Soft sensors to predict critical quality attributes and monitor crystallinity and polymorphism change in solid oral dosage manufacturing: case studies

Abstract

In the past decades, the advancement of sensor technology has enabled the development and application of reliable process analytical technology in pharmaceutical manufacturing for process monitoring and control. Soft sensors as mathematical models are often coupled with process analytical technology tools to monitor critical quality attributes such as concentrations and particle sizes. Crystallinity and polymorphism changes are prevalent phenomena in pharmaceutical manufacturing. These changes may impact drug manufacturability, drug quality, and patients’ safety. Therefore, assessment of impact of crystallinity and polymorphism change has been one critical aspect of pharmaceutical chemistry, manufacturing, and control review and inspection. Chemistry, manufacturing, and control risk assessment has been largely qualitative in nature and has heavily relied on past knowledge and experience. The potential use of soft sensors to monitor such changes and establish a science supported risk-based control strategy is not widely discussed. In this work, by applying soft sensor models to key unit operations, we presented case studies to discuss the capability and potential of soft sensors in predicting critical quality attributes for key pharmaceutical unit operations, including crystallinity and polymorphism changes in selected drugs with moderate to high solid-state risk levels in drug product manufacturing. Population balance models, semi-empirical models, and statistical correlations are applied to wet granulator, fluidized bed dryer, mill, and tablet press to enable soft sensing. Sensitivity analysis using the established models is conducted to quantitatively assess the impacts of process inputs onto different outputs to support a risk-based control strategy with regulatory insights. Knowledge, experience, and discussion in these aspects can contribute to the future development of advanced technologies and the implementation of modeling tools toward advanced manufacturing.

Graphical abstract

Keywords

soft sensor / crystallinity / polymorphism / process modeling / regulatory science

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