Today we’re joined by Jannis Born, Ph.D. student at ETH & IBM Research Zurich. We caught up with Jannis a few weeks back at NeurIPS, to discuss:  His research paper “PaccMannRL: Designing anticancer drugs from transcriptomic data via reinforcement learning,” a framework built to accelerate new anticancer drug discovery.  How his background in cognitive science and computational neuroscience applies to his current ML research. How reinforcement learning fits into the goal of cancer drug discovery, and how deep learning has changed this research. Jannis describes a few interesting observations made during the training of their DRL learner.  And of course, Jannis offers us a step-by-step walkthrough of how the framework works to predict the sensitivity of cancer drugs on a cell and subsequently discover new anticancer drugs.  Check out the complete show notes for this episode at twimlai.com/talk/341.