Parasites can cause major economic and social impacts worldwide in both humans and animals. High levels of infestation can lead to detrimental effects on their host, leading to undesired outcomes including loss of condition, reduced performance, poor welfare and increased risk of disease and illness. In order to suppress parasite infection and transmission, novel techniques and drugs must constantly be explored to expand our knowledge and reduce the spread and infection of parasites both in animals and humans.
There are several different procedures to ascertain vital information on parasite infestation in humans and animals. The gold standard technique of faecal egg counting is frequently employed to quantify the number of parasite eggs within a pre-processed sample using a microscope, allowing both veterinarians and farmers to know the extent of infestation on a individual and herd basis and provide suitable treatment programmes.
Increasing levels of anthelmintic resistance is constantly being reported across multiple anthelmintics in current practise. The ability to accurately index parasite motility is key when exploring new potential drugs to fight against and reduce anthelmintic resistance. Therefore, we are at a critical stage where we must continue to explore novel drugs to slow down this rate of resistance.
Automating both these processes will not only increase speed of diagnosis and drug discovery pipelines, but also improve overall accuracy and validity of experiments, resulting in greater chance of reproducibility. Therefore, automating both faecal egg counting, and parasite motility will:
- Reduce current day limitations
- Facilitate to reduce anthelmintic resistance
- Increase accuracy and reproducibility
In response, Agxio have created Chiron, an automated image and video classification software with built in pre-determined models and configurable parameters. Chiron can automatically identify and quantify the number of eggs present, automating the current gold standard technique. It will also automatically index parasite motility by detecting and analysing movement between frames, and labelling each video with a motility index value. The results obtained will be extracted and generated into a simple report for quick interpretation of your parasite samples which are stored and easily retrieved from an online library database.