Managing API raw material variability during continuous twin-screw wet granulation

Abstract

Very few studies have investigated the impact of raw material variability upon the granule critical quality attributes (CQAs) produced via twin-screw wet granulation (i.e., granule size distribution, density, flowability). In this study, the impact of the raw material variability of an active pharmaceutical ingredient (API) in a high dose formulation on the twin-screw wet granulation process and on the resulting granule quality attributes was investigated. In a previous study (Stauffer et al., 2018), eight API batches were characterized to determine the API batch-to-batch variability. Principal component analysis (PCA) was then used to analyse the raw material property differences between the API batches and to determine the causes of the batch-to-batch variability. In current study, the three principal components from that PCA model were used as factors together with twin-screw granulation process parameters (i.e., screw speed and liquid-to-solid ratio) in a D-optimal screening design of experiments to understand the influence of these factors upon the granule CQAs. It was found that the API particle size distribution and related properties (e.g., density, agglomeration profile) were critical for the granule CQAs. In a next step, the significant factors from the screening design results were used to determine the design space of the twin-screw granulation process for the studied formulation via a D-optimal optimisation design, herewith controlling the risk of failure for the potential API raw material variability. The possibility to obtain suitable granule CQAs with a risk of failure of 1% for all API batches was demonstrated. It was thus possible to identify a combination of process parameters that can manage the API batch-to-batch variability leading to granules with pre-defined suitable CQAs.

Keywords: Continuous manufacturing; Managing active pharmaceutical ingredient variability; Material properties; Multivariate data analysis; Quality by design; Twin-screw granulation.