High-Throughput Micro-Scale Cultivations and Chromatography Modeling

Up- and downstream – going hand in hand for an integrated process characterization of a cherry-tagged enzyme

Figure: Pareto fronts for yield and purity of the five randomly picked experiments and the global pareto front. The Pareto fronts of the 27 °C setups are shown as blue stars, the 32 °C setups as red and orange stars, and the 37 °C setup as a green stars.

Upstream processes are hard to predict and therefore complex to design. High throughput cultivation screenings in micro-scale format are performed to create an appropriate design space. But the highest titer of cultivation must not lead to overall superior process performance.

Cultivation conditions are of fundamental importance to downstream processing. Critical impurities, which elute close to the product, influence the process performance largely. Therefore, the complexity of protein purification procedure strongly depends on the cultivation conditions. However, up- and downstream processes are mostly developed separately. For an overall superior performance in up- and downstream, both processes should be developed conjointly.

Combination of high throughput cultivation screening and chromatography modeling. A combined process characterization was investigated for a cherry-tagged enzyme. High throughput experiments were performed to screen a large range of upstream conditions. From these, five random experiments were picked to be considered in combination with the downstream process. The latter was simulated using ChromX, whereby four different gradient elution experiments were performed to calibrate the model and to determine the isotherm parameters. Following, both processes were optimized with respect to yield and purity. Results of the optimization could later also be validated successfully.

Superior process performance in up- and downstream. The combined characterization procedure has shown to be an effective tool for integrated process characterization. The final result can be shown as a pareto front that outlines the global set of optimal system points. The optimal operation point can then be chosen based on the demand of quality of the product.

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