Precision RNA Therapeutics Through AI
The AI-native compiler for RNA medicines
AI-Powered RNA Design Platform
Modular Design Architecture
Mix and match components for optimal performance
Rapid Iteration
Design and optimize RNA constructs in seconds, not months
Predictive Analytics
Machine learning models predict efficacy across contexts
Auditable and Instant Sequence Design
Standard Generative Technologies
Scale != Function
Performance is coupled to scaling up data, compute
Rigid Architectures
Slow to adapt to new biological contexts of platforms
Rising Compute Costs
GARDN Generation Platform
Data-efficient
High performance generation with small datasets
Instant Inference
Delivers auditable, interpretable designs in nanoseconds
Simplifies Design and Assembly
Programmable Molecular Platform
Building RNA 2.0
Encode Biological Intent Directly Into Sequence
We translate protein, structural, and microRNA signals into modular control units
Assemble Complete Constructs
The GARDN AI engine compiles these modules into optimized mRNA vectors
Deliver Precise Function
Cell-type specific expression, extended duration, reduced immunogenicity
All compatible with standard linear mRNA and LNP manufacturing
About Us
At GARDN, we merge deep learning with synthetic biology to make RNA design predictable and instant. Our models learn directly from transcriptomic and structural data, capturing the complex relationships that govern translation, stability, and immunogenicity. This allows us to generate complete, optimized mRNA constructs tailored to specific cells, cargos, and therapeutic goals.
We’re building the compiler for programmable biology—transforming how RNA-based treatments are conceived, developed, and brought to patients.
Our Science
Publications
Complete Messenger RNA Design
bioRxiv (2025) — Read paper →
Programmable RNA Switch Generation
Nature Communications (2025) — Read paper →
Contact Us
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