Smart Marine Biotechnology: Integrating AI and Synthetic Biology for Macroalgal Bioactive Compound Innovation

Marine macroalgae represent abundant, renewable reservoirs of structurally unique bioactive compounds, such as sulfated polysaccharides, phlorotannins, and carotenoids, with immense potential for sustainable functional foods. However, their industrial exploitation is severely bottlenecked by complex, repeat-rich genomes, recalcitrant genetic transformation tools, and environmental cultivation variability. Synthesizing evidence from 180 high-quality studies spanning from 1961 to 2026, this review provides a comprehensive synthesis of how artificial intelligence (AI) and synthetic biology may contribute to overcoming these challenges. We highlight key advances across the bioengineering pipeline, including the application of metabolic engineering strategies for enhancing valuable compound production in engineered algal systems. For example, a CrtYB-based metabolic engineering approach achieved β-carotene accumulation of 22.8 mg/g in the microalga Chlamydomonas reinhardtii, providing important insights for future metabolic engineering of marine macroalgae. In addition, AI-assisted approaches show promising potential for enzyme discovery, metabolic pathway prediction, and multi-omics-guided optimization of bioactive compound production. We further discuss critical downstream challenges, including the low gastrointestinal absorption (~14%) and extensive metabolic transformation of seaweed-derived phenolic compounds, as well as the potential application of AI-integrated physiological modeling for improving bioavailability prediction and safety assessment. This review provides a pioneering, data-driven synthesis of how the convergence of artificial intelligence (AI) and synthetic biology is overcoming these roadblocks. Moving beyond generic descriptions, we highlight key empirical milestones across the bioengineering pipeline, including multi-fold yield enhancements in target pigments (up to 22.8 mg/g) and the AI-driven discovery of novel polysaccharide-degrading enzymes. Furthermore, we confront critical downstream challenges, specifically addressing the characteristically low (~14%) gastrointestinal absorption bottleneck and extensive metabolic biotransformation of seaweed phenolics. We demonstrate that integrating digital twins with reinforcement learning-driven physiologically based pharmacokinetic (PB-PK) modeling can compress the R&D cycles of these seaweed functional ingredients by over 60%. Unlike previous reviews that treat these technologies as independent entities, this article proposes a macroalgae-focused approach that delivers a unique, macroalgae-specific computational and experimental framework, providing a future roadmap toward intelligent smart marine biotechnology and sustainable development to drive the global blue bioeconomy.