Determining the Impact of Roller Compaction Processing Conditions on Granule and API Properties.

The attrition of drug particles during the process of dry granulation, which may (or may not) be incorporated into granules, could be an important factor in determining the subsequent performance of that granulation, including key factors such as sticking to punches and bio-performance of the dosage form. It has previously been demonstrated that such attrition occurs in one common dry granulation process train; however, the fate of these comminuted particles in granules was not determined. An understanding of the phenomena of attrition and incorporation into granule will improve our ability to understand the performance of granulated systems, ultimately leading to an improvement in our ability to optimize and model the process. Unique feeding mechanisms, geometry, and milling systems of roller compaction equipment mean that attrition could be more or less substantial for any given equipment train. In this work, we examined attrition of API particles and their incorporation into granule in an equipment train from Gerteis, a commonly used equipment train for dry granulation. The results demonstrate that comminuted drug particles can exist free in post-milling blends of roller compaction equipment trains. This information can help better understand the performance of the granulations, and be incorporated into mechanistic models to optimize such processes.

Lubrication empirical model to predict tensile strength of directly compressed powder blends.

A new approach is proposed to support prediction of tablet tensile strength as a function of both solid fraction (and/or compression pressure) and extent of lubrication by using empirical data to parameterise the model. This is a pre-requisite for simulation of the compaction unit operation where a linkage from tablet press operating parameters and formulation material properties to output tensile strength is required. The approach extends the previously published Kushner and Moore model to allow calculation across a range of solid fractions. The applicability of the approach is supported by testing using formulations with different commonly used pharmaceutical excipients.

Computational Fluid Dynamics-Discrete Element Method Modeling of an Industrial-Scale Wurster Coater.

Large-scale fluid bed coating operations using Wurster coaters are common in the pharmaceutical industry. Experimental measurements of the coating thickness are usually analyzed for just few particles. To better predict the coating uniformity of the entire batch, computational techniques can be applied for process understanding of the key process parameters that influence the quality attributes. Recent advances in computational hardware, such as graphics processing unit, have enabled simulations of large industrial-scale systems. In this work, we perform coupled computational fluid dynamics-discrete element method simulations of a large-scale coater that model the actual particle sizes. The influence of process parameters, inlet air flow rate, atomizing air flow rate, bead size distribution, and Wurster gap height is studied. The focus of this study is to characterize the flow inside the coater; eventually, this information will be used to predict the coating uniformity of the beads. We report the residence time distribution of the beads inside the Wurster column, that is, the active coating zone, which serves as a proxy for the amount of coating received by the beads per pass. The residence time provides qualitative and quantitative measurements of the particle-coating uniformity. We find that inlet air flow rate has the largest impact on the flow behavior and, hence, the coating uniformity.