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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.

Increases in mammalian cell culture titres and densities have placed significant demands on primary recovery operation performance. This article presents a methodology which aims to screen rapidly and evaluate primary recovery technologies for their scope for technically feasible and cost‐effective operation in the context of high cell density mammalian cell cultures. It was applied to assess the performance of current (centrifugation and depth filtration options) and alternative (tangential flow filtration (TFF)) primary recovery strategies. Cell culture test materials (CCTM) were generated to simulate the most demanding cell culture conditions selected as a screening challenge for the technologies. The performance of these technology options was assessed using lab scale and ultra scale‐down (USD) mimics requiring 25–110mL volumes for centrifugation and depth filtration and TFF screening experiments respectively. A centrifugation and depth filtration combination as well as both of the alternative technologies met the performance selection criteria. A detailed process economics evaluation was carried out at three scales of manufacturing (2,000L, 10,000L, 20,000L), where alternative primary recovery options were shown to potentially provide a more cost‐effective primary recovery process in the future. This assessment process and the study results can aid technology selection to identify the most effective option for a specific scenario.

ABSTRACT:This paper describes a decision-support tool that integrates Monte Carlo simulation data derived using a stochastic discrete-event simulation model to mimic process fluctuations with advanced multivariate statistical techniques to help pinpoint the potential root causes of sub-optimal short term facility fit issues. Principal component analysis combined with clustering algorithms was used to analyse the complex datasets from complete industrial batch processes for biopharmaceuticals. The challenge of visualising the multidimensional nature of the dataset was addressed using hierarchical and K-means clustering as well as parallel co-ordinate plots to help identify process fingerprints and characteristics of clusters leading to sub-optimal facility fit issues. Industrially-relevant case studies are presented that focus on technology transfer challenges for therapeutic antibodies moving from early phase to late phase clinical trials. The case study details how sub-optimal facility fit can be alleviated by allocating alternative product pool tanks. The impact of this operational change is then assessed by reviewing an updated process fingerprint.