Inline monitoring and a PAT strategy for pharmaceutical hot melt extrusion
Graphical abstract
Monitoring of extrusion dynamics with in-line NIR spectroscopy.
Introduction
Over last hundred years and longer, batch processing was the prevailing way to produce pharmaceuticals. However, continuous manufacturing may reduce the required investment capital, labour costs, product waste and can in many cases offer a better product quality (Plumb, 2005). Especially the last point, i.e., the control of product quality makes continuous manufacturing an attractive alternative to current production paradigms. However, continuous manufacturing needs strict process control, since end-of-pipe testing is not feasible in such an environment. Moreover, due to the typically small product volume even short process upsets (e.g., during hopper refilling) can lead to significant output fluctuations (Schenck et al., 2011). As such, to ensure constant product quality, an adequate control strategy of the entire process must be established.
Hot melt extrusion (HME) is a continuous process that has significant potential for the manufacturing of different dosage forms with an improved control of the drug release profile (Breitenbach, 2002, Roblegg et al., 2011). The process is well-known and commonly used in plastics industries. HME combines several unit operations in one process to produce homogeneous strands of molten material. The material is typically fed with volumetric or loss-in-weight feeders in the intake zone of the extruder. The solids melt in the plastification zone due to high shear forces and to a lesser extent due to heat transfer via the extruder barrel. Next, the melt is devolatized and subsequently forced into an extrusion die. Depending on the screw configuration, the extruder has a certain mixing capability. Mixing occurs between the plastification zone and the extrusion die, and the extent of mixing depends on the screw design. Cross-sectional mixing is driven by drag flow and back (axial) mixing is driven by pressure flow (Rauwendaal, 2001). Acting as a low pass filter, an extruder can compensate for short-time feeder disturbances in the order of seconds. However, long-term disturbances can affect the product (Mudalamane and Bigio, 2003, Schenck et al., 2011). Feeding is another aspect that depends on many factors (Schenck et al., 2011). Thus, tight process control, e.g., via spectroscopic tools, is essential for a successful implementation.
Near-infrared (NIR) and Raman spectroscopy have been extensively reviewed in literature and have been commonly used in the pharmaceutical industry (De Beer et al., 2011, Gendrin et al., 2008, Roggo et al., 2007, Vankeirsbilck et al., 2002). They have mainly been applied to measure uniformity during blending and moisture content during granulation and drying, to study chemical or physical interactions and to perform coating analysis. With regard to extrusion, NIR has been used to determine the active pharmaceutical ingredient (API) content of extruded films (Tumuluri et al., 2004) and the API content and polymer-API interaction directly in the die (Saerens et al., 2012). Raman spectroscopy has been applied to determine the API content of a melt extruded film (Tumuluri et al., 2008) and for solid state characterization of the melt (Saerens et al., 2011). Both spectroscopic techniques were applied to monitor PE/PP (polyethylene/polypropylene) blends during polymer extrusion (Fischer et al., 1997) (often in combination with ultrasound analysis for blend composition of PE/PP (Barnes et al., 2005, Coates et al., 2003)). For details concerning advantages and drawbacks of each method see (Alig et al., 2005).
Many measurement approaches that are successfully used for research purposes (e.g., a custom-made slit die to hold the probes or at-line measurements) can be difficult to implement for industrial downstream processes, such as die-face pelletizing or calendaring. But the FDA increasingly suggests in-line monitoring and process control of manufacturing processes via the process analytical technology (PAT) initiative (FDA, 2004). Therefore PAT tools (e.g., spectroscopy) are required, which are not restricted to research only, but can be implemented in a manufacturing environment. Hence in-line NIR spectroscopy can be a valuable tool for process control strategies.
The current study presents a PAT strategy for the production of an API (paracetamol) embedded in a calcium stearate (CaSt) matrix via HME. The API content of the melt was assessed with an NIR probe mounted in-line, close to the extrusion die. Using this setup the extrusion process was monitored to gain a better understanding of the factors impacting content uniformity (CU), as well as API content. Experiments were performed and the extrudate concentration was analyzed with the NIR probe, according to an experimental design involving different API concentrations, screw speeds and screw designs.
Section snippets
Materials
The matrix carrier for the extrusion was CaSt (Werba-Chem GmbH, Austria; mean particle size 16.62 μm) and API was paracetamol (GL Pharma GmbH, Austria, mean particle size 139.2 μm). The paracetamol crystals were embedded in CaSt resulting in a solid dispersion. At the processing temperature CaSt is within its smectic liquid crystalline state and paracetamol remains crystalline. The formulation of CaSt and paracetamol, including different plasticizers, introduced by Roblegg et al. (2011), offers a
Theory of sampling considerations
Sampling, either by classical thief sampling based on offline analysis or performed in-line with PAT sensors, is critical for correct measurements. The practical rules defined by the theory of sampling (TOS) (Esbensen and Paasch-Mortensen, 2010) were applied to evaluate different measurement positions of the in-line PAT sensor during the extrusion process.
For this purpose the material stream in the 8-0 adapter was approximated as a pressure-driven flow through a pipe. For a material flowing
Conclusion
This paper presented the development and application of a PAT strategy for quality control of a pharmaceutical hot-melt extrusion process with in-line NIR spectroscopy. Measurements were performed close to the die, in the 8-0 adapter. A chemometric model was developed in a range of 0–60% API content. Predictions were in good agreement with the pre-set API content (as determined via the feeding rates) and with the offline HPLC reference measurements.
The 8-0 adapter was modified for proper sample
Acknowledgements
The authors thank G.L. Pharma GmbH (Lannach, Austria) for supporting this work and providing paracetamol and CaSt. Furthermore, the authors would like to thank the extrusion group at the RCPE GmbH for their great effort.
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