From digital discovery to pilot-scale production

AIMARIA follows an integrated Design–Build–Test–Learn (DBTL) approach, linking computational discovery with biological engineering, experimental validation and sustainable manufacturing.

Scientific approach

1. AI-guided discovery and digital twins

Marine genomic and metagenomic resources are analysed to identify novel biosynthetic gene clusters and enzymes. AI models support functional prediction, target prioritisation and cultivation strategies. The AIMARIA digital twin integrates computational and experimental information to guide subsequent research decisions.

2. Predictive DNA design and pathway engineering

Selected biosynthetic pathways are captured, reconstructed and refactored using advanced DNA assembly and synthetic biology. AI-guided design of regulatory and coding sequences supports expression optimisation in different biological production hosts.

3. Cell-based and cell-free expression

Engineered microbial chassis and cell-free protein synthesis platforms are used to evaluate biosynthetic pathways, enzymes and compounds. These complementary systems enable experimental validation and identification of production bottlenecks.

4. Biological production and validation

The project pursues two application directions: sustainable production of selected high-value marine natural products and discovery of previously uncharacterised bioactive compounds and enzymes. Experimental outcomes feed back into the computational and engineering platforms.

Environmental, economic and responsible-innovation considerations are integrated throughout the development process.

Work packages

AIMARIA is organised into seven interconnected work packages.

WP1 — Project management & governance

Lead: NTNU

Coordinates scientific, administrative and financial management, consortium governance, quality assurance, risk management and research data management.

WP2 — Foundational AI-driven discovery & design platforms

Lead: Wageningen University

Maps marine biosynthetic diversity and develops AI models for enzyme and BGC prioritisation, cultivation prediction and digital-twin-guided biological design.

WP3 — Synthetic biology & expression platforms

Lead: Imperial College London

Develops BGC capture, long-DNA assembly, AI-guided pathway refactoring, engineered microbial hosts and cell-free expression platforms for functional validation.

WP4 — Sustainable supply of high-value marine natural products

Lead: ETH Zürich

Develops heterologous production routes for selected high-value marine compounds, particularly Peloruside A and Pateamine A or an agreed alternative, including pathway optimisation, scale-up and downstream processing.

WP5 — Technology-driven discovery & validation of novel marine bioactives

Lead: Helmholtz Centre for Infection Research

Discovers and validates novel marine bioactive compounds and enzymes through BGC prioritisation, pathway expression, chemical characterisation and biological activity screening.

WP6 — Sustainability, circular bioeconomy & socio-economic impact

Lead: NTNU

Evaluates environmental and economic impacts through life cycle and techno-economic assessment, while addressing circularity, regulatory requirements and responsible use of marine genetic resources.

WP7 — Exploitation, communication & public engagement

Lead: NTNU

Coordinates communication and dissemination, stakeholder engagement, intellectual property and exploitation strategies, training and public dialogue.

An integrated research programme

WP2 and WP3 establish the computational and experimental platforms, while WP4 and WP5 apply them to sustainable production and novel bioactive discovery. WP1, WP6 and WP7 provide the management, sustainability and exploitation framework across the project.

Experimental findings, production measurements and sustainability assessments will inform subsequent design decisions, enabling the platform to improve throughout the project.