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Development of high-throughput assays for neurobiology can be challenging, yet it provides access to information not readily available by other means. Evaluation of neurotoxicity effects is an active area of investigation in drug discovery and disease modeling. While high-content imaging is an efficient tool to capture phenotypic changes in neurite morphology, quantitative image analysis is still a challenging task, due to the manifold changes in morphology and the complexity of analysis algorithms used. Deep learning (AI)-based image analysis can address these challenges by reducing the effort and expertise required to capture morphological changes.
In this webinar, we demonstrate a workflow, which integrates the ImageXpress® Micro Confocal system with the AI-based Genedata Imagence platform to analyze neurotoxicity in human iPSC-derived neurons.