To the best of our knowledge, this paper is the first attempt to formalise a pragmatic logic of scientific discovery in a manner such that it can be realised by scientists assisted by machines. Using Institution Agents, we define a dialectic process to manage contradiction. This allows autoepistemic Institution Agents to learn from a supervised teaching process. We present an industrial application in the field of Drug Discovery, applying our system in the prediction of pharmaco-kinetic properties (ADME-T) and adverse side effects of therapeutic drug molecules.