(400f) Dynamic Optimization of Continuous Manufacturing of Pharmaceuticals

Continuous manufacturing (CM) of pharmaceuticals is being explored as an alternative to traditional batch-wise production. This shift holds great promise to increase production efficiency, enable smaller production facilities, minimize waste, energy consumption, and raw material use and to enable drug quality monitoring on a continuous basis. However, implementing CM in the pharmaceuticals industry implies short operational campaigns, with significant transient phases (start-up and shutdown), constituting up to 30% of the entire time horizon. This significantly hampers the plant's economic feasibility. Efforts to optimize the overall production process involve mathematical modeling and solution of hybrid (discrete-continuous) systems embedding differential-algebraic equations (DAEs), along with the associated parametric sensitivity trajectories to be used in rigorous gradient-based optimization algorithms.

In this contribution, these efforts will be described, addressing the numerical issues related to the hybrid and non-smooth nature of the mathematical model. A case-study pilot plant model incorporating several synthesis, separation and purification steps to produce final tablets [1] is used for demonstration. The dynamic optimization approach that is employed maximizes the accumulated on-spec production directly over the entire time horizon (so-called Economic-Optimization), while guaranteeing differentiability with respect to the controls [2]. Optimization results will be presented followed by a discussion on the process design and formulation and the intelligent choice of the open-loop control decision variables.

[1] S. Mascia et al., "End-to-End Continuous Manufacturing of Pharmaceuticals: Integrated Synthesis, Purification, and Final Dosage Formation", Angew Chem. Int. Ed. Engl., 2013, 52(47), 12359-63

[2] A. Sahlodin and P.I. Barton, "Optimal Campaign Continuous Manufacturing", Ind. Eng. Chem. Res., 2015, 54(45), 11344-59.