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.

PAT for tableting: inline monitoring of API and excipients via NIR spectroscopy.

This paper describes the application and implementation of inline NIR spectroscopy in an industrial tablet press. The content uniformity of a powder was analyzed via a NIR probe mounted on the feed frame. A PLS model with four latent variables (R(2)=0.97, Q(2)=0.95) was developed for the Active Pharmaceutical Ingredient (API) and two main excipients (EX1, EX2), according to the mixture DoE. The RMSEP corresponded to the relative errors of 2.7% for API, 1.7% for EX1 and 2.6% for EX2, compared to the nominal formulation. Transfer of the model, from the lab to an inline setup for manufacturing was achieved using local centering. There was a good agreement between the results of inline NIR and drawn tablets analyzed via UV-Vis. Notably, NIR indicated stochastic segregation behavior of the powder toward the end of the process, which was confirmed by the UV-Vis analysis. The outcome of our work was related to the recently published Ph. Eur. chapter 2.9.47 "Demonstration of uniformity of dosage units using large sample sizes".

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.

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.

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.

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.