[a_bonobo]

I actually do this for a living within pharma now! There's a TON of work that goes into drug discovery before we even call it a program. The odds of success are low, so we put in months of work evaluating a candidate before even have a hunch of a program.

Yes, the science advances, previously high-hanging fruits become low-hanging become high-hanging again [1], but the tooling also advances: we now have databases like OpenTargets which let us more easily evaluate potential drug targets. Failure is so much more than that, though: a program can fail after you've shown efficacy in animals, sometimes it just doesn't happen in the human subjects. Or you fail to find the right measurement (endpoint). A million ways to die.

[1] Gene editing is an example: impossible, then very possible, but now the blocker is public perception which in turn blocks investment.

[ip26]

Is public perception the greater problem, or delivery? My outsider read has been relatively few diseases can be targeted right now due to payload delivery obstacles

[a_bonobo]

Yes, getting the drug into the right cell or tissue is still largely unsolved (kidney is easier than brain, of course). But the investors we talk with have dropped all interest in gene editing, too risky. RNA-based technologies are great, though - ASOs, siRNAs etc. Investors are very happy with those :)

[pmarreck]

Out of employable curiosity, is there anything that pharma might need help with in terms of coding, pattern-matching, AI assistance, reproducibility, determinism, software controls, ETL, reliable workflow design, or simple IT advice?

[a_bonobo]

Depends in which country you are! IT advice is handled by your regular IT service companies. AI assistance is going gangbusters, as evidenced by Anthropic hiring biologists left and right, places like Isomorphic Labs and Xaira have huge valuations.

[pmarreck]

I live in the NYC vicinity (about an hour away by car, less by train, on Long Island)