Le Cong@Stanford, AI+Bio+Gene-Editing

Future of running agentic research from any coding environment, congratulations on the release @phylo_bio @KexinHuang5 @YuanhaoQ

Excited to share AutoScreen—our AI co-scientist for target discovery that changes how we can work with CRISPR screen, human genetics and genomics data, benchmarked on >320 wet-lab screens and enabled a “AutoScreen AI hub” with AI-extracted insights from >500 datasets across BioGrid CRISPR database, EMBL expression atlas, and UK Biobank GWAS studies.

The multi-agent AI can automate design and analysis of target discovery. We validated 3 novel genes that help cancer cells evade immune attack, using previously unpublished, fresh CRISPR screens across melanoma, leukemia, and colon cancer models. AI predictions → real experiments, closing the loop for discovering novel drug target and insights at scale.

This work started by @YuanhaoQ in collaboration with @MengdiWang10 @jure groups, esp @KexinHuang5 now both at @phylo_bio building scientific AI system. With talented members Xuefeng, Xiaotong Wang, Meitong Chen, Xiao Luo, Luna Lyu, Ravi Dinesh, Ming Yin, amazing collaborator including @hcwww_ from Aviv Regev group. Special thanks to our team who drove the wet-lab validation and took this work further into finding cancer immune targets that may one day turn into life-saving drugs.

We are recruiting talents to build models and agentic AI with real lab verifier and discovery impacts to life and medicine, come join us!!!

Preprint: biorxiv.org/content/10.648…

Blog from Phylo: phylo.bio/blog/autoscreen

When would we have “live streaming” of life science / scientific lab work? Perhaps live streaming a Brain implant surgery from @neuralink could be the closest thing? It would be fun to live stream a CRISPR experiment some day but parental DNA test in live session may have more viewers. These you can see something happening within days hopefully. @elonmusk @djseo

Thrilled to release two new preprints on intelligent labs for driving science and innovation. This is in close coordination with Aviv Regev, Jian Ma (@jmuiuc), Michelle Lee (@michellearning), and the teams at @Genentech, @SCSatCMU, and @Princeton University.

In our perspective, we argue that the next generation of labs should be human-in-the-lead and AI-empowered, integrating human intent, machine reasoning, and physical experimentation through scientific world models and an agentic harnessing layer.

Done responsibly, these systems have the potential to make scientific discovery more programmable, reproducible, adaptive, and scalable while enabling scientists to focus on higher-level scientific reasoning and discovery.

It's been a privilege to pursue this Perspective with @MengdiWang10 and an outstanding group of scientists and innovators advancing the intersection of computation, AI, science, and medicine. We're excited to continue exploring where this vision leads.

Our preprint: preprints.org/manuscript/202…
Preprint led by Jian and Aviv team: preprints.org/manuscript/202…

This also kicks off a new Gladstone-Stanford AI Hub efforts, led by Katie Pollard at @GladstoneInst and myself, with an amazing team of scientists including Emma Lundberg (@Prof_Lundberg), Brian L Trippe (@brianltrippe ), Anshul Kundaje (@anshulkundaje ), Barbara Engelhardt (@BeEngelhardt), Christina Theodoris (@TheodorisLab), Catherine Tcheandjieu (@ines_catherine), Bruce Conklin, Alexander Marson, Stacie Dodgson (@StacieDodgson), Seth Shipman (@seth_shipman), Vijay Ramani, Danielle Swaney (@dlswaney), and Nevan Krogan. Excited to be building together across two great institutions!

Heading to SIGGRAPH for the first time! Thanks so much to organizers for inviting me to this cool Graphics4Science workshop next week.