HoneyNaps has officially registered as a Contract Research Organization (CRO) with the Korea National Enterprise for Clinical Trials (KoNECT). The registration marks a significant milestone in the company's expansion into AI-driven sleep data analytics for clinical trials and reinforces its commitment to supporting global pharmaceutical, medical device, and digital health companies with high-quality, standardized sleep analysis services.
Building on this milestone, HoneyNaps is expanding commercialisation of SOMNUM Clinical, its AI-powered clinical trial analytics service. Powered by SOMNUM AI, the company's sleep analysis solution that has received two US FDA clearances, SOMNUM Clinical automatically analyses polysomnography (PSG) data and provides quantitative assessment of key sleep parameters, including sleep stages, apnea-hypopnea index (AHI), arousal events, and other clinically relevant sleep metrics.
HoneyNaps combines its AI technology with extensive clinical research expertise, having supported clinical studies involving more than 10,000 participants and managed nationwide multicenter and multidisciplinary clinical trials. This integrated capability enables the company to deliver both advanced AI analytics and comprehensive clinical trial support for global research programs.
According to Dataintelo's Clinical Sleep Health Market report, the global clinical sleep health market is projected to grow from approximately $22.8 billion in 2025 to $36.9 billion by 2034. Sleep is increasingly recognised not only as a critical endpoint for sleep disorders such as insomnia and obstructive sleep apnea, but also as an important digital biomarker in clinical research involving obesity, cardiovascular disease, neurodegenerative disorders, mental health, and other therapeutic areas.
SOMNUM Clinical addresses one of the major operational challenges in sleep-related clinical trials by automating the traditionally labour-intensive analysis of polysomnography data. The platform can reduce analysis time by more than 90%, significantly improving trial efficiency while accelerating study timelines.
