High-throughput contractility analysis platform for drug-response evaluation of hiPSC-derived cardiac models based on...

In vitro modelling of cardiac microtissues via human pluripotent stem cell-derived cardiomyocytes (hiPSCs-CMs) holds great promise in experimental pharmacology, especially to improve drug safety and efficacy evaluation. However, the predictive capability of these models is currently hampered by a series of heterogeneity sources mainly related, but not limited to, their immature phenotype. While increased levels of complexity in human-derived models can favor maturation, differences in experimental approaches introduce variability in electrophysiological responses, which is difficult to mitigate. To tackle these aspects, this work proposes a novel measurement strategy in the dynamic frequency regime to induce and analyze multiple operation modes in hiPSC-CMs contraction during drug evaluation. We designed and validated a system for fully automated analysis of cardiac models in a dynamic regime via optical time-lapse microscopy. We show that repeated video-based measurements of the same biological samples in the presence of physical conditioning allow, with appropriate normalization and adjustment operations, accurate estimates of the responses of interest. The analyzed operation modes provided increased representativeness of video-based contractile parameters and reliable trend estimates of concentration-response curves without requiring a high number of biological replicates. In particular, the findings obtained with four benchmark experimental models, including two-dimensional (2D), two-dimensional aligned (2DA), tridimensional microtissues (3D-MTs), and engineered heart tissues (EHTs) in triple cell-type co-culturing, indicate that the proposed approach is effective in drug-response evaluation of four pharmacological compounds with known expected effects and a reference solvent, and offers a promising foundation for the development of high-throughput and robust tools for pharmacological screening.