System model driven selection of robust tablet manufacturing processes based on drug loading and formulation physical attributes
Mechanistic process modeling presents an opportunity to reduce experimental burden, enabling relationships between process parameters and product attributes to be mapped out using in-silico experiments. A system model of a pharmaceutical tablet manufacturing process comparing dry granulation with direct compression is developed to answer key material and process design questions. The system model links API physical properties and formulation to process parameters to map out the robust operating space. To demonstrate the application of the model, several drug product formulation design questions were considered:
- Which processing route is the most robust given the API material properties and dosage requirements?
- How does drug loading and tablet size impact the robustness of the manufacturing process?
- What process settings are required for a robust manufacturing route for the API material properties and drug loading requirements?
A computational framework was developed using the system models to generate process classification and design space maps to aid robust pharmaceutical formulation and process decision making. Process classification maps were produced to assess the feasibility of roller compaction and direct compression for different material properties and formulations. Constraints on the critical quality attributes of the intermediate and final products were defined using the Manufacturing Classification System. Design space maps presented here demonstrate how system models can be used to support formulation and process design. The design space maps illustrate how the process operating space can be increased or decreased as the API mass fraction is varied.
The process design and selection system model demonstrate how an understanding of the API physical properties can be used to model the impact of formulation and process design. Furthermore, these models can be instrumental in the dialogue with colleagues developing the API in order to set the requirements of the API physical properties to ensure successful and robust formulation and process designs.
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Article information: Leah R. White, Matthew Molloy, Robert J. Shaw, Gavin K. Reynolds, System model driven selection of robust tablet manufacturing processes based on drug loading and formulation physical attributes, European Journal of Pharmaceutical Sciences, Volume 172, 2022. https://doi.org/10.1016/j.ejps.2022.106140.