ML (or anything really) that could predict which molecules would work in humans without testing them in humans would probably be on of the most important advanc

ML (or anything really) that could predict which molecules would work in humans without testing them in humans would probably be on of the most important advances in medicine ever, and would massively lower drug costs and open up new areas for drug research Phase 2 failure -- ie stuff failing in humans after working in mice -- is the biggest cost driver in drug dev. You spend $50-100M+ to get there and 35% of things fail. If you could eliminate you'd cut a massive chunk of the cost and risk of drug dev However I don't think ML is the thing to study if you want to create ML to predict whether drugs will work in people. There is not enough data about how the human body works to develop a good model. Better to work in biology to develop good models of disease, or in developing tools to better measure the molecular biology of the living human body. It's unclear if predicting drug effectiveness with ML will be possible in our generation For more near term applications of ML in drug discovery and development see here: https://www.getrevue.co/profile/nathanbenaich/issues/6-impactful-applications-of-ai-to-the-life-sciences-new-essay-150757 https://www.getrevue.co/profile/nathanbenaich/issues/6-impac...