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. 2018 Aug;23(7):697-707.
doi: 10.1177/2472555218773086. Epub 2018 May 29.

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery

Affiliations

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery

John Joslin et al. SLAS Discov. 2018 Aug.

Abstract

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Keywords: drug discovery; high-throughput flow cytometry; high-throughput screening; phenotypic screening.

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Conflict of interest statement

Declaration of Conflicting Interests: The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: All authors were employed by Genomics Institute of the Novartis Research Foundation at the time of contribution, and their research and authorship of this article was completed within the scope of their employment with Genomics Institute of the Novartis Research Foundation.

Figures

Figure 1.
Figure 1.
GNF High-throughput flow cytometry screening system. (A) Computer-aided design (CAD) of the screening system. (B) GNF Systems WDII. (C) GNF Systems automated flow cytometry sampler.
Figure 2.
Figure 2.
Informatics. The current data processing pipeline, where each of the individual assay plates is processed by the aforementioned hardware system, resulting in a single .fcs file per plate. The files are split by Segmenter into individual wells and then analyzed by Dispatcher wrapper software through a predefined FlowJo template. The final step of data visualization is accomplished by loading the .csv file and associated .png files in Spotfire.
Figure 3.
Figure 3.
Hybridoma supernatant screening example. (A) In this example, four cell lines were fluorescently barcoded. The individual cell lines were deconvoluted using FlowJo with the gating strategy shown. (B) Antibody binding to each of the individual cell lines was compared by calculating the MFI of BV421 (not shown) and by a histogram comparison of the four cell lines. In this example, the antibody from this clone was human and cyno specific. (C) As an additional example, we designed a multiplexed bead-based assay for determining antibody specificity. This shows five bead populations, each with a unique antigen covalently conjugated to the individual population. (D) Antibody binding was determined by calculating the MFI of BV421 (not shown) and by a histogram comparison of the five bead populations. In this example, the antibody from this clone bound the bead conjugated with full-length human antigen and full-length cyno antigen.
Figure 4.
Figure 4.
Treg agonist assay example. (A) Dose–response comparison of an agonist hit and an antagonist hit relative to the positive control, rapamycin. Data are normalized to the plate median. (B) FlowJo plots of the top concentration (10 µM) for each of the individual hits (x and y axis on log scale).
Figure 5.
Figure 5.
Platelet assay. (A) Platelets are defined as FSClowSSClowCD41+CD42+ using the gating strategy as shown (x and y axis on log scale). (B) The GSK-3 inhibitor CHIR9902127 was included as the assay positive control.
Figure 6.
Figure 6.
NK cell modulators. (A) Representative FACS plots showing a gating scheme for the determination of K562 cytotoxicity. K562 cells are differentiated from NK cells by CellTracer Violet dye. Cytotoxicity is calculated by a shift of K562 FSC/SSC profiles. K562 culture alone shows minimal cell death, while K562 cells co-cultured with IL-2-stimulated NK cells show greatly enhanced cytotoxicity. Violet is on a log scale, and FSC/SSC is on a linear scale. (B) 12-point threefold dose response of a primary hit inhibitor, showing the effect of the NF-κB pathway antagonist. (C) 12-point threefold dose response of a primary hit enhancer, showing the effect of the NF-κB pathway agonist on NK cell function.

References

    1. Haasen D., Schopfer U., Antczak C., et al. How Phenotypic Screening Influenced Drug Discovery: Lessons from Five Years of Practice. Assay Drug Dev. Technol. 2017, 15 (6), 239–246. - PubMed
    1. Horvath P., Aulner N., Bickle M., et al. Screening out Irrelevant Cell-Based Models of Disease. Nature Rev. Drug Discov. 2016, 15 (11), 751–769. - PubMed
    1. Robinson J. P., Durack G., Kelley S. An Innovation in Flow Cytometry Data Collection and Analysis Producing a Correlated Multiple Sample Analysis in a Single File. Cytometry 1991, 12 (1), 82–90. - PubMed
    1. Kuckuck F. W., Edwards B. S., Sklar L. A. High Throughput Flow Cytometry. Cytometry 2001, 44 (1), 83–90. - PubMed
    1. Edwards B. S., Young S. M., Saunders M. J., et al. High-Throughput Flow Cytometry for Drug Discovery. Expert Opin. Drug Discov. 2007, 2 (5), 685–696. - PubMed

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