Conference Dates

November 1-5, 2015

Abstract

Multicolumn chromatography (MCC) is a proven technique to significantly improve performance of bio-processes by increasing specific productivity, reducing volume of resin used and enabling disposable, continuous and integrated processes. But the transfer of process parameters from batch to continuous mode is perceived as complex and could limit adoption at clinical and manufacturing scales.

We have developed and tested a new method to translate data from a minimal number of single column runs into a multicolumn process with predictable performance at large scale. Depending on the titre of the product and the processing time required, the method predicts the optimal number and size of pre-packed columns and the best sequence of column operation. The process economics is determined from all of the input factors (eg titre, process time) and output factors (eg process productivity, g/L/hr) by linking with a process cost analysis software.

The accuracy of the method was challenged for affinity (Protein A) and non-affinity (CEX) applications using both real feedstock (CHO clarified supernatant) and model proteins. The method developed allows accurately predicting the productivity and capturing efficiency of MCC processes. The process economics study shows significant cost savings are achieved during process development. The method also allows an increased appreciation of the process requirements for MCC operation. Therefore, manufacturing process cost can be evaluated through a customized optimisation of process parameters.

This new concept radically simplifies process transfer from batch to continuous operation, accelerates process development and enables a complete optimization of process parameters to fit business needs

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