Example of how precarious a position the off-shoring CRO model has left biopharma innovation in. Silver lining: breaking the incremental labor arb addiction forces an overdue rethink of how synthesis / research broadly gets done just in time to re-orient that foundation for AI.

AI Scientists "discuss science, not do it" @sajithw & @benchling get it. AI for Science is sandwiched by physical layers both upstream (train = move measure atoms) & down (deploy = manipulate make). Who connects those (and where they do it) matters a lot. @satomic_ai is on it.

1/I'm not a scientist, but have spent my career learning that the most important thing you can build in life sciences isn't a drug, but the infrastructure that makes better drugs inevitable. Today we're starting to talk about what we're building at @satomic_ai to do just that.

I spent 20 years at Neurocrine building automated chemistry platforms because I believed something most people didn't yet: Chemistry doesn't have to move at the pace it traditionally has. We found an advanced lead in 6 rounds of synthesis. Six days. We replicated 20 years of CRF biology in one month. But the most important thing I learned wasn't about speed. It was this: Automation is not the goal. Better chemistry is the goal. When automation is built around the chemistry — respecting reaction behavior, purification constraints, data quality — it becomes transformational. When it's not, it becomes theater. That distinction is why I built Satomic. We're generating chemistry data at scale, with rigor, to close the gap from idea to molecule — and to build the foundation that makes synthesis predictable rather than intuitive. I started this work because of my grandfather. It became something bigger. Launching with early customers this fall. $15M seed round. Great investors. Heads down building.

what does an on-shore, autonomous WuXi actually look like and why does it win. not just about competing with china today but taking over their foothold in europe and maybe even asia. - advantageous geo-positioning to ensure long-term ability of companies to work in the US - end-to-end automation starting with the need to haves like chemical synthesis (this I'm less clear on because of chinas strategic initiatives and brute force ability in hardware) - modalities that haven't yet been translated to china (hard esp as they are pioneering new modalities such as mini binders) - faster turnaround time if you have hardware colocated with scientists for hours feedback times. on-sight precious samples needed ( hard if samples are general/not precious as it puts the power back to Wuxi and other co's back into the hardware increases) upshot is that tech might not matter as much in the race as perceived and real threat of ip leaks and advancement losses. maybe missing something here but would love to see a us/europe cloud labs really start competing. think @plasmidsaurus is a version of us.