A shortcut approach for decision-making and operational analysis of an integrated end-to-end continuous pharmaceutical process [Abstract]

A shortcut approach for decision-making and operational analysis of an integrated end-to-end continuous pharmaceutical process [Abstract

Modelling continuous pharmaceutical and bio-based processes at plant-wide level: A roadmap towards efficient decision-making

The importance of developing simulation models for decision-making in pharmaceutical and bio-based production processes is elaborated in this article. The advantages of modelling continuous processes are outlined and certain barriers in this regard are identified. Although there have been some advancements in the field, there needs to be a larger international collaboration in this regard for providing reliable data for model validation, for development of generic model-based frameworks and implementing them in computer-aided platforms in the form of software tools

Transforming data to information: A parallel hybrid model for real‐time state estimation in lignocellulosic ethanol fermentation

Operating lignocellulosic fermentation processes to produce fuels and chemicals is challenging due to the inherent complexity and variability of the fermentation media. Real‐time monitoring is necessary to compensate for these challenges, but the traditional process monitoring methods fail to deliver actionable information that can be used to implement advanced control strategies. In this study, a hybrid‐modeling approach is presented to monitor cellulose‐to‐ethanol (EtOH) fermentations in real‐time. The hybrid approach uses a continuous‐discrete extended Kalman filter to reconciliate the predictions of a data‐driven model and a kinetic model and to estimate the concentration of glucose (Glu), xylose (Xyl), and EtOH. The data‐driven model is based on partial least squares (PLS) regression and predicts in real‐time the concentration of Glu, Xyl, and EtOH from spectra collected with attenuated total reflectance mid‐infrared spectroscopy. The estimations made by the hybrid approach, the data‐driven models and the internal model were compared in two validation experiments showing that the hybrid model significantly outperformed the PLS and improved the predictions of the internal model. Furthermore, the hybrid model delivered consistent estimates even when disturbances in the measurements occurred, demonstrating the robustness of the method. The consistency of the proposed hybrid model opens the doors towards the implementation of advanced feedback control schemesThis project has been partially supported by the Energy Technology Development and Demonstration Program in the frame of the project “Demonstration of 2G ethanol production in full scale” (Grant Number 64015‐0642), and has been realized together with Maabjerg Energy Center. The support of the BIOPRO2 Strategic Research Center (Grant Agreement No. 4105‐00020B) is gratefully acknowledged. The authors wish to acknowledge the support provided by the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska‐Curie Grant Agreement Number 713683 (COFUNDfellowsDTU), by the Danish Council for Independent Research in the frame of the DFF FTP research project GREENLOGIC (Grant Agreement Number 7017‐00175A), and by Novo Nordisk Fonden in the frame of the fermentation‐based biomanufacturing education initiative. Miguel Mauricio‐Iglesias belongs to the Galician Competitive Research Group ED431C 2017/029 and the CRETUS Strategic Partnership (AGRUP2017/01)S