Cardiovascular disease is the leading cause of death in the United States, with over 10% of these deaths attributed to cardiac arrhythmias. We believe novel arrhythmia therapies developed over the coming decades have the potential to substantially improve patient outcomes through the use of increasingly sophisticated precision medicine tools. One such tool --- induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) --- provides a laboratory model for patient-specific investigations. These iPSC-CMs are currently used at academic medical centers to study arrhythmia mechanisms, and by pharmaceutical companies to study the proarrhythmic potential of drugs before clinical trials. While promising, these cells are limited by their relatively immature electrophysiological phenotype and cell-to-cell heterogeneity. Such shortcomings have adversely affected the reproducibility, consistency, and depth of insights from studies with these cells. In this thesis, we develop a novel approach called rapid ionic current phenotyping (RICP) that can be used to investigate the sources and extent of electrophysiological heterogeneity during iPSC-CM patch-clamp experiments. We use this method to study variations in physiology and patch clamp experimental artifact conditions that lead to the heterogeneous phenotype of iPSC-CMs. Based on these findings, we propose best practice methods to mitigate sources of electrophysiological heterogeneity during experiments and address their knock-on effects during post-processing. We use the RICP method in a drug cardiotoxicity screening pipeline, showing how we can acquire surrogate markers of cardiotoxicity and identify proarrhythmia mechanisms from the same iPSC-CM. Finally, we extend the RICP approach for use in an automated patch clamp system to demonstrate its potential in a high throughput setup that is more scalable in an industry setting. Ultimately, we believe RICP, together with insights it has provided in this thesis, has the potential to affect basic science arrhythmia research, and impact the way drugs are screened.