Application of near-infrared spectroscopy to monitor in-process and product quality attributes for granulation and immediate release tablet production

Abstract

The purpose of this study was to investigate the application of NIR spectroscopy to monitor critical in-process and excipient variables in the manufacturing of immediate release tablets. In this study, roller compaction and fluid bed granulation were used for the granulation of Ciprofloxacin hydrochloride and Fexofenadine hydrochloride, respectively. In roller compaction, prior knowledge was systematically incorporated into the risk assessment using failure mode and effect analysis (FMEA). The factors identified using FMEA were quantitatively assessed using a Placket-Burman screening design. Results indicated that roll pressure (RP) was the most critical roller compaction process factor affecting the granule size and flow. Binder grade, Klucel® EXF vs JF and tablet compression force (Pmax) were found to be critical to the release characteristics of Ciprofloxacin. This study demonstrated that the scientific rationale and quality risk management analysis were used to successfully and efficiently determine the Critical quality attributes. Four factors, RP, Pmax, binder source (Klucel® EXF vs Nisso®-L), and lubricant type (monohydrate vs dihydrate), were further investigated using high resolution experimental design. The results showed that binder and lubricant replacement was insignificant. In addition, NIR was used at various stages of the product development, and the partial least square (PLS) regression models developed have successfully predicted blend uniformity, particle size, crushing force, and disintegration time of the batches manufactured in the same location. However, the models yielded higher prediction errors for batches manufactured at a different location. In fluid bed granulation, a PLS model was developed to successfully predict the moisture levels in real time using in-line NIR probe specially designed for this application. This combined with humidity and temperature data from a novel PyroButton® in conjunction with multivariate data analysis techniques was used to develop multivariate statistical process control charts (MSPC) such as scores, distance to model (DModX), and Hotelling T2. The application of these charts for process monitoring and fault detection was further evaluated. In summary, these findings demonstrate the application of NIR in conjunction with multivariate chemometric models as a potential Process Analytical Technology (PAT) tool for effective process monitoring and process control in pharmaceutical manufacturing.