본문 바로가기

바이오스펙테이터

기사본문

Yuhan and Syntekabio to use AI to search for anticancer substances or biomarkers

입력 2018-04-24 07:23 수정 2018-04-24 07:25

바이오스펙테이터 Jongwon Jang 기자

expecting to reduce the cost and time for drug development through a genomic big data-based AI platform

Yuhan and Syntekabio have started drug development using genomic big data and an artificial intelligence (AI) platform.

Yuhan and Syntekabio announced on the 9th of April that they have signed a memorandum of understanding (MOU), by using AI platform, to find anticancer substances, and search for biomarkers through genetic analysis of clinical trial subjects.

Syntekabio owns the platform based on deep learning technology for the purpose of predicting anticancer drug responses, and moreover, the company developed an algorithm for searching biomarkers related to drug response, by employing genomic big data and AI technology. Through this MOU, Yuhan and Syntekabio will apply AI technology, and expand its use into the entire clinical research phases, including from discovering candidate substances, to predicting drug metabolism and adverse effects.

Jung, Jongsun, a founder of Synthekabio, said “We strongly believe that AI technology and genomic big data are the two essential keys that will change the mechanism of the pharmaceutical industry, which is facing the challenge derived from the tremendous cost and time of drug development.”

Synthekabio also made an agreement last year with CJ Healthcare for immune-Oncology drug development; and recently, the company is planning to build the nation’s largest cloud-based genomic big data platform, collaborating with Naver Cloud.

Yuhan is pursuing open innovation strategy to increase the efficiency of drug development, and, as part of this, the company is expecting the MOU with Syntekabio to reduce the cost and time for drug development. A representative of Yuhan said “Through this MOU, Yuhan plans to seek substances with high anticancer activity within a short period, and find biomarkers of drugs under development, to increase the success rate of drug development and the value of new drugs.”