Satomic

It's time for all drug developers to reconsider heavily relying on Wuxi to synthesize their proprietary compounds How $ERAS obtained ERAS-0015 from Wuxi>Joyo>$ERAS should be a case study $RVMD used Wuxi to synthesize their very early pan-RAS compounds, and guess what? Wuxi imminently came up with the nearly identical structures as Darax and tried to patent that...

In the AI era, the traditional biopharma industry is the underdog. Big tech and AI labs are building wet labs. China has overtaken Europe in molecules produced. But the tools available to the industry discuss science, not do it. The hard problem in AI for science is at the interface between the physical and digital worlds. We built an AI Scientist at that seam. It wires together the digital and physical worlds of R&D. Predictive models, data infrastructure, wet lab execution feed into a single loop that reasons, acts, and improves with every experiment. Our ambition: get molecules to the clinic twice as fast. Last fall I wrote about why biotech needs to be rebuilt for the AI era. Today I'm sharing the next chapter: what the AI Scientist is, a blueprint for how it works, and why even Richard Feynman couldn't hack it in a wet lab.