Ion channels are attractive targets for developing new treatments for diseases of the nervous system that involve aberrant electrical activity of neurons, including pain. As many large pharmaceutical companies have discontinued or reduced ion channel research, new directions in drug discovery may increasingly depend on research in academic and small biotech laboratories. Smaller budgets and compressed timelines make drug development in an academic setting challenging. At the same time, increased knowledge about the differential expression of various types of ion channels in different kinds of neurons enables a more rational approach to finding drugs designed to selectively inhibit electrical activity of the neurons underlying pain signaling, and academic research centers can exploit expertise in multiple labs. We describe the evolution of a workflow that integrates a combination of ion channel-focused compound identification (high-throughput fluorescence-based thallium flux screens, followed by 384-channel automated patch clamp) together with phenotypic assays of compound effects on overall excitability of both target and non-target native neurons, using manual patch clamp recording, multi-electrode array recording, and GCaMP-based assays of excitability, with early integration of high-throughput in vivo testing using automated machine learning behavioral tests. We will discuss the challenges of identifying optimal targets, integrating studies on human and rodent channels and neurons, and scaling up electrophysiological and behavioral tests of overall neuronal function that are traditionally done on a smaller scale.