Aplicação de métodos de calibração multivariada para a determinação simultânea de riboflavina (VB2), tiamina (VB1), piridoxina (VB6) e nicotinamida (VPP)

In this work, the artificial neural networks (ANN) and partial least squares (PLS) regression were applied to UV spectral data for quantitative determination of thiamin hydrochloride (VB1), riboflavin phosphate (VB2), pyridoxine hydrochloride (VB6) and nicotinamide (VPP) in pharmaceutical samples. For calibration purposes, commercial samples in 0.2 mol L-1 acetate buffer (pH 4.0) were employed as standards. The concentration ranges used in the calibration step were: 0.1 - 7.5 mg L-1 for VB1, 0.1 - 3.0 mg L-1 for VB2, 0.1 - 3.0 mg L-1 for VB6 and 0.4 - 30.0 mg L-1 for VPP. From the results it is possible to verify that both methods can be successfully applied for these determinations. The similar error values were obtained by using neural network or PLS methods. The proposed methodology is simple, rapid and can be easily used in quality control laboratories.

Estado da arte de figuras de mérito em calibração multivariada

The validation of an analytical procedure must be certified through the determination of parameters known as figures of merit. For first order data, the acuracy, precision, robustness and bias is similar to the methods of univariate calibration. Linearity, sensitivity, signal to noise ratio, adjustment, selectivity and confidence intervals need different approaches, specific for multivariate data. Selectivity and signal to noise ratio are more critical and they only can be estimated by means of the calculation of the net analyte signal. In second order calibration, some differentes approaches are necessary due to data structure.

Calibração multivariada para sistemas com bandas sobrepostas através da análise da fatores do tipo Q

A multivariate calibration method to determine chemical compositions of systems with severely overlapped bands is proposed. Q mode factors are determined from the spectral data and subsequently rotated using the varimax and oblique transformation of Imbrie. The method is applied to two sets of simulated data to test the sensitivity of analytical results to random experimental error. The chemical concentrations of alanine and threonine mixture are determined from spectral data of the 302,5 - 548,5 nm region.

Quimiometria I: calibração multivariada, um tutorial

The aim of this work is to present a tutorial on Multivariate Calibration, a tool which is nowadays necessary in basically most laboratories but very often misused. The basic concepts of preprocessing, principal component analysis (PCA), principal component regression (PCR) and partial least squares (PLS) are given. The two basic steps on any calibration procedure: model building and validation are fully discussed. The concepts of cross validation (to determine the number of factors to be used in the model), leverage and studentized residuals (to detect outliers) for the validation step are given. The whole calibration procedure is illustrated using spectra recorded for ternary mixtures of 2,4,6 trinitrophenolate, 2,4 dinitrophenolate and 2,5 dinitrophenolate followed by the concentration prediction of these three chemical species during a diffusion experiment through a hydrophobic liquid membrane. MATLAB software is used for numerical calculations. Most of the commands for the analysis are provided in order to allow a non-specialist to follow step by step the analysis.

Redes neurais e suas aplicações em calibração multivariada

Neural Networks are a set of mathematical methods and computer programs designed to simulate the information process and the knowledge acquisition of the human brain. In last years its application in chemistry is increasing significantly, due the special characteristics for model complex systems. The basic principles of two types of neural networks, the multi-layer perceptrons and radial basis functions, are introduced, as well as, a pruning approach to architecture optimization. Two analytical applications based on near infrared spectroscopy are presented, the first one for determination of nitrogen content in wheat leaves using multi-layer perceptrons networks and second one for determination of BRIX in sugar cane juices using radial basis functions networks.

Validação de modelos de calibração multivariada: uma aplicação na determinação de pureza polimórfica de carbamazepina por espectroscopia no infravermelho próximo

The application of analytical procedures based on multivariate calibration models has been limited in several areas due to requirements of validation and certification of the model. Procedures for validation are presented based on the determination of figures of merit, such as precision (mean, repeatability, intermediate), accuracy, sensitivity, analytical sensitivity, selectivity, signal-to-noise ratio and confidence intervals for PLS models. An example is discussed of a model for polymorphic purity control of carbamazepine by NIR diffuse reflectance spectroscopy. The results show that multivariate calibration models can be validated to fulfill the requirements imposed by industry and standardization agencies.

