Abstract
Animal models are 78% accurate in determining whether drugs will alter contractility of the human heart. To evaluate the suitability of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) for predictive safety pharmacology, we quantified changes in contractility, voltage, and/or Ca2+ handling in 2D monolayers or 3D engineered heart tissues (EHTs). Protocols were unified via a drug training set, allowing subsequent blinded multicenter evaluation of drugs with known positive, negative, or neutral inotropic effects. Accuracy ranged from 44% to 85% across the platform-cell configurations, indicating the need to refine test conditions. This was achieved by adopting approaches to reduce signal-to-noise ratio, reduce spontaneous beat rate to ≤ 1 Hz or enable chronic testing, improving accuracy to 85% for monolayers and 93% for EHTs. Contraction amplitude was a good predictor of negative inotropes across all the platform-cell configurations and of positive inotropes in the 3D EHTs. Although contraction- and relaxation-time provided confirmatory readouts forpositive inotropes in 3D EHTs, these parameters typically served as the primary source of predictivity in 2D. The reliance of these “secondary” parameters to inotropy in the 2D systems was not automatically intuitive and may be a quirk of hiPSC-CMs, hence require adaptations in interpreting the data from this model system. Of the platform-cell configurations, responses in EHTs aligned most closely to the free therapeutic plasma concentration. This study adds to the notion that hiPSC-CMs could add value to drug safety evaluation.
Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
