(377f) Digital Design of a Dry Granulation-Based Drug Product through Integrated Manufacturing Process and Product Performance Modeling

Motivated by aims to improve R&D efficiency, reduce time to market, and develop robust drug products, the pharmaceutical industry has seen increased application of mechanistic-based system models. Such approach establishes science-based understanding of relationships between various process parameters and Quality Attributes (QAs) with reduced experimentation requirements.

The primary objective of this study is to demonstrate system model of a dry granulation-based drug product manufacturing process with in-vitro dissolution. This approach is used to determine the effect of drug product manufacturing process on tablet (API) dissolution. The system model, which was developed in gPROMS FormulatedProducts, couples multiple unit operations together, namely roller compaction, screen milling, lubrication, tablet compression, and in vitro dissolution. The roller compactor and the tablet press were calibrated by estimating the respective compaction-related model parameters against experimental data for ribbon and tablet properties. In order to capture the effect of the disintegration of the tablet solid matrix on the delayed API dissolution, a hierarchical description of the tablet and a porosity-dependent disintegration scheme was adopted. The in-vitro dissolution was calibrated by estimating the tablet and granule disintegration kinetic parameters in order to capture the dissolution profile of the API.

Following model development activities, the system model (Figure 1) was used to assess the impact of the drug product manufacturing process parameters on API dissolution. Monte Carlo and variance-based analyses were performed using gPROMS FormulatedProducts’ Global System Analysis framework to understand the relationship between drug product process parameters and API dissolution. Such framework can be effectively used in the workflow of pharmaceutical product development to define the input vs output relationships between process parameters and product performance. Furthermore, it has the potential to significantly contribute to QbD framework.

Figure: An integrated drug product and in-vitro dissolution model in gPROMS FormulatedProducts