Dynamic Optimization of a Batch Pharmaceutical Reaction using the Design of Dynamic Experiments (DoDE): the Case of an Asymmetric Catalytic Hydrogenation Reaction

Abstract

The present research work aims to demonstrate the effectiveness of the new methodology of Design of Dynamic Experiments (DoDE) in optimizing an important pharmaceutical reaction. An easily developed response surface model (RSM) is used instead of a hard to develop knowledge-driven process model. The DoDE approach allows the experimenter to introduce dynamic factors in the design, which during the RSM optimization are treated as all the other factors, simplifying the analysis significantly, leading to the rapid optimization of batch processes with respect to time-varying decision variables. The DoDE approach enables the discovery of optimal time-variant operating conditions that are better than the optimal time-invariant conditions discovered by the classical Design of Experiments (DoE) approach. In the present case of the asymmetric catalytic hydrogenation, 24 experiments are conducted for the DoDE approach and the best run results in a 45% improvement comparing to the best run of 17 runs of the DoE approach. This is achieved by applying a decreasing temperature profile during the batch reaction. Optimization of the economic performance index of the process through the respective response surface models defines an optimum operation. The DoDE optimum operation is better than the respective one through the DoE. The DoDE advantage increases as the required quality level for the final product is higher. For the medium quality, the DoDE approach results in an improvement of 30% over the DoE one.