Limited open-source data is a major bottleneck to AI approaches in many areas including drug discovery and design. It is hoped that synergy between academia, start-ups, and pharmaceutical companies will further increase available data for learning, accelerate the design of new drug candidates, and reduce the gap that often exists between academia and industry. This may, however, be a fond hope as the entities in the pharmaceutical industry typically have different research agendas from academic scientists, and there is, of course, the issue of proprietary data that is an important constraint on the sharing of data generated within pharmaceutical companies.