kinetic analysis. The reactions of oxidation of these compounds with cerium(IV), in sulphuric acid medium, were monitored by following the changes on the fluorescence of the oxidation products, in stopped-flow mode. The differences on the kinetic profiles obtained at λ ex=256 nm and λ em=351 nm, were used to determine mixtures of both compounds by multivariate calibration of the kinetic data, using PLS-1, a modification of hybrid linear analysis (HLA) and net analyte pre-processing combined with classical least squares (NAP/CLS) methods. The NBMs allowed the selection of optimal time data regions by calculating the minimum error indicator function (EIF), improving the results and making NBMs very convenient for the analysis. In addition, the use of the net analyte signal concept allows the calculation of the analytical figures of merit, limit of detection (LOD), sensitivity and selectivity, for each component.

Chemometric assisted simultaneous spectrophotometric determination of four-component nasal solutions with a reduced number of calibration samples

The use of multivariate spectrophotometric calibration for the simultaneous determination of three active components and one excipient in nasal solutions is presented. The resolution of four-component mixtures of phenylephrine, diphenhydramine, naphazoline and methylparaben in a matrix of excipients has been accomplished by using partial least-squares (PLS-1) and a variant of the so-called hybrid linear analysis (HLA) named net analyte preprocessing (NAP). Notwithstanding the presence of a large number of components and their high degree of spectral overlap, they have been rapidly and simultaneously determined with high accuracy and precision, with no interference, and without resorting to extraction procedures using non-aqueous solvents. A simple and fast method for wavelength selection in the calibration step is used, based on the minimisation of the predicted error sum of squares (PRESS) calculated as a function of a moving spectral window. The use of calibration designs of reduced size has been attempted. Satisfactory results were obtained when the number of calibration samples was reduced from 25 (full central composite) to 17 (fractional central composite) using the net analyte-based NAP method.

Simultaneous Fluorimetric Determination of Pteridin Derivatives: Comparison between Synchronous, Partial Least-Squares, and Hybrid Linear Analysis Methods

Several methods are described for the simultaneous determination of binary mixtures of xanthopterin (XAN) and isoxanthopterin (ISO) and of binary mixtures of xanthopterin and biopterin (BIO). The total luminiscence information from each compound has been used to optimize the most adequate analytical signal. A synchronous spectrofluorometric univariate procedure to analyze XAN and ISO is proposed. The procedure is compared with two multivariate procedures based on partial least-squares (PLS-1) and hybrid linear analysis (HLA/XS), by using synchronous spectral data as analytical signals. For the resolution of binary mixtures of XAN and BIO, a comparison between the predictive ability of the multivariate calibration methods, PLS-1 and HLA/XS, on two spectral data sets, excitation and emission spectra, has been performed. The calculation of the net analyte signal (NAS) by the HLA/XS method allows the determination of selectivity and sensitivity in each case. The proposed procedures are validated in the determination of several mixtures of these compounds, and the error values in a test set are reported.

Comparative study of partial least squares and a modification of hybrid linear analysis calibration in the simultaneous spectrophotometric determination of rifampicin, pyrazinamide and isoniazid

Two multivariate methods, the classical partial least squares (PLS-1) and a modification of the novel hybrid linear analysis (HLA/XS method), are described for the simultaneous determination of rifampicin, pyrazinamide and isoniazid. A calibration set is constructed, using a combined central composite and factorial design (15 objects), in the range of concentrations comprised between 0 and 15 μg/ml for rifampicin and pyrazinamide, and 0–10 μg/ml for isoniazid. The proposed methods are satisfactorily applied to the determination of mixtures of these drugs. The precision expressed as R.S.D. (%) is calculated for both models. HLA/XS and PLS optimized calibrations are tested and compared in the analysis of several pharmaceutical formulations. The calculation of the net analytical signal using a modified HLA/XS method, allows us the determination of several figures of merit, as selectivity, sensitivity, analytical sensitivity and limit of detection of the proposed multivariate calibration. PLS-1 and HLA/XS calibration show similar ability to determine rifampicin and pyrazinamide but slightly worse results for isoniazid are obtained when using HLA/XS.

