Understanding protein phase behavior is important for purification, storage, and stable formulation of protein drugs in the biopharmaceutical industry. Glycoproteins, such as monoclonal antibodies (MAbs) are the most abundant biopharmaceuticals and probably the most difficult to crystallize among water-soluble proteins. This study explores the possibility of correlating osmotic second virial coefficient (B(22)) with the phase behavior of an intact MAb, which has so far proved impossible to crystallize. The phase diagram of the MAb is presented as a function of the concentration of different classes of precipitants, i.e., NaCl, (NH4)2SO4, and polyethylene glycol. All these precipitants show a similar behavior of decreasing solubility with increasing precipitant concentration. B(22) values were also measured as a function of the concentration of the different precipitants by self-interaction chromatography and correlated with the phase diagrams. Correlating phase diagrams with B(22) data provides useful information not only for a fundamental understanding of the phase behavior of MAbs, but also for understanding the reason why certain proteins are extremely difficult to crystallize. The scaling of the phase diagram in B(22) units also supports the existence of a universal phase diagram of a complex glycoprotein when it is recast in a protein interaction parameter.

This paper summarizes the main findings of a round-table discussion held to examine the key bottlenecks in the further application and industrial implementation of in-situ product removal (ISPR) techniques. It is well established that ISPR can yield great benefits for processes limited by inhibitory or toxic products, as well as unstable products or reactions that are thermodynamically unfavorable. However, several issues for industrial implementation were revealed in the discussion. Most notably implementation will be dependent on (1) research into the appropriate process structure, (2) methods to achieve process robustness, (3) systematic selection methods for separation operations and (4) the nature of the product market. Here, these four issues will be discussed as a basis for future work in this area.

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The swelling kinetics of two types of Sephadex dextran gels in water is described by a model based on the generalized Maxwell-Stefan (GMS) relations. The driving force for the swelling process is the gradient of the chemical potential gradient, which includes terms for mixing of solvent and polymer as well as for the elasticity of the swollen gel network. The friction is related to the relative motion of the components, via an effective diffusion coefficient. This is described as a function of the volume fraction of polymer via the Ogston relation (diffusion based) and a hydrodynamic model (based on the analogy with viscous flow). The resulting swelling model is evaluated via rigorous solution of the equations (homogeneous driving force approach, HDF), in which intraparticle gradients are taken into account, and approximated by a singlestep central difference method (linear driving force approach, LDF). The latter allows much faster evaluation of the swelling process. These two numerical solution methods give similar results for the simulation of the expanding outer radius of the gel particles, regardless of which expression is used for the effective diffusivity. When intraparticle dynamics are considered (HDF solution method), some differences between the two effective diffusivity relations arise. The hydrodynamic model predicts steeper composition gradients than the Ogston model and leads to a distinctly later dissolution of the shrinking core. However, there is a lack of reliable dynamic intraparticle profile data to verify either model.

The advantages of continuous chromatography with respect to increased capacity are well established. However, the impact of different loading scenarios and total number of columns on the process economics has not been addressed. Here four different continuous multicolumn chromatography (MCC) loading scenarios are evaluated for process performance and economics in the context of a Protein A mAb capture step. To do so, a computational chromatography model is validated experimentally. The model is then used to predict process performance for each of the loading methods. A wide range of feed concentrations and residence times are considered, and the responses of operating binding capacity, specific productivity, and the number of process columns are calculated. Processes that are able to add more columns proved to be up to 65% more productive, especially at feed concentrations above 5 g L−1. An investigation of the operating costs shows that discrete column sizing and process performance metrics do not always correlate and that the most productive process is not necessarily the most cost effective. However, adding more columns for the non‐load steps at higher feed concentrations allows for overall cost savings of up to 32%.