PaccMann^RL: Designing Anticancer Drugs with Reinforcement Learning w/ Jannis Born - #341

This article discusses the research of Jannis Born, focusing on the application of reinforcement learning (RL) in anticancer drug discovery. The core of the research, "PaccMann^RL", utilizes RL to predict the sensitivity of cancer drugs on cells and subsequently discover new anticancer drugs. The interview with Born covers his background in computational neuroscience, the role of RL in drug discovery, and the impact of deep learning (DL) on his research. The article promises a step-by-step explanation of the framework's functionality.

• •PaccMann^RL uses reinforcement learning for anticancer drug discovery.
• •The research involves predicting drug sensitivity and discovering new drugs.
• •The framework integrates computational neuroscience and deep learning.