The role of bioprocess simulation is addressed and the specific capabilities required in a bioprocess simulator are defined in this paper. Such a bioprocess simulator has been built and is being used in developing and evaluating the bioprocess for manufacturing porcine growth hormone (pGH). The benefits of bioprocess simulation are demonstrated in this example application by demonstrating how laboratory and pilot plant data can be captured in building a flowsheet model and used to evaluate the process economics and to define priorities for process improvement. Based on available laboratory and pilot plant data and initial assumptions, the BioProcess Simulator was used to develop a flowsheet model of the pGH process. The bioprocess engineer examined the results of the initial simulation in several steps. The first step was to carry out a sensitivity analysis on the assumptions to determine what additional information would be most critical to building a reliable model. Once model confidence was achieved, the next step was to examine how the process could be improved. The number of alternatives and parameters that could be investigated to improve a process is very large. Therefore, the bioprocess simulator was used to help direct and focus this task by serving to prioritize the questions that must be asked and to examine the impact on the whole process as each question is answered. The process proposed was simulated and found to have an overall yield of only 25% with 70% of the manufacturing costs being associated with the downstream recovery. Therefore, the potential for process improvement was large and our first questions were “Where is most of the product loss occurring?” and “What unit operations have the largest contributions to the overall costs?” The simulation has identified that the inclusion body recovery and solubilization and refolding steps are the two largest contributors to products loss, and that the cost of detergent used for inclusion body washing and fractionation as well as the cost of detergent used for inclusion body washing and fractionation as well as the cost of guanidine hydrochloride and urea required for solubilization are contributing substantially to the processing costs. The bioprocess simulator alone will usually not have an immediate answer to problems like these. However, by identifying the critical areas for improvement, research personnel can be appropriately focused on these most critical aspects of the process. The simulator also serves to eliminate those alternatives that have weak potential for being economical solutions, before too much research effort has been invested.
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