Heart failure affects 2-3% of the US population and remains the single largest cause of mortality. Despite the large unmet need, heart failure drug development is notoriously difficult, and few first-in- class drugs have been approved in the past decade. Human induced pluripotent stem cell (hiPSC)- based models of heart disease are widely considered to hold tremendous potential for the development of heart failure drugs because they faithfully model disease phenotypes and reflect individual patient genetics. However, their utility for drug screening is limited because the technology for assessing disease modifying effects are too cumbersome and low throughput for large-scale screens. Visualizing disease-modifying activity of genes and drugs for heart failure requires kinetic read outs of cardiomyocyte function that correlate calcium (Ca2+) cycling with contractile force and resting tension to reveal systolic and diastolic heart dysfunction. The lack of off-the-shelf solutions for simultaneous measurement of these parameters is a critical gap that has hindered the pace of basic research into disease mechanisms and drug development. Although modern high content imaging systems can acquire the requisite fast kinetic datasets, the major roadblock is that available data analysis tools lack key capabilities, are too low throughput, and/or require substantial coding expertise to implement in large-scale genetic studies and drug discovery. Resolving this roadblock will be transformative by placing powerful tools in the hands of scientists without coding expertise, enabling them to develop gene and drug screens using iPSC and adult cardiomyocyte models of heart failure. We will deliver an integrated toolbox of software, reagents, and standardized protocols for contemporaneous measurement of intracellular and subcellular Ca2+ dynamics with contractile force and resting tension that can be overlaid with subcellular feature detection – all compatible with 384-well plate format – to model systolic and diastolic heart function. The software will have a user-friendly graphical user interface to fully automate measurements of Ca2+- contractility force curves (in absolute µM and nN terms) from beating cardiomyocytes. A key feature will be individual, cell-by-cell analysis that will increase dynamic range and allow the recognition of cellular heterogeneity in the preparations making possible realistic culture models with multiple cell types. We will also develop a toolkit of viral vectors to deliver genetically encoded sensors of absolute intracellular Ca2+ concentrations in cardiomyocyte populations without generating stable cell lines. The integrated platform will be validated and benchmarked against current software in pilot drug and gene screens that demonstrate ability to quantify disease-modifying activities for systolic and diastolic heart disease. Quantitative performance measures will evaluate assay readiness.