This is a nice article and is a great example of a few technological advances that are making now an incredible time to start a biotech company: massive increas

This is a nice article and is a great example of a few technological advances that are making now an incredible time to start a biotech company: massive increase in genomic data and advances in biology (in this case stem cells) to enable better modeling of whether things will work in humans It costs up to $2.6B to develop a drug. The majority of this is not out of pocket spend on developing the drug, but the cost of risk -- all the money spent on drugs that end up failing. The biggest driver of the cost of failure is failing in Phase 2. Phase 2 trials are the first test of whether a drug is effective in humans. Prior studies look at animal or cellular models of effectiveness, or safety in humans. It can cost $50-100M+ to get to phase 2 Genomic data is one of the most cost efficient ways to predict whether a drug will work in humans. certain mutations, like apoe4, are strongly correlated with disease risk and prognosis. Of course this does not imply causality, but researchers can tease this out with established models. Clinical trials of drugs based on genetic markers have greatly increased odds of success Genetic biomarkers also enable smaller studies -- rather than study big heterogenous population to find a signal, you can do so with a smaller homogenous population. This is all very important for Alzheimer's, a field where trials are big and expensive and failure is the norm The other advance is the ability to easily create neural cells from skin cells. As the paper says, mice are very different than humans, especially neurologically. But it's hard to study human neurons in the lab. The ability to turn skin cells into stem cells and then into other cells enables this (previously only embryonic stem cells were available). So researchers can perform experiments to determine causation in a model that is much better predictor than typical mouse models There has been a lot of work in cancer developing genetically targeted drugs, but it is not as common in other fields. Part of the challenge is getting enough data, and part of it is that data alone isn't enough, you really need the biological hypothesis to come first