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Review of high-content screening applications in toxicology

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Abstract

High-content screening (HCS) technology combining automated microscopy and quantitative image analysis can address biological questions in academia and the pharmaceutical industry. Various HCS experimental applications have been utilized in the research field of in vitro toxicology. In this review, we describe several HCS application approaches used for studying the mechanism of compound toxicity, highlight some challenges faced in the toxicological community, and discuss the future directions of HCS in regards to new models, new reagents, data management, and informatics. Many specialized areas of toxicology including developmental toxicity, genotoxicity, developmental neurotoxicity/neurotoxicity, hepatotoxicity, cardiotoxicity, and nephrotoxicity will be examined. In addition, several newly developed cellular assay models including induced pluripotent stem cells (iPSCs), three-dimensional (3D) cell models, and tissues-on-a-chip will be discussed. New genome-editing technologies (e.g., CRISPR/Cas9), data analyzing tools for imaging, and coupling with high-content assays will be reviewed. Finally, the applications of machine learning to image processing will be explored. These new HCS approaches offer a huge step forward in dissecting biological processes, developing drugs, and making toxicology studies easier.

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Acknowledgements

This study was supported in part by the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health. The authors thank Dr. DeeAnn Visk for assistance of editing the manuscript. The views expressed in this review are those of the authors and do not necessarily reflect the statements, opinions, views, conclusions, or policies of the National Center for Advancing Translational Sciences, the NIH. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

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Correspondence to Menghang Xia.

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Li, S., Xia, M. Review of high-content screening applications in toxicology. Arch Toxicol 93, 3387–3396 (2019). https://doi.org/10.1007/s00204-019-02593-5

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