Simultaneous spectrophotometric-multivariate calibration determination of several components of ophthalmic solutions: phenylephrine, chloramphenicol, antipyrine, methylparaben and thimerosal

The use of multivariate spectrophotometric calibration for the simultaneous determination of several active components and excipients in ophthalmic solutions is presented. The resolution of five-component mixtures of phenylephrine, chloramphenicol, antipyrine, methylparaben and thimerosal has been accomplished by using partial least-squares (PLS-1) and a variant of the so-called hybrid linear analysis (HLA). Notwithstanding the presence of a large number of components and their high degree of spectral overlap, they have been determined simultaneously with high accuracy and precision, with no interference, rapidly and without resorting to extraction procedures using non aqueous solvents. A simple and fast method for wavelength selection in the calibration step is presented, based on the minimisation of the predicted error sum of squares (PRESS) calculated as a function of a moving spectral window.

Numerical Pattern Recognition Analysis of CO Atmospheric Simulation Experiments

A technique entitled Hybrid Linear Pattern Analysis (HLPA), which represents a combination of model-based and pattern recognition-based approaches to the analysis of spectroscopic data, is introduced and applied to the analysis of time-resolved infrared emission spectra of ground electronic state (X1Σ+) CO obtained in atmospheric simulation experiments. The spectra are highly congested and consist of incompletely resolved, overlapping v‘ − v‘ ‘ = 1 emission bands from v‘ = 1 up to at least v‘ = 12. The analysis of the time dependence of the emission intensity in the various vibrational bands had been stymied by a severe optical opacity effect in the v = 1 → 0 emission, which is difficult to simulate; thus, conventional least-squares fitting could not be used confidently to determine the time-dependent emission intensity of this band, or that of at least three other emission bands that overlap strongly with it. The HLPA technique permits an alternate approach in which the v = 1 → 0 emission band is considered to be an unknown pattern that is identified by the Extended Cross Correlation (XCC) pattern recognition technique (J. Chem. Phys. 1997, 107, 8349). The intensity profiles of the other bands, however, can be predicted accurately based on the experimental parameters, and this knowledge is used in conjunction with the results of the XCC to determine the time dependence of all of the vibrational bands, and the intensity profile of the v = 1 → 0 emission band.

Determination of bromhexine in cough–cold syrups by absorption spectrophotometry and multivariate calibration using partial least-squares and hybrid linear analyses. Application of a novel method of wavelength selection

The mucolitic bromhexine [ N-(2-amino-3,5-dibromobenzyl)- N-methylcyclohexylamine] has been determined in cough suppressant syrups by multivariate spectrophotometric calibration, together with partial least-squares (PLS-1) and hybrid linear analysis (HLA). Notwithstanding the spectral overlapping between bromhexine and syrup excipients, as well as the intrinsic variability of the latter in unknown samples, the recoveries are excellent. A novel method of wavelength selection was also applied, based on the concept of net analyte signal regression, as adapted to the HLA methodology. This method allows one to improve the performance of both PLS-1 and HLA in samples containing nonmodeled interferences.

Wavelength selection by net analyte signals calculated with multivariate factor-based hybrid linear analysis (HLA). A theoretical and experimental comparison with partial least-squares (PLS)

A wavelength selection procedure is presented for the recently introduced factor-based multivariate calibration technique of hybrid linear analysis (HLA). It involves the calculation of the net analyte signal regression plot (NASRP) for each test sample, combined with a moving window strategy. A search for the minimum error indicator (EI) is performed using the first significant factors of a data matrix from which the contribution of the analyte of interest has been removed. HLA uses less factors than both principal component regression (PCR) and partial least-squares (PLS), and is simpler to adapt to the NASRP methodology. The ability of the method to select wavelength regions that minimize the effect of non-modeled interferences is illustrated both with simulated examples and with experimental bromhexine-containing cough suppressant syrup samples.

An enhanced algorithm for linear multivariate calibration.

We present a new method of linear multivariate calibration that can generate better prediction results than those obtained by partial least squares (PLS). This is accomplished by incorporating the spectrum of the desired species into the calibration procedure. The method combines the advantages of different standard methods and is therefore called hybrid linear analysis (HLA). In side-by-side tests using both simulated and experimental data, HLA produced lower prediction errors than PLS in all instances. We recommend HLA over PLS in situations where the spectrum of the desired species is available.