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.

Quantitative on-line vs. off-line NIR analysis of fluidized bed drying with consideration of the spectral background.

Quantitative dehydration studies of dibasic calcium phosphate anhydrous (DCPA) in a small-scale cold-model fluidized bed dryer with process air control were conducted. Near-infrared spectroscopy (NIRS) with partial least squares regression (PLSR) was used to predict DCPAs' residual moisture content. Loss-on-drying (LOD) was employed as a reference method and confirmed the actual moisture content of DCPA. First, dynamic PLSR modeling was carried out, i.e., the NIR spectra were on-line recorded and predicted throughout the drying process. Secondly, PLSR off-line modeling was performed, i.e., samples were consecutively thief-probed from the processor, put into glass vials and analyzed off-line. Furthermore, two background spectra were collected prior to the in- and off-line measurements in an attempt to increase the method's sensitivity, i.e., (i) dry DCPA that was fluidized at respective process air velocity (on-line) or inside a glass vial (off-line) and (ii) Spectralon®--a highly reflecting standard reference material made of fluoropolymer. Benefits and drawbacks of the in- and off-line approaches with different spectral backgrounds are discussed in detail. The results indicated that (i) the thief-probed sample amount from the processor and thus the sample weight and (ii) the downtime between thief-probing a sample and its actual analysis via NIRS and LOD can bias the moisture content predictions.