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TPLS as predictive platform for twin-screw wet granulation process and formulation development

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In recent years, there has been a growing interest in continuous manufacturing techniques, such as twin-screw wet granulation. However, our comprehension of how the combination of raw material properties and process settings influences granule quality attributes remains limited. This study aimed to address this gap by developing a T-shaped partial least squares (TPLS) model. This model establishes connections between raw material properties, the ratios at which these materials are combined, and the applied process parameters in twin-screw wet granulation, with a focus on granule quality attributes. Additionally, the predictive capability of the TPLS model was utilized to identify an optimal combination of formulation composition and twin-screw granulation process settings for a new Active Pharmaceutical Ingredient (API), ensuring the achievement of desired granule quality attributes. In essence, this study contributes to a better understanding of the intricate relationships among raw material properties, formulation composition, and process settings, ultimately impacting granule quality attributes. Moreover, TPLS serves as a valuable starting point for formulation and process development for new APIs, potentially reducing the need for extensive experimental efforts and mitigating the consumption of expensive and often limited new API resources.
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