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Updated: Jun 22, 2026

Using High Content Imaging to Quantify Target Engagement in Adherent Cells
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Published on: November 29, 2018

Image analysis in high-content screening.

Antje Niederlein1, Felix Meyenhofer, Daniel White

  • 1High Throughput Technology Development Studio, Max Planck Institute for Molecular Cell Biology and Genetics, 108 Pfotenhauerstrasse, D-01307 Dresden, Germany.

Combinatorial Chemistry & High Throughput Screening
|June 18, 2009
PubMed
Summary
This summary is machine-generated.

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High Content Screening (HCS) generates vast data, posing challenges in data mining and storage. Automated image analysis offers solutions for this powerful, increasingly accessible technology.

Area of Science:

  • Biotechnology
  • Cell Biology
  • Drug Discovery

Background:

  • High Content Screening (HCS) has transitioned from pharmaceutical secondary screening to broader applications in academia for primary screening and basic research.
  • The increasing size and complexity of HCS experiments are driving significant advancements in automated image acquisition and analysis.

Purpose of the Study:

  • To review the evolution and current state of High Content Screening (HCS).
  • To identify major challenges in automated high-throughput image analysis within HCS.
  • To present available software solutions for data mining and storage in HCS.

Main Methods:

  • Review of technological advancements in automated image acquisition platforms.
  • Analysis of progress in automated image analysis for biological problems.

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Last Updated: Jun 22, 2026

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  • Survey of current software solutions (commercial and open-source) for HCS data management.

    • Main Results:

    • HCS technology is now more powerful and accessible due to automation in image acquisition and analysis.
    • Data mining and data storage are critical challenges due to the large datasets generated by HCS.
    • Numerous image analysis solutions exist, with ongoing development to enhance data extraction quality and quantity.

    Conclusions:

    • Automated image analysis is crucial for addressing the data challenges in modern High Content Screening.
    • The accessibility of HCS is increasing for researchers beyond specialized pharmaceutical settings.
    • Continued development of software solutions is essential for maximizing the potential of HCS in research and drug discovery.