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Design of natural fungicide

Tackling Saprolegnia in Salmon Farming Through Intelligent Molecular Discovery

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Roberto IbanezChief Technology OfficerPublished: August 2025

The Challenge

Saprolegnia, a devastating aquatic pathogen, poses a critical threat to salmon aquaculture worldwide. This fungal-like organism causes severe infections, leading to significant fish mortality and economic losses for farmers. Traditional treatments often rely on harsh chemicals that can harm both the fish and the surrounding ecosystem, creating an urgent need for natural, selective, and effective solutions.

Our Solution: A Four-Step Approach

  1. AI-Assisted Literature Mining: Our intelligent agents rapidly analyze vast databases of scientific publications, extracting relevant knowledge from decades of research in minutes rather than months. This comprehensive foundation ensures no critical insights are overlooked.
  2. Differential Molecular Analysis: Our Technology performs detailed genomic comparisons between the Saprolegnia pathogen and salmon hosts, identifying unique targets present only in the pathogen. This precision targeting ensures treatments are highly selective, eliminating the pathogen while keeping salmon completely safe.
  3. Virtual Molecular Screening: Our Technology simulates millions of plant-derived molecules, predicting their effectiveness against the identified targets. This digital approach dramatically accelerates the discovery process while reducing costs.
  4. Optimal Plant Source Selection: Based on the most promising molecular candidates, our Technology recommends specific plants with the highest concentrations of active compounds, optimizing extract potency and commercial viability.

The Game-Changer: Iterative Digital Screening

The true power of our Technology lies in iterative digital screening, a continuous learning cycle that makes each subsequent search exponentially more intelligent and precise.

How It Works

Instead of a single screening event, our Technology launches multiple rounds of virtual discovery, with each result teaching the system to identify better candidates. Every data point becomes a stepping stone to greater accuracy and effectiveness.

The Learning Journey

  • Round 1: Initial Discovery (Result: 20,000 ppm)
    • First digital screening identifies broad candidate pool
    • Laboratory validation provides crucial baseline data
    • AI begins learning molecular success patterns
  • Round 2: Focused Refinement (Result: 12,000 ppm)
    • AI eliminates thousands of low-potential candidates
    • Screening becomes highly targeted based on previous learnings
    • 37.5% improvement in extract effectiveness
  • Round 3: Precision Breakthrough (Result: 500 ppm)
    • AI identifies complex molecular synergies
    • Ultra-precise candidate selection
    • Massive 97.5% reduction in required concentration
    • 40x more potent than initial formulation

Reduction in Required Concentration (ppm)

Each iteration reduced the dosage required for effective treatment.

Measurable Impact

  • 40x increase in treatment potency
  • 97.5% reduction in required dosage
  • Months of research compressed into weeks
  • 100% natural solution

The Future of Natural Product Discovery

This Saprolegnia project demonstrates how artificial intelligence is revolutionizing biotechnology. By combining computational power with biological expertise, we've created a system that learns, adapts, and continuously improves, delivering solutions that would be impossible through traditional methods.

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