Rethinking clonality using modeling approaches
May 6-11, 2018
A combination of experimental procedures, imaging, and probability estimation are typically used as evidence of clonality for the manufacture of a biotherapeutic product. In situations where the totality of evidence is unavailable, establishing a high statistical probability for monoclonality can help strengthen the argument for clonality. In this study, the probability of clonality was re-examined for the limiting dilution method using a combination of experimental and modeling approaches. A limiting dilution experiment was performed using a 50:50 mixed population of GFP-and RFP-expressing cells and the plates were imaged over a span of two weeks. The imaged cells were scored for clonality and double checked with fluorescence imager. Among all wells that had single colony-like growth on day 14 and a single cell-like image on day 0, a fraction of the wells were confirmed to have two colors on day 14 by fluorescence imaging, indicating the singe cell-like day 0 images for these wells were false reads. Considering the possibility of having 2 or more cells with the same color in a particular well, we estimated the worst case total possible number of wells with 2 or more cells on day 0. Moreover, assuming a Poisson distribution for limiting dilution, the recovery rate of any single cell that grew into a visible colony by day 14 was estimated. Our modeling analysis indicated that only a fraction of the wells with >2 cells on day 0 could grow into non-monoclonal colonies. If cells from any of the wells with single colony-like growth on day 14 and single cell-like image on day 0 were chosen as the final clone, the probability of monoclonality was estimated to be > 95% with a 95% upper confidence limit.
Chun Chen, Nicole Tejeda, Kim Le, Trent Munro, Jennitte Stevens, Chetan Goudar, and Tharmala Tharmalingam, "Rethinking clonality using modeling approaches" in "Cell Culture Engineering XVI", A. Robinson, PhD, Tulane University R. Venkat, PhD, MedImmune E. Schaefer, ScD, J&J Janssen Eds, ECI Symposium Series, (2018). https://dc.engconfintl.org/ccexvi/194