The continuous manufacturing in the pharmaceutical industry for drug substance synthesis and drug product processing are shifting the manufacturing paradigm. The significant impact of process intensification and continuous manufacturing have been demonstrated for reducing energy, cost, time, waste, and footprint, but improving quality and consistency in quality, and also enabling new type of reactions (by flow-chemistry) and new paradigm in process control. Predictive models can aid process development by estimating the impact of process and equipment parameters, and material attributes (i.e., the model inputs) on product attributes (i.e., the model outputs) thereby providing a quantitative framework for assessing risk and evaluating risk mitigation approaches. In continuous manufacturing multiple synthetic steps can be operated in a single uninterrupted network of reactors. In continuous manufacturing, the dynamic interactions between different unit operations increases the complexity of the system.
Mechanistic models can describe process non-linearities and can be used to control the process and mitigate quality risks. In this work a comprehensive case study is presented, in which first principle models are developed for quality risk assessment of manufacturing processes. Examples of simulation application for drug substance and drug product processes will be discussed. And, the role of modeling and simulation in pharmaceutical process intensification via continuous manufacturing will be demonstrated by steady state and dynamic models.
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