Inversion and computational maturation of drug response using human stem cell derived cardiomyocytes in microphysiological systems.
Our research represents the intersection of two technologies, advanced hiPSC organ-on-chip systems and computation modeling of excitable cells, in order to leverage both to improve understanding and prediction of drug induced cardiac events. hiPSCs represent a powerful new tool for in vitro research, however, a principal challenge for their application is the relative immaturity of the hiPSC-derived cells compared to their in vivo counterparts. This is particularly difficult in the case of cardiomyocytes, since these cells develop and mature over decades in the body, rendering lab reproduction impractical. In this manuscript, we suggest a novel remedy for this problem - the mapping of data collected using immature hiPSC-derived cardiomyocytes directly onto developed mathematical models of mature cells. We demonstrate that changes to optically measured transmembrane potentials and calcium dynamics from ion channel blocking drugs in hiPSC-derived cardiomyocytes can be effectively inverted, and this inversion can be used to estimate how the drug would behave in adult cardiomyocytes. In this way, we provide a new framework for leveraging the human specificity of hiPSCs to detect unwanted cardiac side effects of new compounds, a practical problem of immense importance in drug development.
While cardiomyocytes differentiated from human induced pluripotent stems cells (hiPSCs) hold great promise for drug screening, the electrophysiological properties of these cells can be variable and immature, producing results that are significantly different from their human adult counterparts. Here, we describe a computational framework to address this limitation, and show how in silico methods, applied to measurements on immature cardiomyocytes, can be used to both identify drug action and to predict its effect in mature cells. Our synthetic and experimental results indicate that optically obtained waveforms of voltage and calcium from microphysiological systems can be inverted into information on drug ion channel blockage, and then, through assuming functional invariance of proteins during maturation, this data can be used to predict drug induced changes in mature ventricular cells. Together, this pipeline of measurements and computational analysis could significantly improve the ability of hiPSC derived cardiomycocytes to predict dangerous drug side effects.