Dynamic modelling of aqueous two-phase systems to quantify the impact of bioprocess design, operation and variability

Exploring all potential sources of variability is challenging due to resource and time constraints, however, the use of targeted mathematical modelling can significantly reduce the need for expensive and time consuming experimentation. In this work, we present a dynamic equilibrium stage process model, and a methodology for prediction of key process parameters from limited experiments, capable of describing ATPE separations under both multi-cycle batch and continuous counter-current modes of operation. The capabilities of the proposed methodology are demonstrated using a case study separation of the enzyme α-amylase from impurities in a PEG 4000-phosphate aqueous two phase system (ATPS) containing NaCl. The model can be used to predict the separation performance of the process, as well as for the investigation of suitable design and operating conditions.