Determinação espectrofotométrica simultânea de paracetamol e ibuprofeno em formulações farmacêuticas usando calibração multivariada

A simple method was proposed for determination of paracetamol and ibuprofen in tablets, based on UV measurements and partial least squares. The procedure was performed at pH 10.5, in the concentration ranges 3.00-15.00 µg ml-1 (paracetamol) and 2.40-12.00 µg ml-1 (ibuprofen). The model was able to predict paracetamol and ibuprofen in synthetic mixtures with root mean squares errors of prediction of 0.12 and 0.17 µg ml-1, respectively. Figures of merit (sensitivity, limit of detection and precision) were also estimated. The results achieved for the determination of these drugs in pharmaceutical formulations were in agreement with label claims and verified by HPLC.

Aplicação de métodos de calibração multivariada para a determinação simultânea de riboflavina (VB2), tiamina (VB1), piridoxina (VB6) e nicotinamida (VPP)

In this work, the artificial neural networks (ANN) and partial least squares (PLS) regression were applied to UV spectral data for quantitative determination of thiamin hydrochloride (VB1), riboflavin phosphate (VB2), pyridoxine hydrochloride (VB6) and nicotinamide (VPP) in pharmaceutical samples. For calibration purposes, commercial samples in 0.2 mol L-1 acetate buffer (pH 4.0) were employed as standards. The concentration ranges used in the calibration step were: 0.1 - 7.5 mg L-1 for VB1, 0.1 - 3.0 mg L-1 for VB2, 0.1 - 3.0 mg L-1 for VB6 and 0.4 - 30.0 mg L-1 for VPP. From the results it is possible to verify that both methods can be successfully applied for these determinations. The similar error values were obtained by using neural network or PLS methods. The proposed methodology is simple, rapid and can be easily used in quality control laboratories.

Estado da arte de figuras de mérito em calibração multivariada

The validation of an analytical procedure must be certified through the determination of parameters known as figures of merit. For first order data, the acuracy, precision, robustness and bias is similar to the methods of univariate calibration. Linearity, sensitivity, signal to noise ratio, adjustment, selectivity and confidence intervals need different approaches, specific for multivariate data. Selectivity and signal to noise ratio are more critical and they only can be estimated by means of the calculation of the net analyte signal. In second order calibration, some differentes approaches are necessary due to data structure.

Determinação de sibutramina em formas farmacêuticas através de espectroscopia no infravermelho com refletância difusa e métodos de calibração multivariada

The goal of this work is the development and validation of an analytical method for fast quantification of sibutramine in pharmaceutical formulations, using diffuse reflectance infrared spectroscopy and partial least square regression. The multivariate model was elaborated from 22 mixtures containing sibutramine and excipients (lactose, microcrystalline cellulose, colloidal silicon dioxide and magnesium stearate) and using fragmented (750-1150/ 1350-1500/ 1850-1950/ 2600-2900 cm-1) and smoothing spectral data. Using 10 latent variables, excellent predictive capacity were observed in the calibration (n=20, RMSEC=0.004, R= 0.999) and external validation (n=5, RMSEC= 9.36, R=0.999) phases. In the analysis of synthetic mixtures the precision (SD=3,47%) was compatible with the rules of the Agencia Nacional de Vigilância Sanitária (ANVISA-Brazil). In the analysis of commercial drugs good agreement was observed between spectroscopic and chromatographic methods.

Determinação de constituintes químicos em madeira de eucalipto por Pi-CG/EM e calibração multivariada: comparação entre redes neurais artificiais e máquinas de vetor suporte

Multivariate models were developed using Artificial Neural Network (ANN) and Least Square - Support Vector Machines (LS-SVM) for estimating lignin siringyl/guaiacyl ratio and the contents of cellulose, hemicelluloses and lignin in eucalyptus wood by pyrolysis associated to gaseous chromatography and mass spectrometry (Py-GC/MS). The results obtained by two calibration methods were in agreement with those of reference methods. However a comparison indicated that the LS-SVM model presented better predictive capacity for the cellulose and lignin contents, while the ANN model presented was more adequate for estimating the hemicelluloses content and lignin siringyl/guaiacyl ratio.

