Development of bioreactor scale‐down model using orthogonal projections to latent structures method and CO2 supplementation

Abstract

AbstractScale‐down model qualification is an important step for developing a large‐scale cell culture process to enhance process understanding and support process characterization studies. Traditionally, only harvest data are used to show consistency between small‐scale and large‐scale bioreactor performance, allowing attributes that are dynamic over the cell culture period to be overlooked. A novel statistical method, orthogonal projections to latent structures (OPLS) analysis, can be utilized to compare time‐course cell culture data across scales. Here we describe an example where OPLS is used to identify gaps between small‐scale and large‐scale bioreactor performances. In this case, differences in the partial pressure of carbon dioxide (pCO2) and lactate profiles were observed between small‐ and large‐scale bioreactors, which were linked to differences in the product‐quality attributes fragments and galactosylation. An improved small‐scale model was developed, leading to improved consistency in the process performance and product qualities across scales and qualification of the scale‐down model for regulatory submissions. This new statistical approach can provide valuable insights into process understanding and process scale‐up.