No abstract

Continuous pharmaceutical manufacturing processes are of increased industrial interest and require uni- and multivariate Process Analytical Technology (PAT) data from different unit operations to be aligned and explored within the Quality by Design (QbD) context. Real-time pharmaceutical process verification is accomplished by monitoring univariate (temperature, pressure, etc.) and multivariate (spectra, images, etc.) process parameters and quality attributes, to provide an accurate state estimation of the process, required for advanced control strategies. This paper describes the development and use of such tools for a continuous hot melt extrusion (HME) process, monitored with generic sensors and a near-infrared (NIR) spectrometer in real-time, using SIPAT (Siemens platform to collect, display, and extract process information) and additional components developed as needed. The IT architecture of such a monitoring procedure based on uni- and multivariate sensor systems and their integration in SIPAT is shown. SIPAT aligned spectra from the extrudate (in the die section) with univariate measurements (screw speed, barrel temperatures, material pressure, etc.). A multivariate supervisory quality control strategy was developed for the process to monitor the hot melt extrusion process on the basis of principal component analysis (PCA) of the NIR spectra. Monitoring the first principal component and the time-aligned reference feed rate enables the determination of the residence time in real-time.

No abstract

Near infrared (NIR) spectroscopy is a versatile, non-invasive and non-destructive tool that is often used for process monitoring in the pharmaceutical industry. Often, equipment window fouling or probe fouling of in-situ NIR probes occurs, leading to biased spectra and wrong interpretations (e.g. process-state estimation). Physical countermeasures, including self-cleaning probes and geometrical considerations, are called for. This paper presents a mathematical solution to the problem of window fouling for an NIR-monitored process: by determining the distance to the particles, we established which part of the signal was missing owing to the coating accumulation on the probe window. The proposed approach is illustrated with the example of hot-melt coating in a fluidised bed, during which coating buildup on substrate particles was monitored despite window fouling.