The planned initial public offering of two South Korean biotech startups – JLK Inspection and Syntekabio – is raising expectations about broader applications of artificial intelligence in the local healthcare sector to spread up the process of drug discovery and design.
The two are due to go public this month. JLK Inspection has developed a platform of 37 AI-based solutions applicable to support doctors’ decision in the diagnosis on medical imaging modalities including MRI, CT and X-ray.
Syntekabio has a track record of identifying a promising molecule just in six months after CJ Healthcare had tried in vain for two years. The firm has also an AI-powered platform to discover biomarkers, which are unique characteristics that can be used to identify patients who are more likely to respond to a specific treatment. Traditional screening of candidate molecules requires human involvement and thus is slow. Syntekabio is dedicated to a platform to look for biomarkers in oncology and nervous system treatments. The company`s cancer drug biomarker discovery platform accumulates big data on the reactivity of 265 cancer drugs and candidate molecules, as well as 1,001 cancer cell line genomes of 331 cancer types.
JLK Inspection has clustered its 37 AI solutions to read medical images of 14 body parts under brand platform AIHuB. The platform includes: AI medical system that provides analytical services by combining various medical devices, AI quantitative analysis platform that provides quantitative analysis results for input images, AI remote platform to provide analysis services for a remote diagnosis platform, and AI medical diagnosis platform for patient diagnosis by connecting hospital systems.
The company’s UNISTRO designed to help diagnose and treat stroke provides a lifecycle analysis from the time a patient arrives to the emergency room to treatment, discharge and rehabilitation based on 1.4 million medical images and 100,000 clinical records from 14,000 patients. It also sells UNIPROS, which analyzes cases of prostate cancer based on MRI images, which leads to digital pathology.
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