Deep Learning-Assisted Nephrotoxicity Testing with Bioprinted Renal Spheroids

Kevin Tröndle, Guilherme Miotto, Ludovica Rizzo, Roman Pichler, Fritz Koch, Peter Koltay, Roland Zengerle, Soeren S. Lienkamp, Sabrina Kartmann, Stefan Zimmermann

Article ID: 528
Vol 8, Issue 2, 2022, Article identifier:

VIEWS - 760 (Abstract) 244 (PDF) 101 (PDF)

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Abstract


We used arrays of bioprinted renal epithelial cell spheroids for toxicity testing with cisplatin. The concentration dependent cell death rate was determined using a lactate dehydrogenase assay. Bioprinted spheroids showed enhanced sensitivity to the treatment in comparison to monolayers of the same cell type. The measured dose-response curves revealed an inhibitory concentration of the spheroids of IC50 = 9 ± 3 μM in contrast to the monolayers with IC50 = 17 ± 2 μM. Fluorescent labeling of a nephrotoxicity biomarker, kidney injury molecule 1 indicated an accumulation of the molecule in the central lumen of the spheroids. Finally, we tested an approach for an automatic readout of toxicity based on microscopic images with deep learning. Therefore, we created a dataset comprising images of single spheroids, with corresponding labels of the determined cell death rates for training. The algorithm was able to distinguish between three classes of no, mild, and severe treatment effects with a balanced accuracy of 78.7%.


Keywords


Bioprinting, Spheroids, Kidney, Nephrotoxicity, Deep learning


Included Database


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DOI: http://dx.doi.org/10.18063/ijb.v8i2.528

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