No abstract

UV absorbance measurements play an important role in bioprocess development. Yield and purity are often evaluated in terms of peak percentages in analytical SEC or ion-exchange chromatography. Also, industrial chromatography steps are usually controlled based on UV data with pooling decisions according to absorbance thresholds. Model-based process development would make elaborate screening experiments redundant, once the model has been calibrated to the specific process step. So far, absorbance measurements could not be used directly for modeling chromatography steps as the commonly applied models rely on mass or molar concentration. This study presents mechanistic modeling of an industrially relevant chromatography setting without any knowledge of the feed composition. The model equations were rewritten to employ boundary conditions in UV absorbance units, the absorption coefficients were shifted into the isotherm, and standard parameter estimation procedures could be applied. An anion-exchange chromatography case study of a target protein expressed in Escherichia coli and 11 lumped impurity peaks demonstrated practical applicability. The target protein concentration in the feed material was estimated from chromatograms. Using this method, initially unknown feed concentrations can be determined a posteriori for ion-exchange and multimodal chromatography from single-component absorbance curves.

The identification of optimal process parameters for the isolation of a target component from multicomponent mixtures is especially challenging in industrial applications. With constantly increasing time-to-market pressure, screening a large parameter space is not feasible and design-of-experiment approaches with few experiments might fail due to dynamic and nonlinear reactions to small parameter changes. Model-based optimization can determine optimal operating conditions, once the model has been calibrated to the specific process step. In this work, parameters for the steric mass action model were estimated for the target protein and three impurities of an industrial antibody cation-exchange purification step using only chromatograms at different wavelengths and additional fraction analyses with size exclusion chromatography. Information on the molar or mass concentrations in the feed are not available. The model-based optimization results coincide with conventional chromatogram-based optimization.

Industrial purification of biomolecules is commonly based on a sequence of chromatographic processes, which are adapted slightly to new target components, as the time to market is crucial. To improve time and material efficiency, modeling is increasingly used to determine optimal operating conditions, thus providing new challenges for current and future bioengineers. At the Karlsruhe Institute of Technology (KIT), mechanistic modeling of protein chromatography has long been part of the curriculum of the Bioengineering master's degree program, supported by exercises using simulation software. Emphasis lies on nonlinear preparative chromatography, where the result strongly depends on the sample concentration. For undergraduate students to gain hands-on experience in model-based optimization, a three-week, in-depth laboratory course was designed on the purification of a ternary mixture of proteins using ion-exchange chromatography and mechanistic modeling. Students apply in-house software ChromX, which is made available for download, together with tutorials on numerics and practical applications. This article presents the working principle of ChromX and results of the laboratory course for undergraduate students.

A main requirement for the implementation of model-based process development in industry is the capability of the model to predict high protein load densities. The frequently used steric mass action isotherm assumes a thermodynamically ideal system and, hence constant activity coefficients. In this manuscript, an industrial antibody purification problem under high load conditions is considered where this assumption does not hold. The high protein load densities, as commonly applied in industrial downstream processing, may lead to complex elution peak shapes. Using Mollerup's generalized ion-exchange isotherm (GIEX), the observed elution peak shapes could be modeled. To this end, the GIEX isotherm introduced two additional parameters to approximate the asymmetric activity coefficient. The effects of these two parameters on the curvature of the adsorption isotherm and the resulting chromatogram are investigated. It could be shown that they can be determined by inverse peak fitting and conform with the mechanistic demands of model-based process development.