Mixed integer optimisation of antibody purification processes

Chromatographic operations are identified as critical steps in a monoclonal antibody (mAb) purification process and can represent a significant proportion of the purification material costs. The optimisation of chromatography equipment sizing strategies is therefore crucial to improve the cost-effectiveness of mAb manufacture. In this work, a mixed-integer linear programming model (MILP) was developed to determine the optimal chromatography column sizing decisions, so as to minimise the cost of goods per gram (COG/g) of the whole mAb manufacturing process. Modelling challenges related with non-linearities involving the multiplication of decision variables were addressed by the use of linearisation techniques allowing the resulting model to determine global process performance metrics (e.g. chromatography processing time, COG/g). The application of the MILP model to an industrially-relevant case study combined with the use of visualisation methods proved to be a valuable tool to explore the characteristics of the optimal sizing strategies across different scenarios and to facilitate decision-making.