As Boas Práticas de Fabricação de Medicamentos (BPFM) enfatizam que a indústria farmacêutica deve dirigir seus esforços no sentido de compreender a variação do processo, incluindo as fontes, o grau de variação e o impacto dessa variação nas características de qualidade do produto. O processo de fabricação de medicamentos tem apresentado significativas mudanças, em especial no que se refere à introdução de tecnologias analíticas que permitem o controle do processo em tempo real. A abordagem baseada na análise de risco e no novo Sistema de Qualidade Farmacêutica constitui ponto central das BPFM para o século XXI. Os órgãos regulatórios têm exigido da indústria farmacêutica sua adesão na melhoria contínua relativa ao desempenho de seus processos e, por consequência, na qualidade do produto. O objetivo do presente trabalho foi o desenvolvimento e validação de método analítico empregando espectroscopia no infravermelho próximo, assim como a avaliação do processo de fabricação de comprimidos de Captopril 25 mg, empregando abordagem racional-científica. Com referência à avaliação do processo, foram adotadas as seguintes ferramentas: análise de modos e efeitos de falhas (FMEA); gráficos de controle; índices de capacidade e análise de variância (ANOVA). A espectroscopia por infravermelho próximo (NIR) foi selecionada por apresentar maior rapidez na obtenção dos resultados, maior simplicidade na preparação das amostras, multiplicidade das análises a partir de uma única leitura e por apresentar característica não invasiva. Os resultados comprovaram a adequação dessa tecnologia na avaliação quantitativa do Captopril nas etapas de mistura de pós e de compressão. Os desvios padrão relativos na determinação da uniformidade de Captopril na mistura de pós e nos comprimidos empregando método no NIR foram, respectivamente 3,15 e 0,18%. No que se refere à avaliação da estabilidade e da capacidade do processo, as ferramentas adotadas permitiram a compreensão das fontes de variabilidade, assim como a determinação de seu grau, nas diferentes etapas do processo. Os índices de capacidade (CpK) relativos à uniformidade de Captopril (% p/v) na mistura de pós, ao peso médio do comprimido, à uniformidade de conteúdo e à % (p/v) dissolvida de Captopril, no ensaio de dissolução, foram 0,70, 1,94, 1,80 e 2,19, respectivamente. / The Good Manufacturing Practices (GMP) for Medicinal Products point out that the pharmaceutical industry must direct efforts to understand the variation of the processes, including the sources, the level of variation and the variation impact on the process in characteristics of the product. The manufacturing process has shown meaningful changes, especially in the introduction of new analytical technologies that allow the process control in real time. The approach based on risk analyses and on the new Pharmaceutical Quality System is a central key for the GMP for the XXI century. The Regulatory Agencies have demanded the pharmaceutical industry to adhere the continuous improvement related to the performance of its processes and, consequently, the product quality. Thus, the present paper aimed the development and validation of the analytical method employing NIR spectroscopy as the assessment of manufacturing process of Captopril 25 mg tablets, using rational scientific approach. Regarding the process assessment, the following tools were adopted: analysis of failure modes and effects analysis (FMEA), control charts, capability indexes, as well as analysis of variance (ANOVA). The near-infrared spectroscopy was selected due to its greater speed in getting the results, simplicity in sample preparation, and multiplicity of analysis from a single reading and provide non-invasive feature. The results confirmed the suitability of this technology in quantitative assessment of Captopril on the steps of mixing powders and compression. The relative standard deviations for the determination of Captopril uniformity in the post mixtures and in the tablets employing NIR were 3,15 e 0,18%, respectively. In reference to the stability assessment and process capacity, the tools adopted permitted the understanding of the sources of variability, as well as the determination of their level in different phases of the process. The capacity indexes relating to Captopril uniformity (% p/v) in the powder mixture, the average weight of the tablet, the content uniformity and the % (p/v) dissolved Captopril, in the dissolution assay were 0,70, 1,94, 1,80 and 2,19, respectively.

