RESUMEN
The pharmaceutical industry is encouraged within Quality by Design (QbD) to apply science-based manufacturing principles to assure quality not only of new but also of existing processes. This paper presents how QbD principles can be applied to an existing industrial pharmaceutical fluid bed granulation (FBG) process. A three-step approach is presented as follows: (1) implementation of Process Analytical Technology (PAT) monitoring tools at the industrial scale process, combined with multivariate data analysis (MVDA) of process and PAT data to increase the process knowledge; (2) execution of scaled-down designed experiments at a pilot scale, with adequate PAT monitoring tools, to investigate the process response to intended changes in Critical Process Parameters (CPPs); and finally (3) the definition of a process Design Space (DS) linking CPPs to Critical to Quality Attributes (CQAs), within which product quality is ensured by design, and after scale-up enabling its use at the industrial process scale. The proposed approach was developed for an existing industrial process. Through enhanced process knowledge established a significant reduction in product CQAs, variability already within quality specifications ranges was achieved by a better choice of CPPs values. The results of such step-wise development and implementation are described.
Asunto(s)
Composición de Medicamentos/métodos , Industria Farmacéutica/métodos , Tecnología Farmacéutica/métodos , Análisis Multivariante , Preparaciones Farmacéuticas/química , Control de Calidad , Proyectos de Investigación , Medición de RiesgoRESUMEN
A set of 192 fluid bed granulation batches at industrial scale were in-line monitored using microwave resonance technology (MRT) to determine moisture, temperature and density of the granules. Multivariate data analysis techniques such as multiway partial least squares (PLS), multiway principal component analysis (PCA) and multivariate batch control charts were applied onto collected batch data sets. The combination of all these techniques, along with off-line particle size measurements, led to significantly increased process understanding. A seasonality effect could be put into evidence that impacted further processing through its influence on the final granule size. Moreover, it was demonstrated by means of a PLS that a relation between the particle size and the MRT measurements can be quantitatively defined, highlighting a potential ability of the MRT sensor to predict information about the final granule size. This study has contributed to improve a fluid bed granulation process, and the process knowledge obtained shows that the product quality can be built in process design, following Quality by Design (QbD) and Process Analytical Technology (PAT) principles.