Background and Purpose: Before advancing to clinical trials, new drugs are screened for their proarrhythmic potential using a method that is overly conservative and provides limited mechanistic insight. The shortcomings of this approach can lead to the misclassification of beneficial drugs as proarrhythmic. Experimental Approach: An in silico-in vitro pipeline was developed to circumvent these shortcomings. A computational human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CMs) model was used as part of a genetic algorithm to design experiments, specifically electrophysiological voltage-clamp (VC) protocols, to identify which of several cardiac ion channels were blocked during in vitro drug studies. Such VC data, along with dynamically clamped action potentials (AP), were acquired from iPSC-CMs before and after treatment with a control solution or a low- (verapamil), intermediate- (cisapride), or high-risk (quinidine or quinine) drug. Key Results: Significant AP prolongation (a proarrhythmia marker) was seen in response to both high-risk drugs. The VC protocol identified block of IKr (a source of arrhythmias) by all strong IKr blockers, including cisapride, quinidine, and quinine. The protocol also detected block of ICaL by verapamil and Ito by quinidine. Further demonstrating the power of the approach, the VC data uncovered a previously unidentified funny current (If) block by quinine, which was confirmed with experiments using a HEK-293 expression system and automated patch-clamp. Conclusion and Implications: We developed an in silico-in vitro pipeline that simultaneously identifies proarrhythmia risk and mechanism of ion channel-blocking drugs. The approach offers a new tool for evaluating cardiotoxicity in the preclinical drug screening phase.