ISSUE FOCUS 46 FEED & ADDITIVE MAGAZINE August 2025 compounds, a costly and inefficient process. AI will completely invert this model. By leveraging machine learning algorithms trained on massive chemical and biological datasets, researchers will perform in silico (computational) screening of millions of molecules. These models will predict a compound's potential efficacy, safety, and even its mechanism of action based on its chemical structure alone. This will change the form of discovery from a brute-force physical search to a highly targeted computational one. The impact will be a dramatic acceleration of the R&D pipeline; AI will identify a shortlist of high-potential candidates in weeks, a task that once took years, allowing research efforts and resources to be focused only on the most promising options. 2. Deciphering Biological Mechanisms at Scale Understanding how an additive works will be crucial for optimizing its use. AI's ability to integrate and analyze enormous, multi-layered 'omics' datasets will provide a panoramic view of an additive's biological impact. Instead of studying a single pathway, AI will map the entire systemic response of a fish to a phytogenic compound. This will change the form of research from isolated analysis to holistic systems biology. The impact will be the ability to design additives with surgical precision. For example, AI will identify a compound that not only inhibits a pathogen but also specifically upregulates the genes for mucus production in the gut lining, creating a dual-action solution. This deep mechanistic insight will lead to more reliable, potent, and predictable products. 3. Engineering Intelligent Synergistic Solutions The most effective natural solutions will be complex mixtures, not single ingredients. While human formulators are limited in the number of combinations they can test, AI will explore a virtually infinite design space. Machine learning algorithms will analyze millions of potential interactions between different phytogenics, probiotics, prebiotics, and enzymes to design "intelligent blends" with synergistic effects. This will shift the form of product development from simple mixing to computational engineering of complex formulas. The impact will be the creation of multi-targeted additives that offer holistic benefits—for instance, a single product that is simultaneously antimicrobial, anti-inflammatory, and a gut microbiome modulator. These AI-designed solutions will be far more powerful and cost-effective than their individual components. 4. Digital Twins and Virtual Trials One of the biggest bottlenecks in additive development is the reliance on lengthy and expensive animal trials. AI will offer a revolutionary alternative: The creation of "digital twins". These will be sophisticated virtual models of a fish or an entire aquaculture system, built from biological data. Researchers will use these digital twins to conduct Photo: Freepik
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