LG Chem Advances AI Drug Development and Patient Selection

LG Chem plans to apply AI across its drug development decisions, from discovering drug candidates to selecting patients for clinical trials. Based on biomarkers, the company intends to identify patients suited to clinical trials and improve precision. The company will also apply AI to a personalized mRNA cancer vaccine, aiming to enter clinical development in 2029 after preclinical work next year. LG Chem also plans to expand cooperation with global AI bio companies.

LG Chem announced on the 21st that it held the '2026 LG AI Bio Conference' on the 20th at the ISC building of LG Science Park in Gangseo-gu, Seoul, together with LG AI Research and Flagship Pioneering, a US biotech venture capital firm. The event, held for the first time to build a domestic AI bio innovation ecosystem and expand global cooperation, drew more than 140 domestic and foreign company representatives to discuss the direction of AI-based drug development and industry innovation. In precision oncology, LG Chem plans to use AI to select patients and design treatment strategies that account for the complex biological characteristics of tumors. Biomarkers are biological indicators that reveal disease status or treatment response.

Son Ji-woong, head of LG Chem's Life Sciences Business Unit, said in his opening remarks that AI is evolving from a drug development tool into a core engine that determines competitiveness. He said future competitiveness lies not only in finding structurally excellent drugs but in using AI to identify patients likely to benefit most. LG Chem is building and refining an AI model that predicts individual neoantigens and aims to improve the precision of cancer treatment by finding treatment targets suited to each patient.

At the conference, Andre Andonian, Asia-Pacific chairman of Flagship Pioneering, mentioned expanding AI-driven life sciences collaboration and cited the cases of Moderna and Lila Sciences. Wang Zhu, global business development head at Insilico Medicine, presented a case in which a candidate discovered with generative AI entered clinical stage. Ryan Leng, life sciences product head at Lila Sciences, introduced the concept of an autonomous laboratory in which AI agents repeatedly design, synthesize, experiment and learn. The panel discussed strategies for selecting patient groups using cancer whole-genome data and for discovering biomarkers and selecting patients with spatial biology-based AI.

LG Chem plans to apply AI across its drug development decisions, from discovering drug candidates to selecting patients for clinical trials. Based on biomarkers, the company intends to identify patients suited to clinical trials and improve precision. The company will also apply AI to a personalized mRNA cancer vaccine, aiming to enter clinical development in 2029 after preclinical work next year. LG Chem also plans to expand cooperation with global AI bio companies.

LG Chem announced on the 21st that it held the '2026 LG AI Bio Conference' on the 20th at the ISC building of LG Science Park in Gangseo-gu, Seoul, together with LG AI Research and Flagship Pioneering, a US biotech venture capital firm. The event, held for the first time to build a domestic AI bio innovation ecosystem and expand global cooperation, drew more than 140 domestic and foreign company representatives to discuss the direction of AI-based drug development and industry innovation. In precision oncology, LG Chem plans to use AI to select patients and design treatment strategies that account for the complex biological characteristics of tumors. Biomarkers are biological indicators that reveal disease status or treatment response.

Son Ji-woong, head of LG Chem's Life Sciences Business Unit, said in his opening remarks that AI is evolving from a drug development tool into a core engine that determines competitiveness. He said future competitiveness lies not only in finding structurally excellent drugs but in using AI to identify patients likely to benefit most. LG Chem is building and refining an AI model that predicts individual neoantigens and aims to improve the precision of cancer treatment by finding treatment targets suited to each patient.

At the conference, Andre Andonian, Asia-Pacific chairman of Flagship Pioneering, mentioned expanding AI-driven life sciences collaboration and cited the cases of Moderna and Lila Sciences. Wang Zhu, global business development head at Insilico Medicine, presented a case in which a candidate discovered with generative AI entered clinical stage. Ryan Leng, life sciences product head at Lila Sciences, introduced the concept of an autonomous laboratory in which AI agents repeatedly design, synthesize, experiment and learn. The panel discussed strategies for selecting patient groups using cancer whole-genome data and for discovering biomarkers and selecting patients with spatial biology-based AI.