Scale-up of affinity chromatography for purification of enzymes and other proteins

On the apparent dispersion coefficient of the equilibrium dispersion model: An asymptotic analysis

To model chromatography, researchers have developed several approaches. These cover a broad range of applications and, depending on the assumptions adopted, have different levels of accuracy. In general, the most suitable modelling approach is the simplest that can describe a process with the desired accuracy. A model that often meets this criterion is the equilibrium dispersion model (EDM). This features one mass balance equation per analyte, including an axial dispersion term, and assumes the analyte concentrations in the mobile and stationary phases to be in local equilibrium. To account for the finite mass transfer rate between the phases, the model employs an apparent dispersion coefficient. Two expressions are available for this coefficient, one being used much more frequently than the other. In this paper, we aimed to clarify which one should be favoured. A desirable feature of simple models is that they can be derived from more general ones with appropriate physical assumptions and rigorous mathematical methods. Thus, to answer our research question, we derived the EDM from the more general pore diffusion model (POR), using an asymptotic method. The expression obtained for the apparent dispersion coefficient does agree with one of the two reported in the literature - the less frequently used. To test the validity of this expression, we simulated elution profiles using the two versions of the EDM and compared the results against those from the POR model. The simulations were conducted in the range where the POR and EDM models should be essentially equivalent, their results confirming the outcome of the asymptotic analysis. This work offers a solid theoretical grounding for the EDM, clarifies which formulation of the model is correct, and provides usable applicability conditions for the model.

Mechanistic modeling of cation exchange chromatography scale-up considering packing inhomogeneities

In process development and characterization, the scale-up of chromatographic steps is a crucial part and brings a number of challenges. Usually, scale-down models are used to represent the process step, and constant column properties are assumed. The scaling is then typically based on the concept of linear scale-up. In this work, a mechanistic model describing an anti-Langmuirian to Langmuirian elution behavior of a polypeptide, calibrated with a pre-packed 1 ml column, is applied to demonstrate the scalability to larger column volumes up to 28.2 ml. Using individual column parameters for each column size, scaling to similar eluting salt concentrations, peak heights, and shapes is experimentally demonstrated by considering the model's relationship between the normalized gradient slope and the eluting salt concentration. Further scale-up simulations show improved model predictions when radial inhomogeneities in packing quality are considered.

A new approach for affinity-based purification of horseradish peroxidase

We have developed efficient procedure for isolation of horseradish peroxidase (HRP) using aminobenzohydrazide-based affinity chromatography. Sepharose 4B-bounded aminobenzohydrazides are suitable for long-term use and large-scale purification. In this study, 26 aminobenzohydrazide derivatives were synthesized, characterized and defined as new HRP inhibitors. In addition, detailed inhibition effects of these molecules on HRP enzyme were investigated. Affinity matrix was formed by bonding aminobenzohydrazides, which exhibited inhibitory activity to sepharose-4B-l-tyrosine. HRP was isolated from crude homogenate in single step and purification factors were recorded as 1,151-fold (recovery of 8.5%) with 4-amino 3-bromo benzohydrazide and as 166.16-fold (recovery of 16.67 %) with 3-amino 4-chloro benzohydrazide.

Modelling approaches for bio-manufacturing operations

Fast and cost-effective methods are needed to reduce the time and money needed for drug commercialisation and to determine the risks involved in adopting specific manufacturing strategies. Simulations offer one such approach for exploring design spaces before significant process development is carried out and can be used from the very earliest development stages through to scale-up and optimisation of operating conditions and resource deployment patterns both before and after plant start-up. The advantages this brings in terms of financial savings can be considerable, but to achieve these requires a full appreciation of the complexities of processes and how best to represent them mathematically within the context of in silico software. This chapter provides a summary of some of the work that has been carried out in the areas of mathematical modelling and discrete event simulations for production, recovery and purification operations when designing bio-pharmaceutical processes, looking at both financial and technical modelling.