Patrick R. Wahl

Inline monitoring and a PAT strategy for pharmaceutical hot melt extrusion.

Implementation of continuous manufacturing in the pharmaceutical industry requires tight process control. This study focuses on a PAT strategy for hot melt extrusion of vegetable calcium stearate (CaSt) as matrix carrier and paracetamol as active pharmaceutical ingredient (API). The extrusion was monitored using in-line near-infrared (NIR) spectroscopy. A NIR probe was located in the section between the extrusion screws and the die, using a novel design of the die channel. A chemometric model was developed based on premixes at defined concentrations and was implemented in SIPAT for real time API concentration monitoring. Subsequently, step experiments were performed for different API concentrations, screw speeds and screw designs. The predicted API concentration was in good agreement with the pre-set concentrations. The transition from one API plateau to another was a smooth curve due to the mixing behaviour of the extruder. The accuracy of the model was confirmed via offline HPLC analysis. The screw design was determined as the main influential factor on content uniformity (CU). Additionally the influence of multiple feeders had a significant impact on CU. The results demonstrate that in-line NIR measurements is a powerful tool for process development (e.g., mixing characterization), monitoring and further control strategies.

Monitoring Blending of Pharmaceutical Powders with Multipoint NIR Spectroscopy

Blending of powders is a crucial step in the production of pharmaceutical solid dosage forms. The active pharmaceutical ingredient (API) is often a powder that is blended with other powders (excipients) in order to produce tablets. The blending efficiency is influenced by several external factors, such as the desired degree of homogeneity and the required blending time, which mainly depend on the properties of the blended materials and on the geometry of the blender. This experimental study investigates the mixing behavior of acetyl salicylic acid as an API and α-lactose monohydrate as an excipient for different filling orders and filling levels in a blender. A multiple near-infrared probe setup on a laboratory-scale blender is used to observe the powder composition quasi-simultaneously and in-line in up to six different positions of the blender. Partial least squares regression modeling was used for a quantitative analysis of the powder compositions in the different measurement positions. The end point for the investigated mixtures and measurement positions was determined via moving block standard deviation. Observing blending in different positions helped to detect good and poor mixing positions inside the blender that are affected by convective and diffusive mixing.

Supervisory Control System for Monitoring a Pharmaceutical Hot Melt Extrusion Process

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.

Adsorption-driven tuning of the electrical resistance of nanoporous gold

The electrical resistance of nanoporous gold prepared by dealloying is tuned by charging the surfaces of the porous structure in an electrolyte. Reversible variations in the resistance up to approximately 4% and 43% occur due to charging in the regimes of double layer charging and specific adsorption, respectively. Charging-induced variations in the electron density or of the volume cannot account for the resistance variation, indicating that this variation is primarily caused by charge-induced modifications of the charge carrier scattering at the solid-electrolyte interface. The relative resistance variation in nanoporous Au with surface charging is found to be much higher than reported for porous nanocrystalline Pt. This is due to the lesser resistance contribution from internal grain boundaries. The resistance variation in nanoporous Au is also higher than that found in thin films owing to the stronger surface scattering in the ligament structure compared to plan surfaces. We argue that the strong resi...

In-line implementation of an image-based particle size measurement tool to monitor hot-melt extruded pellets.

This work focuses on the implementation and application of an in-line particle measurement tool to monitor particle properties of hot-melt extruded pellets. A novel image analysis system (Eyecon) is used to analyze pellets with a size of approximately 1mm. The method is based on photometric stereo imaging, which is achieved by three different-colored light sources arranged circularly around the lens. Several implementations, whereby the product stream was led through the optical sampling volume, have been tested. The advantages and disadvantages of each implementation are discussed and evaluated. The most suitable implementation was applied to an extrusion run with constant throughput and different cutting frequencies resulting in different pellet sizes. A particle size distribution comparison between the image analysis system and an off-line reference particle analysis (QICPIC) showed good agreement although only a small fraction of the particles were analyzed in-line. Additionally, some illustrative examples for process development are given. With this approach the capability of hot-die face pelletizing to manufacture nearly-spherical pellets with a narrow size distribution is proven.

