Set Sensible Metrics

So it's funny when you go into Y Combinator, you meet in these groups and they tell you to set metrics every week. Every week we're going in, other people were like, oh, we have this 30% week over week user growth. Our metric initially was number of drugs discovered, which was always zero. So it's always like, yeah, zero drugs discovered this week, same last week and same next week. And actually that was a really, I feel like a key lesson for me to understand that actually metrics for all companies are not the same and when to kind of like adopt advice and when to ignore it or when to adopt a different form of advice. And so for us, the metrics were always around technical risk. So I think obviously if you can create a drug that works, every pharma company will want it and every patient will want it. The kind of question is, how do you actually create a case that your technology works? So a lot of our early milestones were technical. It was showing, okay, we made this prediction, can we put it in some cells and show that it actually works? Which actually in and of itself is a big step because of the silos, computational teams infrequently actually test their predictions. Then next was, if we put into a living animal, could we actually see an effect? And then could we actually make a drug that was safe and non toxic? A lot of our milestones are very much scientific based. And then another big one was the team, can we actually recruit a team that really bought into the idea enough to join? And that's actually a big de risking factor for people because no one knows the technology more like engineers and scientists. So if you have really high quality scientists that are coming into your company that are all in, that's also a really positive signal for other folks as well.