(377e) Digital Design of an End-to-End Drug Manufacturing Process Using Mechanistic Modeling

Digital twins built using mechanistic models are playing an increasingly significant role in helping pharmaceutical industries develop robust and more economically efficient manufacturing processes. Building a digital twin for an end-to-end drug manufacturing process allows exploration of individual and combined effects of numerous process parameters and material attributes within the end-to-end process. The end-to-end process includes the active pharmaceutical ingredient (API) and drug product manufacturing stages as well as the final drug product performance. This can allow for the development of a more robust drug manufacturing process and greater assurance of product quality while reducing process development timelines and resources.

This work details an actual application and analysis performed on an existing UCB drug product manufacturing process by building the end-to-end flowsheet model in gPROMS FormulatedProducts, shown in Figure 1. This analysis includes qualitative understanding of the effect of process disturbances, API variability, process parameters, formulation parameters and model uncertainty on tablet properties, and manufacturability key performance indicators (KPIs). Along with this analysis, the relative influence of those factors (sensitivity indices) on the desired tablet properties are presented.

Critical gaps were identified in the scientific understanding of the effects of some of the API and granule attributes on the desired tablet properties and KPIs (e.g. mechanistic link of the particle size distribution to the bulk density of the powder impacting on cohesive forces of powder during roller compaction operation, critical fine fraction generated during the particle forming steps leading to segregation of the powder during powder charge operation and impact on content uniformity, etc.). The importance of data integrity, breaking silos across departments and ensuring correct operating ranges used in the analysis are some of the lessons learnt when developing a digital twin.

This work acts as a starting point for UCB to begin utilizing the end-to-end approach with gPROMS FormulatedProducts as a platform for future drug development pipelines. It also opens up new avenues for scientific understanding in the mechanistic models employed to address the gaps identified during the project (e.g. availability of critical material characterization information for fully exploiting the early adoption of these digital twins in a model risk assessment approach and analysis the feasibility and manufacturability of the drug product production processes). As regards gaps in science, these will be addressed either through improving mechanistic understanding or incorporating data driven elements in the overall mechanistic end-to-end process model.