ISSUE FOCUS FEED & ADDITIVE MAGAZINE August 2025 45 has traditionally been a monumental task. Today, a suite of advanced technologies allows researchers to screen, analyze, and validate these compounds with unprecedented speed and precision. The first leap forward has been High-Throughput Screening (HTS), which uses automated platforms to rapidly test thousands of plant extracts against specific pathogens or on fish cell lines. This technology quickly narrows the vast library of natural compounds to a manageable number of promising candidates for in-depth study. While HTS tells us if a compound works, a suite of "omics" technologies (genomics, transcriptomics, proteomics, and metabolomics) tells us how it works. This multi-faceted approach provides a holistic view of a compound's biological impact at the molecular level. Together, these technologies create a detailed map of a compound's journey through the fish's system, confirming its efficacy and ensuring its safety. THE COMING RISE OF AI AND MACHINE LEARNING The most transformative advance will be the full integration of Artificial Intelligence (AI) and machine learning into the research pipeline. AI algorithms will analyze the chemical structures of thousands of phytochemicals and predict their bioactivity before they ever enter a lab. By training on vast datasets from past HTS and 'omics' studies, these models will identify novel candidates with a high probability of success, saving immense resources. Furthermore, AI will be instrumental in making sense of the complex data generated by 'omics' research. Machine learning will pinpoint subtle patterns in gene expression or metabolic changes that would be invisible to the human eye, linking specific compounds to enhanced immune function or improved gut health. This predictive power will revolutionize the discovery pipeline, moving it from a process of trial-and-error to one of intelligent design. HOW AI WILL REVOLUTIONIZE ADDITIVE DISCOVERY The scaling of phytogenic research, supercharged by Artificial Intelligence, will trigger a profound and lasting transformation in global aquaculture. AI will fundamentally change not just the speed, but the very nature of how new additives are discovered, developed, and deployed. This shift will move the industry from a reactive to a predictive model of animal health and sustainability, built on four key pillars of innovation. 1. Predictive Discovery: From Haystack to Pinpoint The traditional method of finding new additives relies on physically screening thousands of ShutterStock | 572515873
RkJQdWJsaXNoZXIy MTUxNjkxNQ==