Robust factor selection in early cell culture process development for the production of a biosimilar monoclonal antibody

Abstract

This work presents a multivariate methodology combining principal component analysis, the Mahalanobis distance and decision trees for the selection of process factors and their levels in early process development of generic molecules. It is applied to a high throughput study testing more than 200 conditions for the production of a biosimilar monoclonal antibody at microliter scale. The methodology provides the most important selection criteria for the process design in order to improve product quality towards the quality attributes of the originator molecule. Robustness of the selections is ensured by cross-validation of each analysis step. The concluded selections are then successfully validated with an external data set. Finally, the results are compared to those obtained with a widely used software revealing similarities and clear advantages of the presented methodology. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:181-191, 2017.

Tailoring recombinant protein quality by rational media design

“…Then the multivariate analysis to select the process settings yielding a product quality as close as possible to targeted molecule was carried out according to Sokolov et al 269 in three characteristic steps. First, a PCA was performed on thirteen glycoforms (Y variables) and the number of relevant principal components (PCs) was quantified visually from the scree plot [271][272][273] .…”

“…Good alignment of the glycan profiles between 96-DWP and shake tubes has been shown, and in the same study trends observed in high-throughput systems have been confirmed in lab-scale bioreactors 28 . In addition, by calling on rational experimental design strategies and the use of statistical tools, many quality attributes can be assessed simultaneously in media optimization 269 . This significantly improves the efficiency in process development by enabling to derive relevant knowledge in early process screening and to drive the process development to larger scales in a focused manner, resulting in reduced experimental efforts.…”

Parallel experimental design and multivariate analysis provides efficient screening of cell culture media supplements to improve biosimilar product quality

“…The obtained results were visualized using box plots (McGill et al, ). Then the multivariate analysis to select the process settings yielding a product quality as close as possible to targeted molecule was carried out according to Sokolov et al () in three characteristic steps. First, a PCA was performed on 13 glycoforms (Y variables) and the number of relevant Principal Components (PCs) was quantified visually from the scree plot (Hou et al, ; Jolliffe, ; Thomassen et al, ).…”

“…Good alignment of the glycan profiles between 96‐DWP and shake tubes has been shown, and in the same study trends observed in high‐throughput systems have been confirmed in bioreactors (Rouiller et al, ). In addition, by calling on rational experimental design strategies and the use of statistical tools, many quality attributes can be assessed simultaneously in media optimization (Sokolov et al, ). This significantly improves efficiency in process development by enabling to derive relevant knowledge in early screening and to drive the development to larger scales in a focused manner, resulting in reduced experimental efforts.…”

Sequential Multivariate Cell Culture Modeling at Multiple Scales Supports Systematic Shaping of a Monoclonal Antibody Toward a Quality Target

“…For this purpose, an extensive number of operating conditions have to be investigated. Automated high throughput experimental systems such as DWP and AMBR bioreactors have enabled the screening of tens to hundreds of process parameters simultaneously . Additionally, improvements in the process analytical technologies have been of great benefit for the efficiency and efficacy in bioprocess development.…”