Process Understanding in the Context of QbD: Current Approaches and Desired State

The development of process understanding is a critical element of the quality design framework. In this context, designed experiments are currently considered the best method for developing process understanding, mostly via MVDA models. However these models lack extrapolatory capabilities, are scale-dependent and may miss critical system behavior. Thus, novel approaches are required that rely on mechanistic understanding of the processes. Several methods, which also can be used for rational risk ranking, are presented in this talk. Moreover, their respective advantages over the current methods are discussed.

In the presentation a model is presented of how detailed high-fidelity computer simulations can be used to support a quantitative risk evaluation process and how a scale-dependent design space can be transformed for routine manufacturing. Specifically, the coating of tablets and the mixing of powders are considered as model processes. For the purpose of these simulations advanced DEM and CFD tools are applied, in combination with advanced material characterization tools.