Determinação simultânea de ácido kójico e hidroquinona por espectrofotometria visível e calibração multivariada

A multivariate spectrophotometric method was developed for analysis of kojic acid/hydroquinone associations in skin whitening cosmetics. The method is based on the reaction between kojic acid and Fe3+ and on the reduction of Fe3+ by hydroquinone and further complexation of Fe2+ with 1,10-phenanthroline. The multivariate model was developed by Partial Least Squares Regression (PLSR), using 25 synthetic mixtures and mean-centered spectral data (350-380 nm). The use of 3 (kojic acid) and 2 (hydroquinone) latent variables permits the observation of mean errors of about 5% in the external validation phase.

Experimento didático de quimiometria para calibração multivariada na determinação de paracetamol em comprimidos comerciais utilizando espectroscopia no infravermelho próximo: um tutorial, parte II

The aim of this manuscript was to show the basic concepts and practical application of Partial Least Squares (PLS) as a tutorial, using the Matlab computing environment for beginners, undergraduate and graduate students. As a practical example, the determination of the drug paracetamol in commercial tablets using Near-Infrared (NIR) spectroscopy and Partial Least Squares (PLS) regression was shown, an experiment that has been successfully carried out at the Chemical Institute of Campinas State University for chemistry undergraduate course students to introduce the basic concepts of multivariate calibration in a practical way.

Determinação simultânea de NADH e ácido ascórbico usando voltametria de onda quadrada com eletrodo de carbono vítreo e calibração multivariada

O método dos mínimos quadrados parciais (PLS) foi aplicado aos dados obtidos por voltametria de onda quadrada para a determinação simultânea de ácido ascórbico (AA) e do co-fator b-nicotinamida adenina dinucleotídeo (NADH) em misturas sintéticas. As curvas voltamétricas foram obtidas em tampão fosfato 0,2 mol L-1 (pH 8,0). Foi possível verificar que o método PLS permite a determinação destes compostos simultaneamente nas condições escolhidas. Os resultados mostraram um erro relativo máximo de 1,7% para o NADH e 2,1 % para o AA. A metodologia proposta é simples e desenvolvimentos posteriores podem torná-la útil para análises in vivo.

Determinação simultânea de amarelo tartrazina e amarelo crepúsculo em alimentos via espectrofotometria UV-VIS e métodos de calibração multivariada

Os corantes sintéticos são usualmente adicionados a alimentos industrializados para conferir e restaurar a cor obtendo-se a qualidade estética desejada. Em função destes aspectos e do potencial toxicológico que alguns corantes podem apresentar, o controle de qualidade destes compostos é de fundamental importância. Neste trabalho, foi estudado o potencial das metodologias matemáticas como o princípio da aditividade, espectrofotometria derivativa e técnica multivariada (Regressão por Mínimos Quadrados Parciais - PLSR) na determinação simultânea de dois corantes alimentícios: Amarelo Crepúsculo (AC) e Amarelo Tartrazina (AT), extraídos com lã natural. Estas metodologias foram avaliadas e comparadas em função das suas capacidades de previsão, sendo que o modelo PLSR otimizado (faixa espectral de 305 a 645 nm, empregando-se 1ª derivada como transformação dos dados e 2 componentes principais) apresentou o menor valor de Raiz Quadrada da Soma dos Erros de Previsão (RMSEP) (AT = 0,191 e AC = 0,102). A faixa de concentração estudada foi de 1,0 a 16,0 mg.L-1 para AC e de 2,0 a 22,0 mg.L-1 para AT. O conjunto de validação externa apresentou erros relativos médios de 1,97% para AC e 1,39% para AT. A aplicação desta metodologia em amostras reais mostrou que em todas as amostras analisadas as concentrações destes corantes estavam de acordo com os limites estabelecidos pela legislação brasileira