Made available in DSpace on 2017-07-21T18:53:14Z (GMT). No. of bitstreams: 1 Elisangela Serenato.pdf: 1216828 bytes, checksum: 1e4a058b95c9b4cbdc1c0a22185ded54 (MD5) Previous issue date: 2010-02-25 / Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná / Ricotta is a kind of fresh cheese, obtained by the precipitation of the proteins in the cheese whey. According to the current legislation, ricotta is framed on standards of identity and quality of low-fat cheeses, however, studies show a great variability on the centesimal composition. It justifies the necessity of establishing quality standards, and the development of methodologies that allow a fast and efficient control of the product. Besides it, conventional methodologies used to determine the centesimal composition of the ricotta, though they are part of the routine analysis in laboratories of quality control, they are onerous, time consuming and generate residues. In this sense, the objective of this study was to develop a method for the quantification of physical/chemical standards, using Near Infrared Diffuse Spectroscopy (NIRRS), associating to methods of multivariate calibration. For the construction of multivariate models (specially PLSR) it were used the media of concentration of acidity, carbohydrates, ashes, chlorides, fat, pH, protein and moisture, obtained by conventional methodologies (titration method, spectroscopic, muffle carbonization, titration, Gerber, potentiometric, Kjeldahl and gravimetric method, respectively), as well as data of the near infrared spectroscopy. It was collected spectra in duplicate, 33 spectra were used for the calibration phase, and the 5 remaining used to the external validation phase. The best results for fat, protein and moisture levels were obtained on the spectral region between 1100 to 2500 nm. The optimized model for determination of fat used the Multiplicative Scatter Correction (MSC), with 6 latent variable (VLs), acquiring correlation coefficients of Rcal= 0.968 and Rval= 0.936 allowing the quantification of fat with a medium prevision error (Er) of 6.37%. For the protein level, the best result was obtained using MSC and data centered on media (DCM). The model of regression, with 6 VLs, presented correlation coefficients of Rcal= 0.968 and Rval= 0.885, and determination of protein with Er of 5.95%. The best model for determination of moisture used normalization, with 4 VLs correlation coefficients of Rcal= 0.851 and Rval= 0.757 and allowing the quantification of moisture with and Er of 1.91%. It was not possible to build models for acidity, carbohydrates, ashes, chloride and pH parameters, presenting low values of Rcal and Rval, demonstrating the low capacity of forecasting even for samples that compose the calibration set through the proposed methodology. These results demonstrate the potential of multivariate models on determination of fat, protein and moisture levels on samples with complex matrices (ricotta) and also show the advantages of the association NIRRS-PLSR which allows a fast quality control with minimum manipulation of the sample. / A ricota é um tipo de queijo fresco, obtido pela precipitação das proteínas do soro do queijo. Segundo a legislação vigente, a ricota é enquadrada nos padrões de identidade e qualidade de queijos magros, no entanto, estudos demonstram a grande variabilidade na sua composição centesimal. Isto justifica a necessidade de estabelecimento de padrões de qualidade, e o desenvolvimento de metodologias que possibilitem um controle rápido e eficiente do produto. Além disso, as metodologias convencionais empregadas para a determinação da composição centesimal da ricota, embora façam parte das análises de rotina em laboratórios de controle de qualidade, são onerosas, demoradas e geram resíduos. Neste sentido, o objetivo deste estudo foi desenvolver um método para a quantificação dos parâmetros físico-químicos, utilizando-se espectroscopia no infravermelho próximo por reflectância difusa (NIRRS) associado a métodos de calibração multivariada. Para a construção dos modelos multivariados (principalmente PLSR) foram utilizadas as médias das concentrações de acidez, carboidratos, cinzas, cloretos, gordura, pH, proteína e umidade, obtidas pelas metodologias convencionais (método titulométrico, espectroscópico, carbonização em mufla, titulométrico, Gerber, potenciométrico, Kjeldahl e método gravimétrico, respectivamente), bem como, os dados de espectroscopia no infravermelho próximo. Foram coletados espectros em duplicata, sendo que 33 desses espectros foram utilizados para a fase de calibração e os 5 restantes utilizados para a fase de validação externa. O melhores resultados para os teores de gordura, proteína e umidade foram obtidos na região espectral entre 1100 a 2500 nm. O modelo otimizado para a determinação de gordura empregou a correção do espalhamento multiplicativo (MSC), com 6 variáveis latentes (VLs), obtendo-se coeficientes de correlação de Rcal= 0,968 e Rval= 0,936 possibilitando a quantificação de gordura com um erro médio de previsão (Er) de 6,37%. Para o teor de proteína, o melhor resultado foi obtido utilizando-se a MSC e dados centrados na média (DCM). O modelo de regressão, com 6 VLs, apresentou coeficientes de correlação de Rcal= 0,968 e Rval= 0,885, e determinação de proteína com Er de 5,95%. O melhor modelo para a determinação de umidade empregou a normalização, com 4 VLs, obtendo-se coeficientes de correlação de Rcal= 0,851 e Rval= 0,757 e possibilitando a quantificação de umidade com um Er de 1,91%. Não foi possível a construção de modelos para os parâmetros acidez, carboidratos, cinzas, cloretos e pH, apresentando baixos valores de Rcal e Rval, demonstrando a baixa capacidade de previsão mesmo para as amostras que compõem o conjunto de calibração através da metodologia proposta. Estes resultados além de demonstrarem o potencial dos modelos multivariados na determinação dos teores de gordura, proteína e umidade em amostras com matrizes complexas (ricota) evidenciam as vantagens da associação NIRRS-PLSR que permite um controle de qualidade rápido com uma manipulação mínima da amostra.

