Integration of a fully automated flow cytometry system with high robustness into a Screening Station

Abstract

In recent years, there has been an increasing demand for the detection of rare cells in drug discovery research, such as cells that have differentiated off-purpose or are required for immunogenicity evaluation. Since detection and quantification limits depend on the robustness of the experiment, inter-human differences in technique have a significant impact on the performance of the assay system. Here, we integrated flow cytometry into a cell experiment platform, Screening Station, to construct a robust assay system, examined each step of the flow cytometric pretreatment using Jurkat cells, and finally evaluated the overall assay performance. Cell detection rate when the experiment was performed manually was 48.8 % ± 5.7 % (CV=11.6 %) versus 73.7 %±2.0 % (CV=2.8 %) with the automated method. To further clarify the analytical performance of the automated method, 1-100 PD-1 expressing Jurkat cells were spiked with 1 × 10⁵ Jurkat cells, and the lower limit of detection, linearity, and CV% were evaluated. Average detection rate was 69 %, decision count was 0.985, and lower limit of detection was 4 cells (0.004 %). We evaluated the CV% value of the number of detected cells per spiked cell and found our system to be highly robust, approximating a binomial distribution with a 69 % recovery rate. In conclusion, we have integrated the Novocyte flow cytometry system into an automated experimental platform, Screening Station, to create a fully automated flow cytometric assay system with high robustness. Our platform can fulfill the technology needs of drug discovery for rare cell detection, which have intensified in recent years.

Keywords: Automated system; Flow cytometry; Laboratory automation; Rare cell detection; Robust assay.