Hanmi Pharm uses AI platform to advance obesity drug candidate into clinical trials

Hanmi Pharm has developed AI-driven next-generation drug development technology and presented its findings at a major US academic conference.

The company has derived a novel obesity drug candidate, HM17321, which it describes as the world's first to simultaneously achieve weight loss and muscle gain, and has advanced it into clinical development. Unlike existing treatments that merely offset muscle loss, HM17321 is designed to increase muscle mass while selectively reducing fat — a first-in-class approach in obesity medicine. A Phase 1 trial is currently underway in the United States.

Hanmi Pharm also secured what it calls the world's first peptide-based myostatin-inhibiting next-generation muscle-enhancement treatment candidate, HM500197. The compound was unveiled at the American Diabetes Association annual meeting last June.

Both achievements were made possible through the company's proprietary AI platform, HARP-pSAR, which predicts pharmacological activity based on subtle changes in protein sequences and proposes optimal directions for drug candidate design.

"HARP-pSAR overcomes the biggest bottleneck in early-stage drug development — the lack of experimental data — and maximizes research efficiency," the company said. Unlike conventional AI models that require large datasets and high-performance computing infrastructure, the platform uses quantization technology to reduce computational costs and is designed to run without interruption even in standalone environments, it added.

The company also built a model capable of predicting activity against both target and off-target receptors using only dozens of internal experimental results, enabling ultra-high-speed screening to identify promising drug candidates based on AI predictions.

Hanmi Pharm presented these findings in a poster session at the Intelligent Systems for Molecular Biology (ISMB) 2026 conference, held July 16 (local time) in Washington, D.C. ISMB is the world's largest academic conference in bioinformatics and computational biology, and leads global research trends in AI-driven biology and drug development.

"This demonstrated that AI can go beyond being a simple data analysis tool and serve as a genuine research partner — one that combines with researchers' expertise to suggest directions for drug candidate design and reduce trial and error throughout the development process," the company said.