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The connection between the microbiome and various diseases has already been proven through numerous research results.
Recently, it is said that the microbiome and medical artificial intelligence can be combined to diagnose liver diseases at an early stage and even develop treatments for diseases such as muscle loss.
Reporter Seon-yeop Kim covered the story.
<Reporter>
Intestinal microbiome not only measures the state of intestinal health, but also reveals its relationship with various diseases such as obesity, cancer, and depression.
For this reason, cases of using the microbiome for early diagnosis of diseases and development of customized treatments are increasing significantly.
In particular, the role of artificial intelligence in learning big data is essential to properly grasp the habitat and balance of tens of trillion microbiomes in our bodies.
AIDOT, a medical AI company in Gangwon-do, which was recently designated as a special zone for precision medical big data, entered the microbiome-related business with Hallym
University Chuncheon Sacred Heart Hospital.
It started research and development of an AI microbiome solution that diagnoses liver disease early with a simple fecal test.
This is the principle of applying next-generation sequencing (NGS) to microbiome research results to identify alcoholic liver disease and applying it to AI algorithms.
[Gi-tae Suk / Professor, Department of Gastroenterology in Hallym University Chuncheon Sacred Heart Hospital: People with liver cirrhosis, hepatitis, and other liver diseases
also have characteristic findings for each disease. In diagnosing diseases, this research was conducted because it was thought that developing (AI solution) by measuring the
distribution of
the microbiome or the area of pathological strains would be helpful in diagnosing liver diseases.]
AIDOT's AI solution, which learned from the microbiome big data of 1,800 patients with liver disease, diagnoses liver disease by classifying it into four stages: normal (fatty liver),
hepatitis, cirrhosis, and liver cancer.
MRI tests that must be performed to diagnose liver disease are low in sensitivity, so invasive biopsy must be performed together. For this case, diagnosis of liver disease using AI
could overcome.
[Jae-hoon Jeong / CEO of AIDOT: We're now aiming for more than 80% sensitivity (no more risk) for finding biomarkers through microbiome and examine them through microbial
genome analysis of feces]
AIDOT plans to commercialize the solution within two years.
Bioleaders, which has started developing a treatment for geriatric sarcopenia using AI and microbiome, is also drawing attention.
The principle is to remove the substances that cause senile sarcopenia by expressing the antigenic proteins myostatin and activin on the surface of the microbiome using AI.
[ Do-young Lee / Clinical Development Center Executive Director in Bioleaders : The most important thing in developing a treatment is to know which proteins should be targeted for
senile sarcopenia to be treated the most effectively.Therefore, although there are many literature data on senile sarcopenia, but we simulated which targets are most effective
through
AI, and in the process, we concluded that targeting two proteins at the same time is the most effective, so we developed a treatment.]
As artificial intelligence is added to the microbiome, expectations for the development of diagnosis and treatment for various diseases using this source technology are growing.
17th. Dec. 2021. / Korea Economy TV / Reporter Seon-yeop Kim
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