At the time I first got involved, Google Health was still a thing but it was clear it was not going to be successful. I felt that Google's ML (even early on, they had tons of ML, just most of it wasn't known externally) was going to be very useful for genomics and drug discovery.
Verily was its own thing that was unrelated to my push in Research. I think Larry Page knew Andy Conrad and told him he could do what he wanted (which led to Verily focusing on medical devices, which is a terrible industry to be in). They've pivoted a few times without much real success. My hope is that Alphabet sheds Verily (they've been trying) or just admit it's a failure and shut it down. It was just never run with the right philosophy.
Calico... that came out of Larry and Art Levinson- I guess Larry thought Art knew the secret to living forever and by giving him billions Art would come up with the solution to immortality and Larry would have first access to it. But they were ultra-secretive and tried to have the best of both worlds- full access to Google3 and borg, but without Googlers having any access to calico. That, combined with a number of other things, have led Calico to just be a quiet and not very interesting research group. I expect it to disband at some point.
Isomorphic is more recent than any of the stuff I was involved in, and is DeepMind (specifically Demis's) attempt to commercialize their work with AlphaFold. However, everybody in the field knows the strategy of 1. solve protein structure prediction 2. ??? 3. design profitable drugs and get them approved... is not a great strategy because protein structure determine has not ever been the rate limiting step to identifying targets and developing leads. I agree I don't really see a future for it but Demis has at least 10-20 years of runway before he has to take off or bail.
All of my suggestions were just for Google to do research with the community and publish it (especially the model code and weights, but also pipelines to prep data for learning) and turn a few of the ideas into products in Google Cloud(that's how Google Genomics was born... I was talking to Jeff, and he said "if we compress the genome enough, we can store it all on Flash, which would make search fast but cheap, and we'd have a useful product for genomics analysis companies"). IMHO Jeff's team substantially achieved their goals before the DeepMind stuff- DeepVariant was well-respected, but almost every person who worked on it and related systems got burned out and moved on.
What is success, anyway, in biotech? Is it making a drug that makes a lot of money? What if you do that, but it costs so much that people go bankrupt taking it? Or is the goal to make substantial improvements to the technology, potentially discovering key biological details that truly improve people's lives? Many would say that becoming a successful real estate ownership company is the real destination of any successful pharma/biotech.