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Revolutionizing Drug Development: How LG CNS and Dong-A Socio Group’s AI Platform Cuts Costs and Time

HealthRevolutionizing Drug Development: How LG CNS and Dong-A Socio Group's AI Platform Cuts Costs and Time
/ LG CNS
/ LG CNS

LG CNS is set to bolster Dong-A Socio Group’s artificial intelligence (AI)-driven drug development efforts.

On Wednesday, LG CNS revealed that it has successfully established an AI Drug Development Platform in partnership with DAI, the information technology (IT) affiliate of Dong-A Socio Group.

This platform, the result of a six-month collaborative effort, integrates drug research data and supports crucial research stages from candidate compound discovery to validation. A standout feature is its capacity to enhance AI prediction accuracy as research progresses, achieved by correlating and learning from AI predictions and real experimental data.

The AI drug development platform consolidates and standardizes previously fragmented drug research data, including compound and genomic information, experimental outcomes, scientific literature, and patents. This integration enables researchers to access essential data from a single platform and leverage AI analysis and prediction tools with just a few clicks.

Traditionally, drug development has been a lengthy and costly process, typically spanning 10 to 15 years and requiring investments of 1 billion to 3 billion USD, with clinical success rates below 10%. However, industry experts anticipate that AI-driven drug development will significantly reduce timelines, costs, and failure risks, potentially revolutionizing the pharmaceutical landscape.

Lee Jae-seung, Executive Vice President of Cloud Business at LG CNS, stated that through the cutting-edge AI transformation (AX) technology, including agentic AI, and the specialized expertise in the pharmaceutical and biotech sectors, it aims to drive innovation in AI-powered drug research and development within the domestic industry. It’s committed to actively supporting our clients in enhancing their competitive edge in drug development.

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