(328e) Multiscale Modeling of a Plug Flow Reactor for a Continuous Drug Substance Manufacturing Process

Yazdanpanah, N., U.S. Food and Drug Administration
O'Connor, T., U.S. Food and Drug Administration
Cruz, C. N., U.S. Food and Drug Administration
A simple tabular reactor (at different sizes) for a Friedel-Craft acylation reaction, conventionally being used in continuous manufacturing of drug substance (flow-chemistry), is simulated at macro and micro level. The effect of reactor dimensionality and flow rate on dispersion and deviation of models from ideal plug flow regime is investigated. A Finite Element Method model, with radial and axial discretization, and a Distributed Lumped Model with axial discretization are used to simulate the reactor’s transport phenomena (at low Reynolds number) and the reaction (endothermic). The reaction modeling accuracy is compared with reported experimental values for model validation analysis. The model demonstrates the RTD and dispersions in the reactor and effects of process parameter on deviations from ideal plug flow regime.

In Quality by Design framework, mathematical models can be utilized at every stage of product development and manufacturing including risk management. 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. The emerging technology, continuous manufacturing, is a potential driving force for the utilization of process modeling and simulation. Mechanistic model can describe process nonlinearities and can be used to control the process and mitigate quality risks. Process modeling and simulation and given that process design, integration, evaluation, scale up, and optimization can be performed for the overall process once individual process unit have been characterized mathematically using models.