Cartas de controle multivariadas aplicadas na revisão periódica de produtos e no estudo de estabilidade em uma indústria farmacêutica nacional

Abstract

Statistical process control is becoming increasingly important in the pharmaceutical industry, since it can act on the product quality assurance and monitoring of production efficiency. Regulatory agencies worldwide already include multivariate statistical process control on their recommendations. In this work we perform three applications of multivariate control charts to detect small variations in monitoring pharmaceutical process. The studies were performed in the Laboratório Farmacêutico do Estado de Pernambuco Governador Miguel Arraes - LAFEPE using process data and addressing real problems of the industry routine. The first one consists in the elaboration of the Annual Product Review using multivariate control charts based on Principal Component Analysis, accompanied by a simple and unique methodology for identification of multivariate signal out of control, which was performed by decomposition of T2 statistics based on the loadings of VARIMAX rotation. The method developed has allowed the sector responsible for the Quality Assurance industry to verify the variables that most impact the process. The second application consists in monitoring of the degradation of captopril in tablets by High Performance Liquid Chromatograph measurements. For this aim multivariate control charts based on residuals of principal component analysis were built. The weighting of the retention time of the chromatogram in the region of captopril disulfide highlights the residual chart for revealing slight changes in the chromatographic standards. The third and last application consists in monitoring of the degradation of captopril in tablets by near infrared and middle infrared measurements. For this aim T2 control charts were built by using a variable selection method and a CUSUM-COT scheme. Both the techniques showed to be able for detection of expired samples and Middle infrared was able to identify slight changes during degradation process. Keywords: Monitoring of Process, Multivariate Control Charts, Annual Prod