Discerning key parameters influencing high productivity and quality through recognition of patterns in process data

Background The adoption of Quality by Design (QbD) approach to biologics manufacturing requires fundamental understanding of complex relationship between the quality of the product, especially critical quality attributes (CQAs), and various parameters of the manufacturing process [1]. This can be approached through multivariate analysis of historical cell culture bioprocess data [2]. In this study, process parameters and raw materials data obtained from 51 runs with final titer varying from 0.8 to 2.0 units and Gal0 glycan ranging from 47.5 to 67.5% was investigated. The aim was to discover prominent patterns which may cause the spread of final process outcome.