Development of a Granule Growth Regime Map for Twin Screw Wet Granulation Process via Data Imputation Techniques

Abstract

Twin screw granulation (TSG) is a continuous wet granulation technique that is used widely across different solid manufacturing industries. The TSG has been recognized to have numerous advantages due to its modular design and continuous manufacturing capabilities, including processing a wide range of formulations. However, it is still not widely employed at the commercial scale because of the lack of holistic understanding of the process. This study addresses that problem via. the mechanistic development of a regime map that considers the complex interactions between process, material, and design parameters, which together affect the final granule quality. The advantage of this regime map is that it describes a more widely applicable quantitative technique that can predict the granule growth behavior in a TSG. To develop a robust regime map, a database of various input parameters along with the resultant final granule quality attributes was created using previously published literature experiments. Missing data for several quality attributes was imputed using various data completion techniques while maintaining physical significance. Mechanistically relevant non-dimensional X and Y axis that quantify the physical phenomena occurring during the granulation were developed to improve the applicability and predictability of the regime map. The developed regime map was studied based on process outcomes and granule quality attributes to identify and create regime boundaries for different granule growth regimes. In doing so breakage-dominant growth was incorporated into the regime map, which is very important for TSG. The developed regime map was able to accurately explain the granule growth regimes for more than 90% of the studied experimental points. These experimental were generated at vastly different material, design, and process parameters across various studies in the literature, this further increases the confidence in the developed regime map.