Analysis of Transformed Upstream Bioprocess Data Provides Insights into Biological System Variation

Abstract

In recent years, multivariate data analysis (MVDA) and modeling approaches have found increasing applications for upstream bioprocess studies (e.g., monitoring, development, optimization, scale-up, etc.). Many of these studies look at variations in the concentrations of metabolites and cell-based measurements. However, these measures are subject to system inherent variations (e.g., changes in metabolic activity) but also intentional operational changes. It is proposed to perform MVDA and modeling on data representative of the underlying biological system operation, that is, the specific rates, which are per se independent of the scale, operational strategy (e.g., batch, fed-batch), and biomass content. Two industrial case studies are highlighted to showcase the approach: one is HEK medium performance comparison study and the other is CHO scale-up/-down study. It is shown that analyzing processes in this way reveals insights into behavior of the underlying biological system, which cannot to the same degree be deducted from the analysis of concentrations.

Keywords: cell cultivation; development; monitoring; multivariate data analysis; optimization; scale-down; scale-up.