RESUMEN
Scale-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.
