The development of a compartment model to simulate mixing within a continuous blender is reported. The main benefit of the method is that it can generate extensive modeling predictions in very short computational time. The model can also be used to explore the effect of sampling parameters on estimated mixing performance, a topic that has been central to pharmaceutical manufacturing for the past fifteen years and that remains a central issue in the PAT initiative. The simulation presented here is able to capture the effects of feeding rate variability (number of particles), API concentration (ratio between the two different particle ratios), while effectively capturing, and making explicit, the effect of sampling parameters such as number of samples and sample size (number of particles per sample). The modeling approach provides a convenient tool for process design.

The authors would like to thank the National Science Foundation for their financial support through grants NSF-0504497 and NSF-ECC 0540855 both to Fernando J. Muzzio as well as the Nanopharmaceutical IGERT Fellowship to Patricia M. Portillo.

Patricia M. Portillo, Fernando J. Muzzio, and Marianthi G. Ierapetritou, Using Compartment Modeling to Investigate Mixing Behavior of a Continuous Mixer, Journal of Pharmaceutical Innovation 3(3)(2008) 161-174.

Researchers should cite this work as follows:

• Patricia Portillo (2014), "Compartment Modeling," https://pharmahub.org/resources/compartmodel.

  BibTex | EndNote

1. Compartment model
2. Process modeling