Model-based monitoring of industrial reversed phase chromatography to predict insulin variants.

Downstream processing in the manufacturing biopharmaceutical industry is a multistep process separating the desired product from process- and product-related impurities. However, removing product-related impurities, such as product variants, without compromising the product yield or prolonging the process time due to extensive quality control analytics, remains a major challenge. Here, we show how mechanistic model-based monitoring, based on analytical quality control data, can predict product variants by modeling their chromatographic separation during product polishing with reversed phase chromatography.

Designing an Autonomous Integrated Downstream Sequence From a Batch Separation Process - An Industrial Case Study.

This work is a proof of concept of how a sequence of industrial batch separation steps together are used to form an integrated autonomous downstream process. The sequence in this case study consisted of an anion chromatography step, virus inactivation and finally a hydrophobic chromatography step. Moving from batch to integrated separation minimizes hold-up times, storage tanks, and required equipment.

Design and control of integrated chromatography column sequences.

To increase the productivity in biopharmaceutical production, a natural step is to introduce integrated continuous biomanufacturing which leads to fewer buffer and storage tanks, smaller sizes of integrated unit operations, and full automation of the operation. The main contribution of this work is to illustrate a methodology for design and control of a downstream process based on integrated column sequences. For small scale production, for example, pre-clinical studies, integrated column sequences can be implemented on a single chromatography system.

Discretized multi-level elution trajectory: A proof-of-concept demonstration.

Biomolecular and pharmaceutical downstream processing is dominated by chromatographic separation, which is associated with high product quality, low capacity and high costs. The separation can be optimized to minimize the costs while achieving a high purity. This paper presents an experimental validation of a discretized multi-level elution (DiME) trajectory, implemented on commercially available chromatography equipment.

Prediction of reversible IgG1 aggregation occurring in a size exclusion chromatography column is enabled through a model based approach.

One important aspect of antibody separation being studied today is aggregation, as this not only leads to a loss in yield, but aggregates can also be hazardous if injected into the body. The aim of this study was to determine whether the methodology applied in the previous study could be used to predict the aggregation of a different batch of IgG1, and to model the aggregation occurring in a SEC column. Aggregation was found to be reversible.