ArticleToxicological sciences : an official journal of the Society of Toxicology2025
Computationally informed point of departure evaluation for proarrhythmic cardiotoxicity assessment using 3D engineered cardiac microtissues from human iPSC-derived cardiomyocytes.
Article in Toxicological sciences : an official journal of the Society of Toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are a promising new approach for in vitro proarrhythmic cardiotoxicity assessment. However, variation due to differentiation batch, individual sample variation, and non-linear responses to test drugs complicate the prediction of proarrhythmic drug concentrations. This study combines a computational human action potential (AP) model of hERG channel block with experimental data from three-dimensional hiPSC-CM engineered microtissues to optimize point of departure (POD) estimation of drug-induced prolongation of AP duration (APD). Computer simulations predicted that APD prolongation from hERG block follows a logistic curve and that >81% hERG block induced early afterdepolarizations (EADs), which significantly shifted the APD response curve. Curve fitting of APD response by logistic, bilinear breakpoint, and maximal curvature was more accurate prior to EAD onset. Goodness-of-fit testing indicated that logistic regression with ≥6 test concentrations was sufficient to accurately estimate PODs. Power analysis, based on experimental variations between batches (n = 14), molds (n = 57), and microtissues (n = 1701), predicted that PODs from 2 ∼ 3 batches with 10 microtissues per mold using a 5% threshold for APD prolongation detected proarrhythmic cardiotoxicity with a negligible false positive rate. We then applied this POD analysis to hiPSC-CM microtissue data after treatment with well-characterized drugs (i.e. cisapride, ranolazine, quinidine, and verapamil). Using bootstrapping, we estimated PODs and confidence intervals that matched concentrations known to cause proarrhythmic effects in patients. This study identified a robust method for calculating PODs for proarrhythmic cardiotoxicity risk in vitro and developed a framework for experimental design in this and other in vitro platforms.
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