Increases in cell culture titers in existing facilities have prompted efforts to identify strategies that alleviate purification bottlenecks while controlling costs. This article describes the application of a database-driven dynamic simulation tool to identify optimal purification sizing strategies and visualize their robustness to future titer increases. The tool harnessed the benefits of MySQL to capture the process, business, and risk features of multiple purification options and better manage the large datasets required for uncertainty analysis and optimization. The database was linked to a discrete-event simulation engine so as to model the dynamic features of biopharmaceutical manufacture and impact of resource constraints. For a given titer, the tool performed brute force optimization so as to identify optimal purification sizing strategies that minimized the batch material cost while maintaining the schedule. The tool was applied to industrial case studies based on a platform monoclonal antibody purification process in a multisuite clinical scale manufacturing facility. The case studies assessed the robustness of optimal strategies to batch-to-batch titer variability and extended this to assess the long-term fit of the platform process as titers increase from 1 to 10 g/L, given a range of equipment sizes available to enable scale intensification efforts. Novel visualization plots consisting of multiple Pareto frontiers with tie-lines connecting the position of optimal configurations over a given titer range were constructed. These enabled rapid identification of robust purification configurations given titer fluctuations and the facility limit that the purification suites could handle in terms of the maximum titer and hence harvest load. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 28: 1019–1028, 2012
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