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.

Simultaneous determination of sulphamethoxazole and trimethoprim in powder mixtures by attenuated total reflection-Fourier transform infrared and multivariate calibration.

A partial least-squares calibration (PLS) procedure in combination with infrared spectroscopy has been developed for simultaneous determination of sulphamethoxazole (SMZ) and trimethoprim (TMP) in raw material powder mixtures used for manufacturing commercial pharmaceutical products. Multivariate calibration modeling procedures, interval partial least squares (iPLS) and synergy partial least squares (siPLS), were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. The experimental matrix was constructed using 49 synthetic samples and 15 commercial samples. The considered concentration ranges were 400-900 mg g(-1) SMZ and 80-240 mg g(-1) TMP. Spectral data were recorded between 650 and 4000 cm(-1) with a 4 cm(-1) resolution by Fourier transform infrared spectroscopy coupled with attenuated total reflectance (ATR-FTIR) accessory. The proposed procedure was compared with conventional procedure by high performance liquid chromatography (HPLC) using 15 commercial samples containing SMZ and TMP. The results showed that PLS regression model combined to ATR-FTIR is a relatively simple, rapid and accurate procedure that could be applied to the simultaneous determination of SMZ and TMP in routine quality control of powder mixtures. A root mean square error of prediction (RMSEP) of 13.18 mg g(-1) for SMZ and 6.03 mg g(-1) for TMP was obtained after selection of better intervals by siPLS. Using the proposed procedure it is possible to analyze each sample in less than 3 min considering two replicates (excluding the grinding step). Accuracy was checked by comparison to HPLC method and agreement better than 98.8% was achieved.

Determination of amoxicillin content in powdered pharmaceutical formulations using DRIFTS and PLS

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 percent 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.

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 por cento 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.

Análise exploratória aplicada no estudo de medicamentos contendo piroxicam / Exploratory analysis applied in study of pharmaceutical formulations with piroxicam

A identificação de diferentes formulações de medicamentos manipulados contendo piroxicam foi estudada, empregando epectros 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...