A lot of insightful articles have already been written around the recently announced Recursion/Ex...

A lot of insightful articles have already been written around the recently announced Recursion/Exscientia merger in the AI drug discovery space, including the great comments from In-Silico's Alex Zhavoronkov, and more recently from STAT's Allison DeAngelis. Both posts are very much worth checking out (STAT is behind a paywall unfortunately).

I'm now very curious to see how the AI drug discovery space will evolve. Will it become more of a dedicated SaaS or CRO type-play to other companies, or will we revert back to the "traditional" biotech drug-development model all the way to phase II, just with AI enablement?

I personally would be willing to rather bet on the latter, as most of the molecules will eventually be picked up by big pharma anyhow, and the valuation model for compounds is so much more established than for AI tools. This, if you believe the STAT article, is clearly the route that Recursion will be taking, after, as nicely reported by STAT, the earlier stage discovery partnerships with pharma are still somewhat tricky.

Furthermore, until we truly have foundational biology models (which depending on who you ask is still 5-10 years away), the role of the wet lab and traditional chemistry and large molecule development skills shouldn't be underestimated, AI still only gets you so far (though it can help optimize many of the steps in the journey).

Would love to hear your thoughts on this topic.

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