Analyzing the effects of control Strategies for Determining Process Feasible Space

The identification of process Design Space (DS) is key to support the development of pharmaceutical processes, where strict requirements on manufacturability and product quality must be satisfied. If the process can be controlled by a set of manipulated variables, the DS can be enlarged with respect to an open-loop scenario, where there are no controls in place. Since pharmaceutical models are typically complex and computationally expensive, surrogate-based feasibility analysis can be suitably exploited to determine whether the process satisfies all constraints by adjusting the process control inputs, and mitigate the effect of uncertainty. The approach is successfully implemented on a pharmaceutical case study; results demonstrate that different control actions can be effectively exploited to mitigate uncertainty and operate the process in a wider range of inputs. The framework can conveniently be exploited to support decisions on control strategies for real industrial applications.