Lunit said that Lunit Insight, its artificial intelligence-based imaging analysis solution, has obtained Class 2 Medical Device approval from Health Canada.
With the approval, Lunit will be able to market Lunit INSIGHT CXR, a chest X-ray image analysis solution, and Lunit INSIGHT MMG, a mammography image analysis solution.
The Canadian approval follows the company receiving approval for the Lunit Insight product from the U.S. Food and Drug Administration in November. As the company has now obtained approval in the U.S. and Canada, it is ready to enter the North American market, the world's largest pharmaceutical and medical device market, Lunit said.
The Canadian medical device market is the eighth largest worldwide, growing rapidly with an aging population. According to Statistics Canada, Canadians 65 and older will increase from about 17 percent of the total population in 2019 to about 23 percent in 2031.
Accordingly, the agency said that the size of the Canadian medical device market will grow from about $7.2 billion in 2019 to $9.2 billion in 2024, with an annual average growth of 4.6 percent.
"With the approval of the Lunit Insight product in Canada, we will target the entire North American market, including the U.S., in earnest," Lunit CEO Suh Beom-seok said. "Lunit Insight is a product that provides an opportunity for patients to receive fast and accurate treatment and improves convenience for medical staff."
Suh added that as the product has already received recognition in the global market, the company would strive to enter the North American market successfully.
Lunit Insight CXR is a product that diagnoses 10 types of chest diseases, including pulmonary nodules, pulmonary sclerosis, and pneumothorax, based on AI. It helps medical professionals read quickly and accurately by finding the suspected disease area and the degree of suspicion in the chest X-ray image with an accuracy of 97 to 99 percent.
Lunit Insight MMG is a product that detects the presence of breast cancer in mammography images based on AI. It detects the suspected breast cancer site with 96 percent accuracy. In addition, it assists medical workers in diagnosis by indicating the location information of the suspected area and the degree of suspicion with numerical values.