Loading video...

Video Failed to Load

Go Home

High-quality experimental data fuels biological discovery. Could an AI-enabled "autonomous lab" fundamentally increase the rate at which we generate it, and accelerate our progress toward cures for disease? That's the question I sat down to explore with Jason Kelly, CEO of Ginkgo Bioworks, for a deep-dive and tour of...

11,508 views • 3 months ago •via X (Twitter)

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

How can generative AI and Robotics help advance drug discovery? 🚀 Excited to introduce LUMI-lab! A foundation model-driven Self-Driving Lab (SDL) for autonomous ionizable lipid discovery in mRNA delivery 🤖🔍 🔬 What is LUMI-lab? LUMI-lab integrates molecular foundation models with autonomous robotic experiments to efficiently explore new LNPs (lipid nanoparticles, mRNA delivery vehicles) with minimal wet-lab data. 🔥 Key Highlights: - 🧠 Foundation model trained on 28M molecules using a three-step strategy: - Unsupervised pretraining to capture broad molecular knowledge - Continual pretraining to specialize in lipid-like molecules - Active learning fine-tuning within a closed-loop experimental system - 🤖 1,700+ new LNPs synthesized & tested across 10 iterative cycles - 🧪 Brominated lipids autonomously identified as a novel structural feature that enhances mRNA transfection—an insight previously unrecognized in LNP design - 🏆 20.3% in vivo CRISPR gene editing efficiency in lung epithelial cells—the highest reported for inhaled LNPs 🚀 Why it matters? LNPs are the backbone of mRNA therapeutics, yet discovery has been slow due to data scarcity. LUMI-lab shows that AI-powered autonomous labs can accelerate mRNA delivery innovation🚀💡 🌐 Beyond mRNA drugs, LUMI-lab exemplifies a scalable framework for AI-driven molecular discovery, pushing boundaries in material science & drug delivery. 📜 Read the preprint: 🔗 💻 Code available on GitHub: 🔗 #AI #DrugDiscovery #mRNA #LNP #SyntheticBiology 🙏 A huge team effort behind this work, with special appreciation to Bowen LI for driving the project. Kudos to Haotian Cui, Yue Xu, Kuan Pang, Gen Li, and Bettycat567!

Bo Wang

27,590 views • 1 year ago