An Experimental and Computational Approach to Development of Mixing Processes for Miscible Liquids in Unbaffled Tanks

Mixing of liquids is a critical unit operation in the biopharmaceutical drug product manufacturing. It commonly consists of mixing miscible liquids to dilute bulk drug substance (DS) or pool multiple lots of drug substance. In the past, at-scale mixing studies have been conducted to determine the mixing parameters, namely mixing speed, and mixing time. At-scale studies have historically been utilized to overcome the challenges associated with geometric dissimilarity of mixing systems found when scaling up. In addition, such studies are quite costly, as they often use actual DS to overcome a lack of representativeness associated with simple salt trace models often employed. As a result, there is a significant need for alternative cost-effective methods that can predict mixing parameters with close agreement to actual experiments and operations.

At-scale mixing experiments were conducted using full-sized tanks and surrogate solutions. Several computational fluid dynamic (CFD) simulation methods were conducted and compared with the experiments to determine the most reliable computational techniques.

The experiments demonstrate that surrogate solutions can be used reliably to determine mixing parameters in at-scale studies instead of the valuable drug products. Studying different CFD methods also showed that transient simulations that use a large eddy simulation (LES) viscous model and a sliding mesh can correctly predict the mixing parameters.

Results of this study establish a practical and reliable methodology to perform mixing studies for miscible liquids with different kinematic viscosities. The methods discussed herein greatly reduce the routine mixing study costs in the biopharmaceutical industry and increase efficiency and accuracy of the results, allowing proactive scale-up of mixing operations.