Optimal Integration of Directly Combined Hydrophobic Interaction and Ion Exchange Chromatography Purification Processes

Abstract

Hydrophobic interaction and ion exchange chromatography are basic steps in purification of fermentative biopharmaceuticals. An optimization by statistical design of experiments requires a huge amount of feed. An alternative approach is the combination of model parameter determination using small scale experimental model parameter determination (1‐mL columns) and rigorous process modeling. Applicability for the prediction of the separation of a fermentation mixture of CHO mammalian cell culture is validated and hence IgG is purified from cell culture supernatant. Hydrophobic interaction chromatography directly combined with ion exchange chromatography is optimized. Any direct integration of those two main unit operations in purification processes is a methodological first step towards total process optimization. The potential for cost reduction and overall yield improvement is demonstrated and this leads to the conclusion that single step optimization is a feigned and not a real optimum.

Calibration‐free inverse modeling of ion‐exchange chromatography in industrial antibody purification

“…This approach ensures fast process development and reduces the time to market, but it is probable that the reduced exploration of design space leads to suboptimal processes . Process understanding is hence a sensible and important addition to the use of platform processes . As the integration of modeling tools into process development is also an essential part of the strategy for the implementation of the quality by design approach , modeling tools are increasingly gaining the attention of the pharmaceutical industry.…”

Integration of Aqueous Two‐Phase Extraction into Downstream Processing

“…Ion‐exchange chromatography is commonly applied for purification and polishing of mAbs 1, 3, 24–27. Therefore, it is used in the given process as an example of a unit operation following ATPE.…”

“…A validated model allows reducing the experimental effort and optimization of process performance by varying process parameters. Since modeling of ultrafiltration 15, 16 and ion‐exchange chromatography 17–19 for the purification of biomolecules is reported in previous works, this paper will provide ATPE modeling studies and comparison with experimental data for a miniplant extraction column. Using an equilibrium stage model, the performance of a multistage extraction will be predicted.…”

Optimization of biopharmaceutical downstream processes supported by mechanistic models and artificial neural networks

“…Nfor et al optimized the sequence of chromatographic unit operations sequentially rather than simultaneously, which reduces the complexity of the combinatorial problem as possible unit operation sequences increase drastically with an increasing number of unit operations (Nfor et al, ). Nevertheless, sequential optimization may lead to a suboptimal overall process . Moreover, several process options were excluded which seemed to be not competitive based on prior knowledge about the process .…”