Issue link: https://www.e-digitaleditions.com/i/1371139
22 May/June 2021 Tablets & Capsules materials that will be suitable for operating a process over extended periods of time. For oral solid dosage (OSD) products, a particle engineering approach can be useful for such purpose, where material properties of the excipients and in-process materials are assessed during formulation design to understand the impact of properties such as par- ticle size and distribution, flow behavior under different process stresses, and bulk and tapped densities. Additionally, generating both in-specification and out-of-specification (OOS) product should inform robust process conditions. Again, using OSD products as an exam- ple, these studies would include assessing the performance of unit operations, such as loss-in-weight feeders, that are critical to achieving dose uniformity and potentially using raw materials with varying physical attributes. Developing an understanding of the overall process cycle time and how the machine speed for each stage of a continuous process affects critical product performance attributes are also important. To this end, a carefully planned and executed DOE to determine the cause-and-effect relationship between the factors affecting a process and product is indispensable. How is quality assurance improved with continuous manufacturing processes? Tony Stuckwisch, RPh, director, quality assurance, Parsolex: Quality indicating data (such as yield and concentration) is available in real time in a continuous process rather than only at the end of a batch. Feedback loops and properly designed control systems minimize the impact of small disturbances. Continuous processes require less dependence on manual intervention and manual product handling, reducing the risk of errors. The risk of OOS material going undetected and not being rejected is reduced. To successfully operate a continuous process, a high degree of process understanding is essential. Michaelis: Quality by Design (QbD) and the use of auto- mated product development tools, such as automated DOE, allow for more information in development and will help robust processing in production. Also, the avoidance of scale up will increase quality in production and reduce risks. In the Xelum process, each X-key contains all manufacturing data, such as raw material data, CQAs, CPPs, and sensor data, allowing for fingerprint comparison between X-keys to keep the process within specification. What are the challenges with equipment cleaning or cleaning validation and product changeover for continuous manufacturing compared to batch manufacturing? Pearce: The primary challenges for equipment clean- ing and changeover for continuous process equipment are time and complexity. Continuous manufacturing pro- cesses require more complex equipment than conventional batch equipment. To minimize cleaning time, continuous process equipment should be designed for cleanability (free- draining, with no dead legs) and should leverage clean-in-place (CIP) systems where appropriate. Cleanable equipment with CIP results in more reproducible cleaning The sampling strategy for product release testing is another challenge that may differ for products manufac- tured using a continuous approach versus a batch approach. Whereas samples are physically removed at discrete stages of a batch for the purpose of in-process testing or final product release testing, sampling during a continuous pro- cess is defined by time and frequency using online tools. During the initial scaleup and validation of the continuous process, on-line detection methods may need to be verified by off-line laboratory test methods. Michaelis: Monitoring content uniformity over the com- plete continuous process with adequate time resolution is the most critical challenge, especially for products with low API concentrations or complex material properties. The trace- ability of typical fluctuations in the powder flow and the determination of RTD is requiring additional development effort. The analytical strategy must be set up following a risk-based approach to evaluate which risks might addi- tionally occur compared to a classical batch process. Here, dosing plays an important role, as it differs significantly between batch and continuous manufacturing. In a continuous setup, feeders must be refilled from time to time. During refill, the feeder's weight signal cannot be used, which means that the loss-in-weight feeders are run- ning "blind" in volumetric mode for about 10 percent of the overall processing time. While some systems use algorithms to compensate for these interruptions, volumetric dosing is still risky, especially for non-particle-engineered substances such as APIs at low feed rates. Algorithms cannot predict for all possible incidents, such as bearding, ratholing, lumps, vibration, or shocks. Regulatory bodies have also recognized this. As a result, redundant measurement systems such as spectrometers are needed to verify the dosing accuracy. An alternative dosing system such as the one used by the Xelum can eliminate this disadvantage. What are the critical studies to develop a continuous process? Michaelis: Besides the design of experiments (DOE) stud- ies, the development of suitable PAT and RTD models are critical, especially considering the increased material consumption. All inline testing methods must be validated, therefore test results determining whether a product portion needs to be released or rejected must be correlated to a respective amount of product. Syntegon's Xelum process offers an advantage here because the system's design doesn't necessarily require RTD and PAT functions, yet it can inte- grate all inline tests applicable for continuous processing. Material traceability is simplified in the Xelum system, which precisely doses ingredients in mini packages, called X-keys, which can be traced throughout the production process. Ammar Khawam, PhD, MBA managing scientist, development solutions, Parsolex: A robust continuous process necessitates a clear understanding of the raw material properties and the performance of unit operations. For example, taking a fit-for-purpose approach to selecting raw materials and excipients is essential not only for achieving the critical product performance attributes, but also for identifying