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.

Prediction of IgG1 aggregation in solution.

Interest in monoclonal antibody aggregation is increasing as aggregates of biopharmaceuticals can cause an immunogenic response when injected into the body. In this work, a stoichiometric reaction model from concentration-time data is developed to predict the dimer ratio in stored antibody solutions over time. IgG1 was incubated at pH from 4.

Modelling and optimisation of preparative chromatographic purification of europium.

A model commonly used to describe the separation of biomolecules was used to simulate the harsh environment when eluting neodymium, samarium, europium and gadolinium with a hot acid. After calibration, the model was used to optimise the preparative separation of europium, as this is the most valuable of the four elements. A kinetic dispersive model with a Langmuir mobile phase modulator isotherm was used to describe the process.

Optimization of preparative chromatographic separation of multiple rare earth elements.

This work presents a method to optimize multi-product chromatographic systems with multiple objective functions. The system studied is a neodymium, samarium, europium, gadolinium mixture separated in an ion exchange chromatography step. A homogeneous Langmuir Mobile Phase Modified model is calibrated to fit the experiments, and then used to perform the optimization task.