Determinação de amoxicilina em formulações farmacêuticas em pó empregando DRIFTS-PLS

Neste trabalho propõe-se a quantificação de amoxicilina em formulações farmacêuticas empregando espectroscopia por refletância difusa no infravermelho com transformada de Fourier (DRIFTS) e regressão por mínimos quadrados parciais (PLS). Foram coletados em um espectrômetro Nicolet Magna 550 os espectros de 24 amostras (17 para o conjunto de calibração e 7 para o conjunto de validação) contendo de 76,7-94,3 % de amoxicilina em amido. Para a construção dos modelos PLS foi empregada a correção do espalhamento de luz (MSC) e os dados foram autoescalados ou escalados pela variância. Foi obtido um excelente modelo para a previsão da amoxicilina o qual apresentou R²=0,9936, RMSEC=0,441 e RMSEV=0,790. O método proposto além de não destrutivo apresenta baixo tempo de análise e baixo custo podendo ser facilmente empregado no controle de qualidade das indústrias farmacêuticas.The amount of amoxicillin in pharmaceutical formulations was determined using spectra of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), in association with partial least squares (PLS) regression. The spectra of 24 different samples (17 for the calibration set and 7 for the validation set), which had been registered using a Nicolet Magna 550 spectrophotometer, contained 76.7-94.3% of amoxicillin in starch. The PLS models were constructed with auto-scaled or variance-scaled data, and multiplicative scatter correction (MSC). The best model presented R²=0.9936, RMSEC=0.441 and RMSEV=0.790. The analytical method proposed is non-destructive and the cost and time of analysis are very much reduced, allowing for the fast and direct determination of amoxicillin content

Exploratory analysis applied in study of pharmaceutical formulations with piroxicam

A identificação de diferentes formulações de medicamentos manipulados contendo piroxicam foi estudada, empregando espectros de reflexão difusa no infravermelho médio com transformada de Fourier (DRIFTS), em associação com a técnica de análise por agrupamentos hierárquicos (AAH). Os espectros de amostras, de 5 diferentes farmácias de manipulação, contendo piroxicam (10 mg e 20 mg) e seus respectivos excipientes, foram adquiridos em um espectrofotômetro NICOLET Magna 550, obtendo-se duas réplicas de cada amostra. Para a análise multivariada, as informações espectrais foram tratadas no programa Pirouette® 2.7 da Infometrix, utilizando-se as regiões espectrais 1340 a 1470 cm-1, 1535 a 1680 cm-1, 2800 a 3004 cm-1 e 3290 a 3400 cm-1. Os dendogramas foram construídos com os dados auto-escalados, e correção do espalhamento da luz (MSC), utilizando três tipos de construção: simples, flexível e incremental. Com a aplicação da análise hierárquica de agrupamentos constatou-se a formação de dois grupos distintos, um contendo os princípios ativos, e outro contendo os excipientes. Os resultados demonstram que a técnica DRIFTS em conjunto com análise por agrupamentos hierárquicos constitui uma alternativa para o controle de qualidade dos processos de produção de medicamentos.The identification of different pharmaceutical formulations with piroxicam was studied, using spectra of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), in association with hierarchical cluster analysis (HCA) technique. The spectra of samples of the 5 different compounding pharmacies, containing 10 or 20 mg of piroxicam and its respective inactive ingredients, had been collected in Nicolet Magna 550 spectrophotometer. For the multivariate analysis, the spectral information had been processed in software package Pirouette® 2.7 of the Infometrix. The dendograms had been constructed with the autoscaled data, and multiplicative scatter correction (MSC), using three types of linkage methods: single, flexible and incremental. By applying the hierarchical cluster analysis the formation of two distinct groups: one with the active principles and another group with the inactive ingredients was proved. These results demonstrate that the DRIFTS associated with chemometrics tools, constitute a quality control alternative of drugs production processes

Desenvolvimento de metodologias no infravermelho aplicadas para a quantificação de cloridrato de metformina em formulações farmacêuticas

Neste trabalho 20 amostras comerciais sob a forma de comprimidos e 15sintéticas de cloridrato de metformina foram utilizadas e seus espectros adquiridos na faixa de 4000–650 cm-1 por espectroscopia difusa no infravermelho com transformada de Fourier (DRIFTS). Foram construídos e comparados modelos de calibração multivariada utilizando toda a região espectral analisada (modelo global PLS) e modelos otimizados empregando sub-regiões dos espectros FT-IR (modelos iPLS e siPLS). Os melhores resultados foram aqueles obtidos utilizando o algoritmo siPLS, dividindo o espectro em 40 intervalos e combinando 3 intervalos (37, 39 e 40), 4 variáveis latentes, e apresentou um valor de RMSEP inferior ao obtido utilizando o modelo global e o algoritmo iPLS. Assim, a aplicação das técnicas de seleção das regiões dos espectros de infravermelho (iPLS e siPLS) mostraram-se eficientes no desenvolvimento de metodologias mais simples, rápidas e não destrutivas para a análise das formulações farmacêuticas contendo metformida na forma de comprimidos, destacando-se a potencialidade destas técnicas no controle e fiscalização de medicamentos industrializados.In this work 20 metformin hydrochloride commercial pill samples and 14 synthetic samples were used and their spectra acquired in the 4000 – 650 cm-1 range by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). Multivariate calibration models were built and compared using all spectral region (global model PLS) and optimized models applying FTIR spectral sub-regions (iPLS and siPLS models). The best results were the ones obtained by using the siPLS algorithm, dividing the spectrum into 40 intervals and combining 3 intervals (37, 39 and 40) with 4 latent variables, which also presented an RMSEP value lower than the one obtained by using the global model and the iPLS algorithm. Finally, the application of selection techniques for infrared spectral regions (iPLS and siPLS) has been efficient to develop simpler, faster and non-destructive methodologies to analyze pharmaceutical pill formulations containing metformin, highlighting the potentialities of these techniques to control and inspect industrialized medicines

Development of infrared methodologies applied to determination of the metformin hidrochloride in pharmaceutical formulations

In this work 20 metformin hydrochloride commercial pill samples and 14 synthetic samples were used and their spectra acquired in the 4000 – 650 cm-1 range by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). Multivariate calibration models were built and compared using all spectral region (global model PLS) and optimized models applying FTIR spectral sub-regions (iPLS and siPLS models). The best results were the ones obtained by using the siPLS algorithm, dividing the spectrum into 40 intervals and combining 3 intervals (37, 39 and 40) with 4 latent variables, which also presented an RMSEP value lower than the one obtained by using the global model and the iPLS algorithm. Finally, the application of selection techniques for infrared spectral regions (iPLS and siPLS) has been efficient to develop simpler, faster and non-destructive methodologies to analyze pharmaceutical pill formulations containing metformin, highlighting the potentialities of these techniques to control and inspect industrialized medicines

Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations

An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS

Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations

An alternative method for the quantifi cation of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse refl ectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1 SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Refl ectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1 for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS