(343c) Effects of Tracer Physical Properties and Quantities on the Residence Time Distribution (RTD) of a Continuous Pharmaceutical Manufacturing Line

Over the last decade, the pharmaceutical industry, along with its technology, ingredient, and equipment suppliers, has embraced a worldwide transformation from batch to continuous manufacturing (CM). This shift is due to its potential for enhancing agility, flexibility, and robustness in both product and process development [1-3]. Regulatory agencies, such as the Food and Drug Administration (FDA), have also supported this transition. Starting in 2004, the FDA progressively endorsed CM, from revising the Process Analytical Technology (PAT) guidance to comprehensive guidelines in 2021 [4]. Recent FDA data revealed that drug approvals for products made via CM are, on average, eight months faster than those produced by traditional batch processes [5].

Residence Time Distribution (RTD) is a tool used to understand process dynamics, including understanding of propagation of disturbances through each unit and the degree of back-mixing in a continuous flow system [6]. This is significant for maintaining a state of control [7]. Characterizing RTDs can be utilized to develop control strategies, implementing PAT to track disturbances to products and divert out-of-specification (OOS) materials [6, 8]. A crucial part of RTD characterization involves selecting a tracer representative of an active pharmaceutical ingredient (API) and injecting the tracer into the system without interfering with the bulk flow.

This work continues previous efforts on tracer selection for continuous processing [9, 10], which focused solely on RTD characterization within a continuous blender. Expanding upon this preliminary work, our study focuses on investigating the effects of both physical properties and quantities of the tracer on the RTD of a continuous direct compression (cDC) manufacturing line. An easy-flowing formulation was used: 50% w/w Compap L^TM, 44% w/w Prosolv® HD90, 5% w/w pregelatinized starch, and 1% w/w MgSt. Three tracers were selected from a large material property database by quantifying material similarity between the API (i.e., Compap L) and other materials (i.e., tracer candidates), two of which were most similar to the API, and the third was dissimilar. For each tracer, 6, 15, and 30g were used. Each quantity was individually injected into a blender inlet, and the concentration of the tracer was measured in the feed frame of a tablet press. RTD metrics, including Mean Residence Time (MRT) and time delay, were analyzed to determine the statistically significant effect of tracer quantities and properties using Analysis of Variance (ANOVA). The complete RTD profiles were compared across different tracer masses and materials using Multivariate Analysis of Variance (MANOVA). The results demonstrated that the amount of tracers and tracer properties did not significantly impact the RTDs measured in the feed frame. This can be explained by the feed frame mixing capability, which effectively disperses the disruption caused by the tracer pulse, due to the prolonged residence time of tracers inside the feed frame. The significance of this work is to expand the methodology for choosing the right tracers for the RTD of cDC: for an easy-flowing formulation, we can select a broader range of materials as tracers and inject larger amounts of tracers with better reproducibility without challenging PAT detection limits.

Reference:

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