I was going to mention this. Andy Grove wrote a number of papers where he said "if biotech just does what the tech sector does, we'd have hundreds of new drugs".
The fact is, it doesn't work that way in biology. When developing new biotech, you'd be lucky if you understood 5% of what a new drug does in the body (sometimes it's 0%!). Serendipity plays a huge part in new drug discovery, although most companies don't like to admit it.
Also, I'm not surprised that Google has matured to the point where "moonshots" don't work so well. You see it in biopharma as well. Huge companies, with billions of dollars of R&D spend fail to produce new innovation on a regular basis. It's the small biotech companies that seem to come up with the innovations, often on a much smaller budget.
The reasons for that are multiple, but it does come down to a big company worrying about how they will grow their $100 billion company by 10% (finding $10B in business isn't easy) and the fact that with large companies comes structure, process and other things that stifle innovation.
I don't think Andy was completely wrong, or right, in his thinking that if biotech copied tech, they would be more successful. He was naive, and didn't really understand the underlying structural reasons for the inability to translate the tech sector to the biotech sector.
I went from academia to industry to learn how to do what Andy said: make biotech copy tech. In many ways, I was extremely successful: I built Exacycle, which took Google's style of warehouse computing and made it available to a number of biology researchers. The scientists who were successful with it basically had to drop a lot of the preconceived notions about how to solve problems- they were accustomed to spending a huge amount of time setting up their simulations or drug docking (months or years of prep work before running sims for a year). Exacycle converted this to a rapid cycle where they could test an idea in a day on 600+Kcores/sec, make a few tweaks, and run again. This greatly sped up the productivity of scientists.
Ultimately, these ideas weren't well received in biotech until we published a bombshell paper on GPCRs that spoke to them in their language. Even then, it wasn't a product that I think any biotech would want to buy (this is the part where Andy was spot-on). I think Google/Verily paid attention to what we had to say and hopefully, they'll be able to succeed in ways that biotech does not.
At this point, though, I think the nail is in the coffin for rational drug design as a multibillion dollar investment for pharma. It's just not productive enough. Instead, I think pharma needs to solve the inverse problem: for every drug that is already approved for something, what diseases can it impact (the RDD problem is "for a given disease, find a drug that modulates the disease").
The real nail is that each individual is unique. There are not X number of disease cases out there, there are Y number of more or less closely related disease states. We might say that someone is suffering from the disease of high blood pressure, but the underlying causes and hence ideal treatment is unique to that individual. Add in idiosyncratic responses and the drug discovery problem is almost impossible.
The fact is, it doesn't work that way in biology. When
developing new biotech, you'd be lucky if you understood
5% of what a new drug does in the body (sometimes it's 0%!).
What’s rather alarming is the sequence of this current
minimal cell: of those 473 genes, 149 of them are of
unknown function.
In the simplest possible bacterial cell, we don't know what fully 31% of the genes do. They're of vital importance to the cell, they're manufacturing proteins it absolutely cannot do without, and we don't know what any of them are.
The example that I really like is the drug Lyrica. It came from research at Northwestern. Made total sense, take a neurotransmitter (GABA) and modify it so it blocks the GABAase enzyme. Perfect! You get more GABA floating around.
The drug made it all the way to market until some folks realized, it doesn't work via GABA at all. It actually impacts the glutamate neurotransmitter.
Yeah biology is sophisticomplexicated. But I believe mostly because of wrong approach and tools. Maybe this era will provide finer views and better abstractions to think about cells, organs, etc.
The trouble is that there is some (new) biological science that takes the old massive and powerful tool and applies them to low-hanging fruit that were (until recently), not worth the effort. I've been waiting for some of these moonshot-ish plans to take on these problems, rather than try and compete with the Goliath drug companies. Sadly, since they keep hiring from drug-company stock, they keep getting the same result.
New fragrances & colors (L'Oreal), new materials (Bolt Threads), new sensors, new foods (Impossible Foods), and further, all the infrastructure required to nurture these kinds of companies. A Google-X-Style project designed to build the boring digital infrastructure that links all of the above companies would be so enabling, if less sexy.
For all the issues I have with for-profit medical care as a root concept, I must say that "disrupting the clinical trial red-tape" is not a phrase I'm interested in seeing anytime soon.
There is a reason pharma and biotech companies are slow lumbering giants. It's so they can absorb the impact of R&D failures.