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Using High Content Imaging to Quantify Target Engagement in Adherent Cells
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Evolution and impact of high content imaging.

Gregory P Way1, Heba Sailem2, Steven Shave3

  • 1Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

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High content imaging automates microscopic image acquisition and analysis for biological research. This technology enables large-scale screening of genetic and environmental effects on various biological models, driving scientific discovery.

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Area of Science:

  • Cell Biology
  • Biotechnology
  • Microscopy

Background:

  • High content imaging (HCI) has evolved significantly since the 1990s.
  • It involves automated acquisition and analysis of microscopic images from biological samples.
  • HCI integrates microscopy with robotics for large-scale screening.

Purpose of the Study:

  • Provide a collective perspective on the evolution of high content imaging.
  • Discuss key advancements in HCI from academic and industry viewpoints.
  • Explore future trends in HCI hardware and software.

Main Methods:

  • Review of the evolution of high content imaging techniques.
  • Analysis of image and data analysis pipeline advancements.
  • Discussion on the role of multiomics and data integration.

Main Results:

  • HCI enables high-throughput screening of perturbations in biological systems.
  • Significant progress in image and data analysis has led to multiparametric profiling.
  • Data integration and multiomics are increasingly important.

Conclusions:

  • High content imaging is a powerful tool for biological research and drug discovery.
  • Continued evolution of hardware, software, and data analysis will further enhance its capabilities.
  • Standardization of data repositories and sharing is crucial for future progress.