High‐throughput screening of antibody‐expressing CHO clones using an automated shaken deep‐well system. (14th October 2018) - Wang, Benjamin; Albanetti, Thomas; Miro‐Quesada, Guillermo; Flack, Layla; Li, Lina; Klover, Judith; Burson, Kerri; Evans, Krista; Ivory, William; Bowen, Michael; Schoner, Ronald; Hawley‐Nelson, Pamela
Abstract : Biopharmaceutical protein manufacturing requires the highest producing cell lines to satisfy current multiple grams per liter requirements. Screening more clones increases the probability of identifying the high producers within the pool of available transfectant candidate cell lines. For the predominant industry mammalian host cell line, Chinese hamster ovary (CHO), traditional static‐batch culture screening does not correlate with the suspension fed‐batch culture used in manufacturing, and thus has little predictive utility. Small scale fed‐batch screens in suspension culture correlate better with bioreactor processes but a limited number of clones can be screened manually. Scaled‐down systems, such as shaken deep well plates, combined with automated liquid handling, offer a way for a limited number of scientists to screen many clones. A statistical analysis determined that 384 is the optimal number of clones to screen, with a 99% probability that six clones in the 95th percentile for productivity are included in the screen. To screen 384 clones efficiently by the predictive method of suspension fed‐batch, the authors developed a shaken deep‐well plate culturing platform, with an automated liquid handling system integrating cell counting and protein titering instruments. Critical factors allowing deep‐well suspension culture to correlate with shake flask culture were agitation speed and culture volume. Using our automated system, one scientist can screen five times more clones than by manual fed‐batch shake‐flask or shaken culture tube screens and can identify cell lines for some therapeutic protein projects with production levels greater than 6 g/L. © 2018 American Institute of Chemical Engineers Biotechnol. Prog ., 34:1460–1471, 2018