OUR FIRST PRODUCT

Fully Biodegradable Seed Coating Polymer

Our coating protects seeds, improves handling, and supports the controlled delivery of nutrients or crop-protection agents during germination. Designed to perform during planting and then break down naturally in the soil, they offer a sustainable alternative to persistent fossil-based coating materials.

“Developed to meet the demands of seed coaters, farmers and regulators without compromising performance”

Impending restrictions on persistent microplastics within the EU are driving demand for high-performing biodegradable alternatives. Using ArtemisAI and precision strain engineering, Danu develops PHAs with tunable properties, reliable processing, and targeted functionality. These materials give seed coaters application-ready solutions, support farmer performance, and provide regulators with a fully biodegradable alternative to fossil-based polymers.

OUR TECHNOLOGY

Engineering Living Systems
To Create Precision Biopolymers

We combine computational biology, AI, and strain engineering to develop biopolymers with tunable properties and predictable performance

Computational Biology

We transform large-scale omics data into mechanistic, genome-scale models that reveal how microbial metabolism can be engineered to accelerate and optimize biopolymer production.

ArtemisAI

Our proprietary platform, Artemis AI, then combines these mechanistic models with machine learning to predict the microbial designs and production conditions needed to create biopolymers with tailored properties.

Strain Engineering

We construct these designs in the laboratory by engineering microbial strains to produce specific polymer compositions, structures, and performance characteristics.

ArtemisAI

Combining the structure of biology with the power of AI for faster, more reliable strain development with less data.

ArtemisAI combines the structured, mechanistic understanding of mechanistic models with the predictive power of artificial intelligence. By embedding biological knowledge directly into its neural network, ArtemisAI learns more effectively from limited data, enabling faster, more reliable strain development with fewer experiments.