A comprehensive assessment of the applicability of RoboColumn as a chromatography scale-down model for use in biopharmaceutical process validation.

High-throughput process development has become a standard practice in the biopharmaceutical industry to enable time, cost, and material savings. In downstream biopharmaceutical process development, miniaturized, parallelized chromatography columns, known as RoboColumn, have become the standard for process development, as RoboColumn have shown generally comparable performance to bench and manufacturing scale columns. However, RoboColumn have yet to be widely implemented in process validation and characterization, where many multifactor experiments are typically executed, and there is a strong value proposition for performing high-throughput experiments.

Prediction uncertainty assessment of chromatography models using Bayesian inference.

Mechanistic modeling of chromatography has been around in academia for decades and has gained increased support in pharmaceutical companies in recent years. Despite the large number of published successful applications, process development in the pharmaceutical industry today still does not fully benefit from a systematic mechanistic model-based approach. The hesitation on the part of industry to systematically apply mechanistic models can often be attributed to the absence of a general approach for determining if a model is qualified to support decision making in process development.

Modeling of complex antibody elution behavior under high protein load densities in ion exchange chromatography using an asymmetric activity coefficient.

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.