IMPORTANCE OF THE FIELD: Cardiac arrhythmias remain a major challenge for modern drug discovery. Clinical events are paroxysmal, often rare and may be asymptomatic until a highly morbid complication. Target selection is often based on limited information and though highly specific agents are identified in screening, the final efficacy is often compromised by unanticipated systemic responses, a narrow therapeutic index and substantial toxicities. AREAS COVERED IN THIS REVIEW: Our understanding of complexity of arrhythmogenesis has grown dramatically over the last two decades, and the range of potential disease mechanisms now includes pathways previously thought only tangentially involved in arrhythmia. This review surveys the literature on arrhythmia mechanisms from 1965 to the present day, outlines the complex biology underlying potentially each and every rhythm disturbance, and highlights the problems for rational target identification. The rationale for in vivo screening is described and the utility of the zebrafish for this approach and for complementary work in functional genomics is discussed. Current limitations of the model in this setting and the need for careful validation in new disease areas are also described. WHAT THE READER WILL GAIN: An overview of the complex mechanisms underlying most clinical arrhythmias, and insight into the limits of ion channel conductances as drug targets. An introduction to the zebrafish as a model organism, in particular for cardiovascular biology. Potential approaches to overcoming the hurdles to drug discovery in the face of complex biology including in vivo screening of zebrafish genetic disease models. TAKE HOME MESSAGE: In vivo screening in faithful disease models allows the effects of drugs on integrative physiology and disease biology to be captured during the screening process, in a manner agnostic to potential drug target or targets. This systematic strategy bypasses current gaps in our understanding of disease biology, but emphasizes the importance of the rigor of the disease model.