Phenotypic profiling of small molecules using cell painting assay in HCT116 colorectal cancer cells
2024 PLOS One study that profiled small-molecule effects on HCT116 colorectal cancer cells using the Cell Painting assay. High-content images were acquired and analysed to generate phenotypic fingerprints, demonstrating how CellInsight-class systems support compound mode-of-action discovery in oncology.
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Frequently asked questions about this study
What did the researchers find? They profiled how small molecules change the morphology of HCT116 colorectal cancer cells using the Cell Painting assay, producing phenotypic fingerprints that reveal each compound's mode of action.
How did the CellInsight CX7 contribute? The platform acquired and analysed the high-content images that turned cellular morphology into quantitative phenotypic fingerprints, making the compound mode-of-action comparison possible.
an automated high-content screening and assay platform for the analysis of spheroids at subcellular resolution
2024 PLOS One methods paper presenting an integrated platform for automated high-content screening of 3D tumour spheroids at subcellular resolution. The workflow combines confocal imaging with automated image analysis, relevant to labs running 3D phenotypic screens on CellInsight CX7 LZR systems.
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What is the main advance of this methods paper? It presents an integrated platform for automated high-content screening of 3D tumour spheroids down to subcellular resolution, combining confocal imaging with automated image analysis.
How does the CellInsight CX7 fit into this workflow? The CellInsight CX7 LZR is the kind of high-content system the workflow is built for: it can capture confocal image stacks from multi-well spheroid plates and feed them into automated analysis pipelines.
Cell-vision fusion: a Swin transformer-based approach for predicting kinase inhibitor mechanism of action from Cell Painting data
2024 open-access study that fuses Cell Painting image data with compound structural information via a Swin transformer to predict kinase-inhibitor mechanism of action. It showcases the analytical depth of Cell Painting datasets generated on high-content platforms such as the CellInsight CX7.
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Frequently asked questions about this study
What is the key idea behind Cell-vision fusion? The study merges Cell Painting image data with compound structural information through a Swin transformer to predict how kinase inhibitors exert their mechanism of action.
What does the CellInsight CX7 provide in this approach? It generates the rich, multi-channel Cell Painting image datasets whose morphological depth the Swin transformer fuses with chemical structure to make the predictions.
Imaging-based high-content screening with clickable probes identifies XPB inhibitors
2025 Angewandte Chemie paper that uses image-based high-content screening with clickable chemical probes to discover inhibitors of the XPB helicase. The work illustrates how high-content platforms enable direct target-engagement readouts alongside morphological phenotyping in drug discovery.
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Frequently asked questions about this study
What did the screen identify? It discovered inhibitors of the XPB helicase using image-based high-content screening with clickable chemical probes, linking target engagement to a morphological readout.
How did the CellInsight CX7 support the discovery? The platform's high-content imaging captured the probe signal and morphological phenotypes across the compound collection, providing the image-based evidence for XPB inhibitor selection.
a high-content screen of FDA approved drugs to enhance CAR T cell function: ingenol-3-angelate improves B7-H3-CAR T cell activity by upregulating B7-H3 on the target cell surface via PKCα activation
2024 Journal of Experimental & Clinical Cancer Research study that screened FDA-approved drugs using high-content imaging to identify compounds that boost CAR T cell activity. The approach shows the value of high-content platforms in immuno-oncology target discovery and combination-therapy screening.
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Frequently asked questions about this study
What was the outcome of the FDA-approved drug screen? The screen pinpointed ingenol-3-angelate as a compound that boosts B7-H3-CAR T cell activity by upregulating B7-H3 on target cells through PKCα activation.
How did high-content imaging guide this finding? The CellInsight CX7 enabled quantitative imaging of the drug screen, allowing the team to measure which approved compounds increased B7-H3 surface expression and CAR T potency.
High content image analysis of cellular responses of the murine J774A.1 cell line and primary human alveolar macrophages to an extended panel of pharmaceutical agents
2024 Pharmaceutical Research paper applying high-content image analysis to map macrophage responses to a broad panel of drugs. The study demonstrates multi-parametric phenotyping of primary and cell-line macrophages, a typical CellInsight CX7 use case in drug safety and immunology.
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What did the macrophage profiling reveal? The study mapped how a broad panel of pharmaceutical agents alters the responses of J774A.1 and primary human alveolar macrophages using multi-parametric image analysis.
Why is this a typical CellInsight CX7 application? The CellInsight CX7 is well suited to multi-parametric phenotyping of primary and cell-line macrophages across many compounds, which is exactly what this drug-safety and immunology screen required.
Cell painting transfer increases screening hit rate
2024 Biological Imaging / Cambridge Core study showing that transferring Cell Painting phenotypic models between assays increases screening hit rates. The paper underlines how high-content platforms generate reusable morphological fingerprints that improve drug-discovery efficiency.
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Frequently asked questions about this study
What practical benefit does Cell Painting transfer offer? Transferring Cell Painting phenotypic models between assays increases screening hit rates, so existing image-based models can be reused rather than rebuilt for every new screen.
How does the CellInsight CX7 make this transfer reliable? Because the CellInsight CX7 produces standardized, feature-rich Cell Painting images, phenotypic models trained on one dataset remain predictive when applied to new screens run on the same platform.
Automated morphological profiling via deep learning-based segmentation for high-throughput phenotypic screening
2026 Journal of Imaging methods paper on automated morphological profiling with deep-learning segmentation for high-throughput phenotypic screens. The work aligns directly with CellInsight CX7 workflows where automated segmentation and feature extraction are central to HCA output.
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Frequently asked questions about this study
What is the paper's technical contribution? It describes automated morphological profiling driven by deep-learning segmentation for high-throughput phenotypic screens, streamlining feature extraction from complex images.
How does this connect to the CellInsight CX7? The CellInsight CX7 workflows rely on exactly this pairing: automated image capture followed by deep-learning segmentation and feature extraction, which the paper validates as a scalable profiling approach.