(377c) Integrated Use of Digital Twin-Based Framework for the Development of a Lomustine Manufacturing Pathway
AIChE Annual Meeting
Friday, November 20, 2020 - 8:30am to 8:45am
In this presentation, the pharmaceutical drug is analyzed under various operational modes, i.e. batch and continuous for various unit operations. Process development was performed starting with parameter estimation from experiments. For example, crystallization kinetic parameters were estimated with metastable width zone determination at the lab scale in batch crystallizers  and nucleation monitoring in microfluidic nitrogen-segmented droplets . We simultaneously developed a digital twin of the process using gPROMS FormulatedProducts to analyze the response of critical quality attributes to process disturbances and better characterize process dynamics under uncertainty. Subsequently, flowsheet simulation and dynamic process analysis via the digital twin was performed. The framework utilizes many computational platforms for analysis by exploiting strengths of different software environments. We utilize Python for parameter estimation and flowsheet simulation, Pyomo for unit operation and flowsheet optimization, and gPROMS FormulateProducts for the digital twin of the process. Thus, the fidelity between gPROMS FormulatedProducts and the custom model library was analyzed as well. The start-to- finish framework is shown to be robust in analyzing different operational modes and conditions in pharmaceutical processing. To demonstrate this capability, we analyze in detail one batch flowsheet, one continuous flowsheet, and one hybrid flowsheet. Here, we compare these flowsheet alternatives manually for proof-of-concept; however, this framework is ultimately to become an end-to-end optimization framework which will algorithmically generate and compare flowsheet alternatives, specifically for the comparison of batch, continuous, and hybrid operational modes.
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