Importance of K_v Distribution in Freeze Drying: Part II: Use in Lyo Simulation Modeling

This article is the second of a series of two articles. In the first article of the series, a new K_v distribution model and an experimental methodology to measure the K_v distribution were introduced. In this second part, the K_v distribution is integrated into a lyo-simulation tool, to more accurately predict the variability of the product temperature, primary drying time, total sublimation mass flow and Pirani signal. The K_v distribution is also integrated into the graphical design space. The impact of incorporating the R_p distribution is briefly discussed. The comparison of the simulation tool with actual product temperature monitoring, Pirani signal or overall sublimation flow shows very good agreement in the case studies presented. Overall, the lyo-simulation incorporating the K_v distribution is a very useful tool to support industrial development, i.e. process optimization, scale assessment, technology transfer, and troubleshooting of the lyophilization process.