LG CNS is expanding its pharmaceutical and biotech business by building an artificial intelligence (AI) drug development platform for Dong-A Socio Group. The platform integrates drug research data and connects the process from candidate discovery to validation, broadening the scope of LG CNS's AX business into core research and development areas for pharmaceutical companies.
On August 12, LG CNS announced the completion of the AI drug development platform in collaboration with its IT affiliate DAI (Dong-A Information). The platform was developed over approximately six months and supports key research processes using AI, from integrating drug research data to candidate discovery and validation. Notably, it continuously links AI prediction results with actual experimental data, enhancing the AI's predictive performance as research progresses.
Drug development typically requires extensive validation of numerous candidate substances, often taking 10 to 15 years and incurring substantial costs. LG CNS aims to quickly identify candidates with a high likelihood of success and predict their efficacy and safety in advance, thereby reducing the duration, costs, and risks associated with drug development.
LG CNS has established a seamless process that connects data collection, AI analysis, experimentation, and validation to accelerate the speed and quality of drug development. Additionally, the accumulated research data is designed to be utilized as an asset. Considering the sensitive nature of drug research data, a management system has been implemented to comply with regulatory and security requirements in the pharmaceutical industry.
Through this platform, LG CNS has integrated and standardized previously dispersed drug research data, including compound and genomic information, experimental results, academic papers, and patents. Researchers can access necessary data from a single platform and easily utilize AI analysis and prediction features with just a few clicks.
The AI platform supports key stages of drug development. In the stage of identifying disease causes, it analyzes and visualizes gene information and tissue location data at the cellular level using AI, assisting researchers in easily discovering therapeutic targets. In the candidate design phase, generative AI directly designs new molecular structures that meet specified conditions. During the validation phase, it simulates the binding potential and action stability between candidates and targets to select promising candidates, conducting virtual validations in a computer environment before actual experiments.
The platform is also designed for continuous performance improvement of the AI model. The company explained that by comparing AI prediction results with actual experimental data, it can reflect these comparisons in model retraining, thereby enhancing predictive performance as research data accumulates.
LG CNS stated that this initiative is based on its accumulated capabilities in the pharmaceutical and biotech AX sector. Previously, LG CNS participated in the Ministry of Health and Welfare's 'K-AI Drug Development Preclinical and Clinical Model Development Project (R&D)' and developed a service for annual quality assessment reports based on agentic AI for Jungkundang, among other projects in the public and private sectors.
Building on its experience in the pharmaceutical and biotech sectors and its 'Agentic Works for BIO' platform, LG CNS is expanding its AX business scope from drug research to production, quality management, and digital healthcare. In January of this year, it partnered with the Cha Bio Group to enter the digital healthcare market, working on a smart big data platform that integrates data from hospitals, pharmaceuticals, and biotech affiliates.
Lee Jae-seung, Executive Vice President of LG CNS's Cloud Business Division, stated, “We will contribute to the innovation of AI drug research and development in the domestic pharmaceutical and biotech industry through differentiated AX technologies, including agentic AI, and our specialized capabilities in this field. We will actively support our clients in enhancing their competitiveness in drug development.”
* This article has been translated by AI.
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