Channelopathies induce severe heart rhythm or conduction disorders. Mutations of the KCNH2 gene, that encodes the human (h) ERG channel, is responsible for 30% of all cases of long QT syndrome. Besides, hERG is frequently responsible for off-target effects of several pharmacological agents. With the advent of Next Generation Sequencing, hundreds of new KCNH2 variants are accumulating in various databases, many being of unknown significance to clinicians which hampers the value of their diagnosis and the quality of patient management. Therefore, there is an urgent need to functionally characterize a large fraction of KCNH2 variants and provide access of this information to hospital clinicians. We assembled a consortium of clinicians, geneticists, biophysicists and computer bioscientists to build the largest web-accessible diagnostic/prognostic database of hERG-related channelopathies. To this end, we will take advantage of high-throughput techniques of channel variant phenotyping.