Abstract
The development and validation of a chromatography rate model for an industrial multicomponent chromatographic bioseparation is presented. The model is intended for use in a process scenario to allow specific variables critical to product quality to be studied. The chromatography provides impurity clearance whilst producing a complex product composed of six closely related variants of a dimer protein therapeutic (∼30kDa), with their monomer subunits in a specific ratio. Impurity removal is well understood, however, achieving the correct monomer subunit ratio can pose a purification challenge. We utilise a stepwise approach to develop a model for studying the effect of feed material variability on product quality. Scale down experiments are completed to quickly generate data for estimating model parameters, before an iterative procedure is employed where the industrial process is used to refine parameters in a sequential manner, until model predictions exhibit satisfactory agreement with experimental data. Final model predictions were in good agreement with experimental product quality (within 3%). The results demonstrate how good understanding of an industrial process can help facilitate model development when an exhaustive description is not required, despite considering a chromatographic bioseparation with crude feed material and challenging purification objectives.
Highlights
Advances in healthcare over the past half century have been of immense benefit to the quality of life for an increasing world population
Problem description The hydrophobic interaction chromatography (HIC) considered in this work is a complex separation with challenging purification objectives
The product form distribution in the elution peak, and in samples taken from the column outlet every column volume (CV) during the load and the wash, was measured during experimental small-scale column runs using cation exchange (CEX) high performance liquid chromatography (HPLC)
Summary
Advances in healthcare over the past half century have been of immense benefit to the quality of life for an increasing world population. The complexity of the industrial feed material in these studies means that the model development procedures involve conducting an extensive range of detailed experiments which may not be suitable in certain scenarios. One such scenario in industry is where the majority of process development has already taken place, but there remains a desire to develop understanding of a key feature of a bioseparation. A chromatography model for predicting product quality in an industrial multicomponent bioseparation is developed and validated. We demonstrate how good understanding of an industrial process can facilitate model development, despite considering a chromatographic bioseparation with crude feed material and challenging purification objectives
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