We presented here a new deep learning-based platform for multi-objective drug hit optimization, which incorporates the generation of analog molecules, docking, and deep-learning-based binding energy estimation. The platform, called Elion in honor of Nobel laureate Gertrude Elion, encompasses all stages of the lead optimization process. It was designed to be easily extensible with diverse methods and properties and with ease-of-use in mind. We show an illustrative example of using Elion to design new inhibitors for COX-2. In one pass, Elion could suggest 99 compounds predicted to have favorable chemical and pharmacological properties, 82 of which are expected to bind to COX-2 more potently than the known compound Vioxx.