Process systems engineering tools in the pharmaceutical industry

The purpose of this paper is to provide a summary of the current state of the application of process systems engineering tools in the pharmaceutical industry. In this paper, we present the compiled results of an industrial questionnaire submitted to pharmaceutical industry professionals. The topics covered in the questionnaire include process analytics, process monitoring, plant-wide information systems, unit operation modeling, quality control, and process optimization. A futuristic view of what process systems engineering tools will enable the pharmaceutical industry will be also be presented. While the industry is regularly using the traditional Design of Experiments approach to identify key parameters and to define control spaces, these approaches result in passive control strategies that do not attempt to compensate for disturbances. Special new approaches are needed for batch processes due to their essential dependence on time-varying conditions. Lastly, we briefly describe a novel data driven modeling approach, called Design of Dynamic Experiments that enables the optimization of batch processes with respect to time-varying conditions through an example of a simulated chemical reaction process. Many more approaches of this type are needed for the calculation of the design and control spaces of the process, and the effective design of feedback systems.

► Process systems engineering tools in the pharmaceutical industry are summarized.
► A futuristic view of process systems engineering tools usage is presented.
► Traditional approaches for control spaces definition result in passive control.
► A novel data driven modeling approach Dynamic Design of Experiments is presented.
► This novel approach enables batch modeling with time-varying process conditions.