Its machine learning systems predict the best ways to synthesize potentially valuable molecules, a crucial part of creating new drugs and treatments. The company's system enters play when you have some exotic new compound you want to make in order to test it in real life, but don't know how to make it. After all, these molecules are brand new to science -- no one has created them before, so why should anyone know? The company leverages machine learning and a large body of knowledge about chemical reactions to create these processes, though as CSO Stanisław Jastrzębski explained, they do it backwards. "Synthesis planning can be characterized as a game," he said.

Say you're a pharmaceutical company. You've figured out that a novel molecule could be effective in treating an illness -- but that molecule only exists in a simulation. How do you actually make it, and enough of it, to test in the real world? Molecule.one is a computational chemistry platform that helps bring theoretical substances to life, and it is debuting its product onstage at Disrupt SF Startup Battlefield. Computational chemistry is, believe it or not, something of a hot ticket right now.