CELLKEY AI is advancing the automation of multi-omics analysis and broader biotechnology R&D workflows using artificial intelligence and cloud-based automation technologies.

The company’s CEO, Namyong Lee, presented its approach at the 2026 SME AX (AI Transformation) Leaders Forum held at The Westin Josun Seoul, under the theme “Redesigning Bio R&D Workflows With AI.”

Lee said multi-omics, which integrates biological data such as genomics, transcriptomics and proteomics, is increasingly used in drug discovery and precision medicine.

However, he noted that the complexity of the data and a shortage of specialized personnel continue to limit analysis and interpretation. He said AI and cloud automation could help address those constraints.

To support this approach, CELLKEY AI has developed OmicsPharm, an agentic AI-based bio R&D platform. When researchers request an analysis, the platform connects them with partner institutions for data generation, then standardizes and accumulates the resulting data for use in AI-driven analysis and follow-up research.

OmicsPharm is designed to connect the research workflow from multi-omics data generation and analysis to learning, interpretation and report generation.

CELLKEY AI plans to use accumulated data to build a Sovereign Multi-Omics Foundation Model and is also developing deep-learning models to predict biomarkers and potential drug candidates.

The company is also expanding the use of AI across biopharmaceutical R&D and manufacturing processes. Its approach includes analyzing scientific literature and patent data to identify potential genomic insertion sites, while using surrogate models to simulate experimental conditions during purification processes.

CELLKEY AI is also applying AI agents to cell-image analysis, automating tasks ranging from image interpretation to the generation of quantitative reports.

Lee identified data, automation and physical AI as three key drivers of future innovation in biotechnology. He emphasized the importance of creating a continuous feedback loop in which data generated through automated experiments is used to train AI systems and improve the design of subsequent experiments.

Going forward, CELLKEY AI plans to further develop its AI-based research platform by combining multi-omics data, AI and cloud automation to improve R&D efficiency in drug discovery and precision medicine.