Abstract
Traditional extraction processes of natural product are widespread, especially in regulated industries. Possibilities of extraction development and manufacturing optimization in regulated industries is limited. Regulatory approvals are often based on traditional preparations of phyto-pharmaceuticals. The dependence on traditional processes can result in sub-optimal extraction parameters causing unnecessary costs and product variability. Innovative methods like Quality-by-Design (QbD), including process analytical technology (PAT), open opportunities for manufacturers to cope with regulatory demanded, narrow batch-to-batch variability. In addition, such validated process models represent perfect digital twins which could be utilized for advanced process control and life cycle analysis.
Highlights
Plant-based products represent a growing market and industry is an important supplier of versatile products
Quality-by-Design (QbD), including process analytical technology (PAT), open opportunities for manufacturers to cope with regulatory demanded, narrow batch-to-batch variability. Such validated process models represent perfect digital twins which could be utilized for advanced process control and life cycle analysis
This generated during experimental process characterization, utilizing common methods, such as statistical data can be generated during experimental process characterization, utilizing common methods, Design of Experiments
Summary
Plant-based products represent a growing market and industry is an important supplier of versatile products. 866assess the possible improvement on biomass valorization, value creation 2 and of 26 productivity increase by adapting the extraction process to the behavior of the extracted components. Model-based process design shortens time-to-market and enables comparison of many different spaces, is shown. Thedigital complexity of the developed model isdifferent stronglyprocess dependent on the to assess the possible improvement on biomass valorization, value creation and productivity increase application of the model. Model-based process design shortens time-to-market and enables comparison of many different during theoretical feasibility studies. Theequations distributed flow model (DPF)conditions can be used tobe consider the effects of axial dispersion in Further, forplug complex equilibrium can implemented. Based appropriate on numerical solutions of the is Navier–Stokes equations, fluid behavior can be processing simulated.
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