Image-based chemical screening

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Abstract

Technological advances have made it feasible to conduct high-throughput small-molecule screens based on visual phenotypes of individual cells, using automated imaging and analysis. These screens are rapidly moving from being small, proof-of-principle tests to robust and widespread screens of hundreds of thousands of compounds. Automated imaging screens maximize the information obtained in an initial screen and improve the ability to select high-quality leads. In this Perspective, I highlight the key steps necessary for conducting a high-throughput image-based chemical compound screen.

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Figure 1
Figure 2: A sampling of image-based phenotypes scored in recent screens.
Figure 3: An example of an unusual, subtle phenotype recently screened in our group and scored automatically using CellProfiler for image analysis and CellVisualizer for machine learning–based automated scoring (raw screening images are shown).

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Acknowledgements

The author sincerely thanks M. Vokes for research and artwork, and N. Tolliday and L. Verplank for helpful comments.

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The author declares no competing financial interests.

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Carpenter, A. Image-based chemical screening. Nat Chem Biol 3, 461–465 (2007) doi:10.1038/nchembio.2007.15

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