Our People
A closed-loop system for programmable biology. Each cycle generates proprietary training data, making the next cycle better.
Novel compact RNA-guided nucleases, ~40% divergent from natural proteins, with up to ~3x the activity of existing compact editors in human cells.
bioRxiv, 2026
Cell Reports Methods, 2024
How the ACE design search ran on NVIDIA GPUs, where BioNeMo fits, and why working editors per GPU hour is the number we track.
Integrating frontier AI capabilities with the Acrobat platform to accelerate the development of genetic medicines for rare disease.
Successful Phase I completion in the DARPA Rapid Inhibitor Discovery and Development pipeLine (RIDDL) program and advancement to expanded Phase II research.
Multi-year award supporting application of the Acrobat platform to protein engineering in neurodegeneration.
Joint program applying spatial transcriptomic profiling to disease-localized target identification in interstitial lung disease.
We're always looking for exceptional scientists and engineers to join our team. If teaching AI the language of biology excites you, we'd love to hear how you'd contribute.
Get in touch
