Multi-parameter MEA analysis of hESC-CM demonstrated improved specificity in compound risk assignment over conventional single-parametric approaches for pre-clinical cardiotoxicity screening.
Does multi-parameter MEA profiling of hESC-CM improve specificity in compound risk assignment for pre-clinical cardiotoxicity assays compared to single-parametric approaches?
Multi-parameter MEA profiling of hESC-CM improves specificity in pre-clinical cardiotoxicity screening compared to single-parameter approaches.
Human stem cell derived cardiomyocytes (hESC-CM) provide a potential model for development of improved assays for pre-clinical predictive drug safety screening. We have used multi-electrode array (MEA) analysis of hESC-CM to generate multi-parameter data to profile drug impact on cardiomyocyte electrophysiology using a panel of 21 compounds active against key cardiac ion channels. Our study is the first to apply multi-parameter phenotypic profiling and clustering techniques commonly used for high-content imaging and microarray data to the analysis of electrophysiology data obtained by MEA analysis. Our data show good correlations with previous studies in stem cell derived cardiomyocytes and demonstrate improved specificity in compound risk assignment over convention single-parametric approaches. These analyses indicate great potential for multi-parameter MEA data acquired from hESC-CM to enable drug electrophysiological liabilities to be assessed in pre-clinical cardiotoxicity assays, facilitating informed decision making and liability management at the optimum point in drug development.
Clements et al. (2014) studied Pre-clinical cardiotoxicity. Multi-parameter MEA analysis vs. Conventional single-parametric approaches was evaluated on Compound risk assignment specificity. Multi-parameter MEA analysis of hESC-CM demonstrated improved specificity in compound risk assignment over conventional single-parametric approaches for pre-clinical cardiotoxicity screening.