Imagine using a super-smart computer to design tiny biological tools that act like precision scissors for plants. These tools help turn wood fibers into a clear, flexible plastic-like wrap that actually disappears in nature. It's like upgrading a traditional factory with a digital brain to make eco-friendly packaging cheaper and faster to produce.
Current fossil-based flexible packaging is environmentally damaging, while existing bio-based alternatives are often too expensive or lack the performance needed for industrial use.
An end-to-end optimisation suite combining AI and machine learning to design enzymes and produce high-performance regenerated cellulose films.
If you are a packaging manufacturer dealing with high costs of bio-plastics — this project developed an AI-optimized production suite that lowers costs to compete with fossil-based films. It ensures your products meet the new Packaging and Packaging Waste Regulation. This allows for a transition to compostable materials without losing performance.
If you are an enzyme producer dealing with slow and expensive protein design cycles — this project developed Bayesian optimisation and machine learning tools that accelerate enzyme design. This reduces the production costs of novel enzymes used in cellulose regeneration. It enables faster time-to-market for bio-catalysts.
If you are a supplier dealing with regulatory pressure to eliminate non-recyclable plastics — this project developed high-performance regenerated cellulose films. These materials are designed for full biodegradability and recyclability. This ensures compliance with EU environmental laws while maintaining packaging strength.
The project uses an end-to-end optimisation suite targeting a significant cost reduction compared with current fossil-based packaging films.
The strategy includes an initial flagship facility output of 28 kt per year, with subsequent plants scaling up to 50 kt per year.
Based on available project data, the exploitation strategy focuses on the commercial deployment of digital tools and packaging products by 2032.
Yes, it is specifically designed to comply with all regulatory requirements, including the new Packaging and Packaging Waste Regulation.
The exploitation strategy envisages commercial deployment by 2032.
The consortium is heavily industry-weighted with 8 industrial partners (53% ratio), including 6 SMEs, which indicates a strong focus on commercialization rather than pure research. With 15 partners across 9 countries and additional advisory input from Japan and India, the project has the global reach and technical breadth to move from AI design to industrial-scale manufacturing.
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