AI for Animal Health
We worked with Vaxxinova on a solution for analyzing and classifying the parasite that causes avian coccidiosis using Artificial Intelligence.
Case Context
Avian coccidiosis is one of the most economically impactful diseases in poultry farming, causing global industry losses of over $14.3 billion each year.
It is caused by seven species of the protozoan from the Eimeria genus, which infect birds through oocysts—small, resistant organisms that spread in the environment and can be ingested by birds.
Vaxxinova’s role is to provide solutions for the prevention and control of avian coccidiosis through vaccines. This production requires strict controls and processes, including the analysis of coccidiosis oocysts.
Project Challenges
The analysis of each sample is quite complex. It requires counting and classifying the oocysts and identifying the Eimeria species to determine the appropriate control strategy.
The process is time-consuming, demands a high level of expertise, and is prone to errors, which can compromise the accuracy of the analysis.
- Complex analysis
- Manually performed
- Prone to errors
Developed Solution
In partnership with Vaxxinova, we developed an advanced Artificial Intelligence model with Computer Vision to perform the analysis and counting of oocysts.
The model identifies patterns and is capable of detecting, classifying, and quantifying the oocysts. It can differentiate between:
- Sporulated (infectious) and non-sporulated (non-infectious) oocysts.
- Eimeria species, identifying the seven species responsible for avian coccidiosis - something the human eye cannot visually distinguish.
With each new sample, the model learns more and becomes even more accurate.
Technologies Used
Results
Testimonials
The project with Venturus was innovative in an area previously seen as unfeasible or requiring complex and costly solutions.
Even without prior experience in animal health, Venturus’ technological expertise, combined with our technical knowledge, allowed us to develop a high-value solution.
Beyond the practical results, this collaboration paves the way for future innovations, strengthening the transformative potential in our field.
The partnership between the two companies was essential to the success of this project, which brought innovation and improvements to our production process.
We developed a fast and accurate method with high applicability, representing a significant advancement in the field.
The solution offers possibilities for use in various future contexts, reinforcing the strategic value of the collaboration and opening doors for new applications.