Hanmi Pharmaceutical announced that it has confirmed the effectiveness of obesity improvement by increasing muscle mass while reducing fat in a preclinical study conducted to predict the clinical response and side effects of the obesity treatment candidate 'HM17321' under development.
On the 5th, Hanmi Pharmaceutical reported that it presented these research results at a poster session during the bioinformatics academic conference 'ISMB/ECCB 2025' held in Liverpool, England, from the 20th to the 24th of last month.
This is the result of a machine learning-based analysis study that predicts the possibility of the efficacy of HM17321, confirmed in mouse experiments, being reproduced in humans by integrating animal protein omics data and human-derived bio big data.
HM17321 is a urocalcitonin (UCN)2 analogue that selectively targets the corticotropin-releasing factor (CRF)2 receptors in the brain hypothalamus, rather than incretin receptors such as glucagon-like peptide (GLP)-1. Hanmi Pharmaceutical is developing it with the goal of simultaneously achieving an increase in muscle mass and a selective reduction in fat.
According to the study, a comparison of blood proteomes from animals administered HM17321 with those from humans indicated that HM17321 induces changes similar to the proteomic characteristics of individuals with lower fat and higher lean mass.
The drug induces changes similar to those seen in the proteome of individuals who have less fat and more muscle.
The company explained that this research reaffirms the efficacy seen in existing animal experiments while demonstrating the possibility of that efficacy being realized in humans.
Choi In-young, head of the Hanmi Pharmaceutical R&D Center (executive director), noted, 'This is a significant achievement that proves the pharmacological effects of HM17321, which is approaching clinical phase 1, may be reproduced in humans.' He added, 'We will present a new paradigm of 'qualitative weight loss' that goes beyond simple weight loss to encompass muscle function and metabolic health, establishing a global standard for obesity treatment.'
Meanwhile, the clinical transition team at Hanmi Pharmaceutical's R&D Center is conducting research to predict the effects and side effects of new drug candidates by integrating the latest bioinformatics techniques and machine learning technology with multi-omics data, including genomes, transcriptomes, and proteomes obtained from both animals and humans.