Astaxanthin biomanufacturing under hierarchical constraints: Integrating synthetic biology and artificial intelligence for scalable production.

Hierarchical constraint management combined with AI enables scalable biomanufacturing of astaxanthin, overcoming nonlinear responses and optimization plateaus in complex biological systems.

• Why it matters: Efficient production of high-value compounds like astaxanthin is limited by biological complexity, including molecular instability and trade-offs between growth and synthesis, which hinder scalable manufacturing.
• What they did: A hierarchical, AI-assisted framework was developed, integrating protein language models, graph-based learning, neural networks, and large language models to optimize enzyme performance, metabolic pathways, and cellular states across biological scales.
• The result: This approach enhances rational design and multiscale optimization, reducing trial-and-error, and can be extended to other resource-intensive secondary metabolites with complex biosynthesis pathways.