Sajith Wickramasekara
@sajithw • 1,775 subscribers
Videos
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.
Sajith Wickramasekara30,736 views • 3 months ago
One of the biggest unsolved problems in making medicines is what comes after AI design. Gleb Kuznetsov, cofounder and CEO of Manifold Bio, is tackling the in vivo bottleneck. Screening hundreds of thousands of antibody designs in a single animal changes what’s possible in drug discovery. I’ve known Gleb since he was my TA at MIT, so it was really fun to have him on Transcribed. We talked about: - Why he left Google to start over in biology (literally showing up at george church’s lab and asking how he could be useful) - How 3 companies came out of his grad school lab bay - What it takes to build a true platform company - Where AI-driven drug discovery is actually headed
Sajith Wickramasekara10,659 views • 6 months ago
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