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Related Concept Videos

Flow Cytometry01:23

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The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Flow Table Test01:12

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The flow table test is an established method used to assess the workability of concrete, particularly useful for evaluating highly flowable concrete mixes. This test employs an apparatus that consists of a wooden board topped with a steel plate, collectively weighing 35 pounds. The board is connected to a base via a hinge and measures 27.6 inches on each side.
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Updated: Feb 10, 2026

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
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A Scalable Pipeline for High-Throughput Flow Cytometry.

Aaron C Wilson1, Ioannis K Moutsatsos1, Gary Yu1

  • 11 Novartis Institutes of Biomedical Research, Cambridge, MA, USA.

SLAS Discovery : Advancing Life Sciences R & D
|May 18, 2018
PubMed
Summary
This summary is machine-generated.

High-throughput flow cytometry (FC) enables scalable cell-based assays. Automated sample preparation and data analysis pipelines streamline high-content data review for drug discovery.

Keywords:
flow cytometryhigh throughputphenotypic assay

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Area of Science:

  • Biotechnology
  • Cell Biology
  • Immunology

Background:

  • Flow cytometry (FC) generates high-content data for cell analysis but faces bottlenecks in sample preparation, acquisition, and analysis.
  • Scaling FC assays for large-scale screening requires efficient and automated workflows.

Purpose of the Study:

  • To outline solutions implemented at Novartis for high-throughput flow cytometry (FC) and large-scale data analysis.
  • To demonstrate the applicability of these methods to various cell-based assays and test samples.

Main Methods:

  • Automated sample preparation for FC in 384-well assay plates.
  • Development of a data analysis pipeline for large volumes of FC data.
  • Implementation of a visualization approach embedding FlowJo (FJ) workspace images into Spotfire files for dynamic data review.

Main Results:

  • Successful implementation of automated methods for high-throughput FC sample preparation.
  • Establishment of an efficient pipeline for analyzing large-scale FC data.
  • Demonstrated utility in a screen for MHC-I expression upregulators.

Conclusions:

  • Automated sample preparation and data analysis pipelines overcome bottlenecks in high-throughput flow cytometry.
  • These methods facilitate efficient and scalable analysis of high-content cell-based assay data.
  • The described approach is broadly applicable to diverse cell-based screening applications.