Wilson, Aaron, Moutsatsos, Ioannis, Yu, Gary, Pineda, Javier, Feng, Yan and Auld, Douglas (2018) A Scalable Pipeline for High-Throughput Flow Cytometry. SLAS DISCOVERY: Advancing Life Sciences R&D. ISSN 2472-55522472-5560

Abstract

Flow cytometry (FC) provides high-content data for a variety of applications, including phenotypic analysis of cell surface
and intracellular markers, characterization of cell supernatant or lysates, and gene expression analysis. Historically,
sample preparation, acquisition, and analysis have presented as a bottleneck for running such types of assays at scale. This
article will outline the solutions that have been implemented at Novartis which have allowed high-throughput FC to be
successfully conducted and analyzed for a variety of cell-based assays. While these experiments were generally conducted to
measure phenotypic responses from a well-characterized and information-rich small molecular probe library known as the
Mechanism-of-Action (MoA) Box, they are broadly applicable to any type of test sample. The article focuses on application
of automated methods for FC sample preparation in 384-well assay plates. It also highlights a pipeline for analyzing large
volumes of FC data, covering a visualization approach that facilitates review of screen-level data by dynamically embedding
FlowJo (FJ) workspace images for each sample into a Spotfire file, directly linking them to the metric being observed. Finally,
an application of these methods to a screen for MHC-I expression upregulators is discussed.

Item Type:	Article
Date Deposited:	13 Jun 2018 00:45
Last Modified:	13 Jun 2018 00:45
URI:	https://oak.novartis.com/id/eprint/34556