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• W4210285493 abstract "Discovery of therapeutics for neurological diseases is hampered by the lack of predictive in vitro and in vivo models. Traditionally, in vitro assays rely on engineered cell lines grown two-dimensionally (2D) outside a physiological tissue context, which makes them very amenable for large scale drug screening but reduces their relevance to in vivo neurophysiology. In recent years, three-dimensional (3D) neural cell culture models derived from human induced pluripotent stem cells (iPSCs) have been developed as an in vitro assay platform to investigate brain development, neurological diseases, and for drug screening. iPSC-derived neural spheroids or organoids can be developed to include complex neuronal and glial cell populations and display spontaneous, synchronous activity, which is a hallmark of in vivo neural communication. In this report we present a proof-of-concept study evaluating 3D iPSC-derived cortical neural spheroids as a physiologically- and pharmacologically-relevant high-throughput screening (HTS) platform and investigate their potential for use for therapeutic development. To this end, a library of 687 neuroactive compounds were tested in a phenotypic screening paradigm which measured calcium activity as a functional biomarker for neural modulation through fluctuations in calcium fluorescence. Pharmacological responses of cortical neural spheroids were analyzed using a multi-parametric approach, whereby seven peak characteristics from the calcium activity in each well were quantified and incorporated into principal component analysis and Sammon mapping to measure compound response. Here, we describe the implementation of the 687-compound library screen and data analysis demonstrating that iPSC-derived cortical spheroids are a robust and information-rich assay platform for HTS." @default.
• W4210285493 created "2022-02-08" @default.
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• W4210285493 date "2022-06-01" @default.
• W4210285493 modified "2023-10-14" @default.
• W4210285493 title "A multiparametric calcium signal screening platform using iPSC-derived cortical neural spheroids." @default.
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• W4210285493 doi "https://doi.org/10.1016/j.slasd.2022.01.003" @default.
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