Hot Melt Extrusion as a Continuous Pharmaceutical Manufacturing Process

The implementation of continuous manufacturing in the pharmaceutical industry has been of increasing interest over the last years. This chapter focuses on continuous hot melt extrusion (HME) processing as well as on the continuous downstream options that are available. Furthermore, process analytical technology (PAT) tools and the integration of such tools in process control environment are presented. In general, 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 chapter describes the development and use of such tools for a continuous 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.

Continuous monitoring of API content, API distribution and crushing strength after tableting via near-infrared chemical imaging

Near-infrared chemical imaging (NIR-CI) with high-speed cameras based on the push-broom acquisition principle is a rapidly-evolving and can be used for a variety of purposes, from classification (and sorting) of products to mapping spatial distribution of materials. The present study examined if NIR-CI is suitable for tablet manufacturing. To that end, the tablets were introduced into the CI system via a flat belt conveyor. A formulation, which consisted of 4wt.%-6wt.% caffeine, 5wt.% crospovidone as a disintegrant, 88wt.%-90wt.% lactose as a filler and 1wt.% magnesium stearate as a lubricator, was tableted at compression forces ranging from 5kN to 30kN. The intra- and inter-tablet homogeneity of caffeine and the tablets hardness were analyzed via NIR-CI. For the homogeneity evaluation, two methods were applied: standard deviation (SD) and distributional homogeneity index (DHI). The results showed that the SD of caffeine in a single tablet increased with an increase in the caffeine content. This was attributed to natural variations in a binary mixture of caffeine and excipients. Overall, the chosen NIR-CI setup has strong potential to be transferred to the production scale to monitor all tablets in a production stream.

Characterization of the coating and tablet core roughness by means of 3D optical coherence tomography

This study demonstrates the use of optical coherence tomography (OCT) to simultaneously characterize the roughness of the tablet core and coating of pharmaceutical tablets. OCT is a high resolution non-destructive and contactless imaging methodology to characterize structural properties of solid dosage forms. Besides measuring the coating thickness, it also facilitates the analysis of the tablet core and coating roughness. An automated data evaluation algorithm extracts information about coating thickness, as well as tablet core and coating roughness. Samples removed periodically from a pan coating process were investigated, on the basis of thickness and profile maps of the tablet core and coating computed from about 480,000 depth measurements (i.e., 3D data) per sample. This data enables the calculation of the root mean square deviation, the skewness and the kurtosis of the assessed profiles. Analyzing these roughness parameters revealed that, for the given coating formulation, small valleys in the tablet core are filled with coating, whereas coarse features of the tablet core are still visible on the final film-coated tablet. Moreover, the impact of the tablet core roughness on the coating thickness is analyzed by correlating the tablet core profile and the coating thickness map. The presented measurement method and processing could be in the future transferred to in-line OCT measurements, to investigate core and coating roughness during the production of film-coated tablets.

Spatially Resolved Spectral Powder Analysis: Experiments and Modeling:

Understanding the behavior of light in granular media is necessary for determining the sample size, shape, and weight when probing using fiber optic setups. This is required for a correct estimate of the active pharmaceutical ingredient content in a pharmaceutical blend via near-infrared spectroscopy. Several strategies to describe the behavior of light in granular and turbid media exist. A common approach is the Monte-Carlo simulation of individual photons and their description using mean free path lengths for scattering and absorption. In this work, we chose a complementary method by approximating these parameters via real physical counterparts, i.e., the particle size, shape, and density and the resulting chord lengths. Additionally, the wavelength dependence of refractive indices is incorporated. The obtained results were compared with those obtained in an experimental setup that included the SAM-Spec Felin probe head by Indatech for detecting spatially resolved spectra of samples. Our method facilitates the interpretation of the acquired experimental results by contrasting the optical response, the physical particle attributes, and the simulation results.