As Boas Práticas de Fabricação de Medicamentos (BPFM) enfatizam que a indústria farmacêutica deve dirigir seus esforços no sentido de compreender a variação do processo, incluindo as fontes, o grau de variação e o impacto dessa variação nas características de qualidade do produto. O processo de fabricação de medicamentos tem apresentado significativas mudanças, em especial no que se refere à introdução de tecnologias analíticas que permitem o controle do processo em tempo real. A abordagem baseada na análise de risco e no novo Sistema de Qualidade Farmacêutica constitui ponto central das BPFM para o século XXI. Os órgãos regulatórios têm exigido da indústria farmacêutica sua adesão na melhoria contínua relativa ao desempenho de seus processos e, por consequência, na qualidade do produto. O objetivo do presente trabalho foi o desenvolvimento e validação de método analítico empregando espectroscopia no infravermelho próximo, assim como a avaliação do processo de fabricação de comprimidos de Captopril 25 mg, empregando abordagem racional-científica. Com referência à avaliação do processo, foram adotadas as seguintes ferramentas: análise de modos e efeitos de falhas (FMEA); gráficos de controle; índices de capacidade e análise de variância (ANOVA). A espectroscopia por infravermelho próximo (NIR) foi selecionada por apresentar maior rapidez na obtenção dos resultados, maior simplicidade na preparação das amostras, multiplicidade das análises a partir de uma única leitura e por apresentar característica não invasiva. Os resultados comprovaram a adequação dessa tecnologia na avaliação quantitativa do Captopril nas etapas de mistura de pós e de compressão. Os desvios padrão relativos na determinação da uniformidade de Captopril na mistura de pós e nos comprimidos empregando método no NIR foram, respectivamente 3,15 e 0,18%. No que se refere à avaliação da estabilidade e da capacidade do processo, as ferramentas adotadas permitiram a compreensão das fontes de variabilidade, assim como a determinação de seu grau, nas diferentes etapas do processo. Os índices de capacidade (CpK) relativos à uniformidade de Captopril (% p/v) na mistura de pós, ao peso médio do comprimido, à uniformidade de conteúdo e à % (p/v) dissolvida de Captopril, no ensaio de dissolução, foram 0,70, 1,94, 1,80 e 2,19, respectivamente. / The Good Manufacturing Practices (GMP) for Medicinal Products point out that the pharmaceutical industry must direct efforts to understand the variation of the processes, including the sources, the level of variation and the variation impact on the process in characteristics of the product. The manufacturing process has shown meaningful changes, especially in the introduction of new analytical technologies that allow the process control in real time. The approach based on risk analyses and on the new Pharmaceutical Quality System is a central key for the GMP for the XXI century. The Regulatory Agencies have demanded the pharmaceutical industry to adhere the continuous improvement related to the performance of its processes and, consequently, the product quality. Thus, the present paper aimed the development and validation of the analytical method employing NIR spectroscopy as the assessment of manufacturing process of Captopril 25 mg tablets, using rational scientific approach. Regarding the process assessment, the following tools were adopted: analysis of failure modes and effects analysis (FMEA), control charts, capability indexes, as well as analysis of variance (ANOVA). The near-infrared spectroscopy was selected due to its greater speed in getting the results, simplicity in sample preparation, and multiplicity of analysis from a single reading and provide non-invasive feature. The results confirmed the suitability of this technology in quantitative assessment of Captopril on the steps of mixing powders and compression. The relative standard deviations for the determination of Captopril uniformity in the post mixtures and in the tablets employing NIR were 3,15 e 0,18%, respectively. In reference to the stability assessment and process capacity, the tools adopted permitted the understanding of the sources of variability, as well as the determination of their level in different phases of the process. The capacity indexes relating to Captopril uniformity (% p/v) in the powder mixture, the average weight of the tablet, the content uniformity and the % (p/v) dissolved Captopril, in the dissolution assay were 0,70, 1,94, 1,80 and 2,19, respectively.

