Statistical analysis of factors affecting monoclonal antibody production by using principal component analysis : molecular markers - Gan, Zun Jia (2018)
The increasing demand for the monoclonal antibodies creates an urge for the biopharmaceutical industry to select high producing cell lines for maximum product concentration in order to cope with the market demand. The development of such cell line is a lengthy and challenging process. However, cell line with high productivity can be predicted by determining the early markers which will significantly minimize the time required to develop new cell line. This study focuses on the molecular markers in the antibody secretion pathway of a panel of six Chinese Hamster Ovary (CHO) stable cell lines which producing recombinant monoclonal antibodies at different rates, ranging between 2 and 50 pg/cell/day. The correlation between the selected molecular parameters and specific productivity (qp) of the cell lines throughout the exponential phase of batch cultures was studied by analyzing the results statistically using Principal Component Analysis (PCA) in STATISTICA 10. The data was arranged and analyzed according to the cell lines and the days in growth phase of the batch cultures. This study revealed that cell line 47 and cell line 76 had greater influences on the specific productivity than the other cell lines and intracellular heavy chain (HC) showed the strongest positive correlation with the specific productivity of the cell line. Higher intracellular HC is associated with higher specific productivity. More researches on the optimization of the molecular markers especially intracellular HC shall be done to further reveal its correlation with specific productivity.