PharmGen Science Initiates Development of Improved New Drug 'RD1401' Through Industry-Academic Cooperation with Seoul National University

Published 19 Jul.2023 09:18(KST)

Pamgen Science announced on the 19th that it has achieved results by concluding the 'AI and Big Data-based Bio New Drug Discovery Outsourcing Research' project, which it has been conducting with the Seoul National University Joint Institute of Biotechnology since 2021, and starting the development of one improved new drug as a combination therapy for dyslipidemia.

Hee-Deok Park, CEO of PharmGen Science, Dae-Hee Hwang, Professor at Seoul National University, and Hye-Yeon Kim, CEO of PharmGen Science (from left), are posing for a commemorative photo at the project completion report meeting for the "Contract Research on Bio New Drug Discovery Using Artificial Intelligence (AI) and Big Data."
[Photo by PharmGen Science]

Pamgen Science recently held a project completion report meeting with Seoul National University, where Professor Dahee Hwang (Director of the Bioinformatics Research Center) presented the results of developing disease treatments through big data analysis, and Professor Sun Kim (Bioinformatics and Life Information Laboratory, Department of Computer Science) presented the results of developing a disease treatment prediction system using big data deep learning.

Through this research, Professor Hwang studied various improved new drugs such as combination therapies for diabetes and liver diseases, achieving the milestone of initiating the development of the dyslipidemia combination drug 'RD1401.' He secured a cohort of 180,000 metabolic disease patients from Seoul National University Hospital and developed analytical methods to establish the medical statistical validity of RD1401, successfully deriving the final improved new drug project for dyslipidemia.

Professor Kim also showed excellent results with two papers in progress, one patent application filed, and one national project selected. He integrated public big data into a database (DB) and developed network analysis and deep learning models based on big data. Through this, he plans to publish one paper on a framework for discovering new drug and drug repositioning candidate substances and another on an AI framework for predicting drug combinations in leading journals in the relevant fields.

Additionally, a patent application for drug combination prediction technology based on a biomedical knowledge graph is underway jointly with Seoul National University. Furthermore, Pamgen Science was selected for a national project by the Korea Pharmaceutical and Bio-Pharma Manufacturers Association for 'Discovery of effective substances for synthetic new drugs for autoimmune diseases using AI' and has conducted related research.

A Pamgen Science representative stated, “We believe this joint research has great significance as it has led to the derivation and initiation of development of an improved new drug project through industry-academia cooperation between the two institutions.” He added, “Since there are no previous cases of applying AI to improved new drug development, we expect that the results of this research can be applied beyond the current patient-based clinical case methods to enable faster and more diverse high value-added improved new drug development.”