Pelchem, a commercial subsidiary of Necsa (South African Nuclear Energy Corporation), produces a range of commercial fluorocarbon products while driving research and development initiatives to support the fluorine product portfolio. One such initiative is to develop improved analytical techniques to analyse product composition during development and to quality assure produce. Generally the C–F type products produced by Necsa are in a solution of anhydrous HF, and cannot be directly analyzed with traditional techniques without derivatisation. A technique such as vibrational spectroscopy, that can analyze these products directly without further preparation, will have a distinct advantage. However, spectra of mixtures of similar compounds are complex and not suitable for traditional quantitative regression analysis. Multivariate data analysis (MVA) can be used in such instances to exploit the complex nature of spectra to extract quantitative information on the composition of mixtures. A selection of fluorocarbon alcohols was made to act as representatives for fluorocarbon compounds. Experimental design theory was used to create a calibration range of mixtures of these compounds. Raman and infrared (NIR and ATR–IR) spectroscopy were used to generate spectral data of the mixtures and this data was analyzed with MVA techniques by the construction of regression and prediction models. Selected samples from the mixture range were chosen to test the predictive ability of the models. Analysis and regression models (PCR, PLS2 and PLS1) gave good model fits (R2 values larger than 0.9). Raman spectroscopy was the most efficient technique and gave a high prediction accuracy (at 10% accepted standard deviation), provided the minimum mass of a component exceeded 16% of the total sample. The infrared techniques also performed well in terms of fit and prediction. The NIR spectra were subjected to signal saturation as a result of using long path length sample cells. This was shown to be the main reason for the loss in efficiency of this technique compared to Raman and ATR–IR spectroscopy. It was shown that multivariate data analysis of spectroscopic data of the selected fluorocarbon compounds could be used to quantitatively analyse mixtures with the possibility of further optimization of the method. The study was a representative study indicating that the combination of MVA and spectroscopy can be used successfully in the quantitative analysis of other fluorocarbon compound mixtures. / Thesis (M.Sc. (Chemistry))--North-West University, Potchefstroom Campus, 2012.

Pelchem, a commercial subsidiary of Necsa (South African Nuclear Energy Corporation), produces a range of commercial fluorocarbon products while driving research and development initiatives to support the fluorine product portfolio. One such initiative is to develop improved analytical techniques to analyse product composition during development and to quality assure produce. Generally the C–F type products produced by Necsa are in a solution of anhydrous HF, and cannot be directly analyzed with traditional techniques without derivatisation. A technique such as vibrational spectroscopy, that can analyze these products directly without further preparation, will have a distinct advantage. However, spectra of mixtures of similar compounds are complex and not suitable for traditional quantitative regression analysis. Multivariate data analysis (MVA) can be used in such instances to exploit the complex nature of spectra to extract quantitative information on the composition of mixtures. A selection of fluorocarbon alcohols was made to act as representatives for fluorocarbon compounds. Experimental design theory was used to create a calibration range of mixtures of these compounds. Raman and infrared (NIR and ATR–IR) spectroscopy were used to generate spectral data of the mixtures and this data was analyzed with MVA techniques by the construction of regression and prediction models. Selected samples from the mixture range were chosen to test the predictive ability of the models. Analysis and regression models (PCR, PLS2 and PLS1) gave good model fits (R2 values larger than 0.9). Raman spectroscopy was the most efficient technique and gave a high prediction accuracy (at 10% accepted standard deviation), provided the minimum mass of a component exceeded 16% of the total sample. The infrared techniques also performed well in terms of fit and prediction. The NIR spectra were subjected to signal saturation as a result of using long path length sample cells. This was shown to be the main reason for the loss in efficiency of this technique compared to Raman and ATR–IR spectroscopy. It was shown that multivariate data analysis of spectroscopic data of the selected fluorocarbon compounds could be used to quantitatively analyse mixtures with the possibility of further optimization of the method. The study was a representative study indicating that the combination of MVA and spectroscopy can be used successfully in the quantitative analysis of other fluorocarbon compound mixtures. / Thesis (M.Sc. (Chemistry))--North-West University, Potchefstroom Campus, 2012.