The path is most likely through reliable structure prediction of drug targets. That would open up rational drug design projects that may have previously been impossible. The only problem is that experimental structure determination is so good in pharma, that it's hard to compete. For example, on a structure-enabled project, it may be possible to experimentally solve multiple high-resolution 3D models per week with an order of magnitude higher accuracy than predicted models. Once you can routinely get structures, there's still the rest of the drug discovery pipeline left to go.
Ah, interesting. How do you experimentally verify that you've solved the 3D model? My first guess is that you can have an agent bind to targets with that structure and then figure out how much binding occurred. This is a very uneducated stab, though.
> experimentally solve multiple high-resolution 3D models per week
I thought this was only true if you already have a structure; otherwise you typically run into the [phase problem](https://en.wikipedia.org/wiki/Phase_problem), which is often a significant hurdle. But I haven't done much biochemistry in years, so there might be better approaches than MAD/MIR/etc. that make the phase problem a non-issue.