A Glasgow-based medical technology company has secured nearly £650,000 in funding to advance artificial intelligence solutions that could revolutionise the diagnosis and treatment of childhood sleep apnoea. Seluna, co-founded by Dr Scott Black and Dr Yola Jones, is launching a major clinical validation study with the Royal Hospital for Children in Glasgow to address what experts describe as a critical gap in paediatric healthcare.
The funding round, led by Gabriel Investment Syndicate with participation from Scottish Enterprise, University of Strathclyde, and new investor STAC Invest, supports a 500-patient NHS validation study running through the end of 2025. The research aims to validate Seluna’s Software as a Medical Device (SaMD), which uses machine learning algorithms to automatically interpret complex sleep study data traditionally requiring manual analysis by specialists.
Addressing a Global Healthcare Crisis
Childhood sleep apnoea affects an estimated 96 million children worldwide, with approximately 80% remaining undiagnosed according to company data. The condition, characterised by repeated interruptions in breathing during sleep, can lead to serious health complications including growth failure, cognitive impairment, and cardiovascular problems if left untreated.
Dr Scott Black, CEO and co-founder of Seluna, emphasised the urgency of the problem: “Paediatric sleep diagnostics has been underserved for too long. It’s a complex challenge, which is why existing tools weren’t built for children – until now”. Black, who completed his doctorate in medical devices at the University of Strathclyde, founded the company in 2022 after conducting market research across multiple UK hospitals.
The current diagnostic pathway relies heavily on polysomnography (PSG), considered the gold standard for sleep disorder diagnosis. However, this approach presents significant challenges in paediatric settings due to its invasive nature, high cost, and the specialised interpretation required. Manual scoring of sleep studies creates substantial bottlenecks in an already strained healthcare system.
Explainable AI for Clinical Trust
Seluna’s technology distinguishes itself through its focus on explainable artificial intelligence, designed to support rather than replace clinical judgement. The system identifies and classifies digital biomarkers from sleep study data, providing interpretable results that clinicians can understand and trust.
Dr Ruth Hamilton, Consultant Clinical Scientist at the Royal Hospital for Children and principal investigator for the study, highlighted this crucial aspect: “What makes Seluna’s approach so compelling is its focus on explainable AI. As clinicians, we need to understand why the technology is making certain recommendations. Seluna’s focus on interpretability builds the trust we need to confidently use this technology in clinical practice”.
The AI system aims to streamline diagnostic workflows, reduce clinical workload, and provide more objective, data-driven decision-making capabilities. Beyond diagnosis, Seluna’s technology seeks to uncover underlying pathological patterns that could guide more precise, personalised treatment decisions.
Clinical Impact and Treatment Challenges
The validation study addresses significant treatment challenges in paediatric sleep medicine. Dr Haytham Kubba, Paediatric Ear, Nose & Throat Surgeon at the Royal Hospital for Children and chief investigator, explained the current dilemma: “Adenotonsillectomy for sleep apnoea is the most common paediatric surgery for the most common reason but right now, we simply don’t know if we’re operating on the right children”.
Adenotonsillectomy, the surgical removal of tonsils and adenoids, remains the primary treatment for childhood sleep apnoea. However, clinicians currently lack sufficient physiological insights to predict which children will benefit from surgery, leading to some unnecessary operations while other children who might benefit are overlooked.
Recent research has shown that many children, particularly those who are obese or have underlying medical conditions, continue to experience sleep apnoea symptoms after adenotonsillectomy. Alternative treatments include continuous positive airway pressure (CPAP) therapy, nasal steroids, and weight management programmes, though patient adherence remains challenging.
Market Opportunity and Healthcare Economics
The global sleep apnoea devices market represents a substantial commercial opportunity, valued at approximately $6.33 billion in 2024 and projected to reach $12.11 billion by 2034, growing at a compound annual growth rate of 6.7%. The paediatric segment remains underserved compared to adult markets, presenting significant growth potential for specialised solutions.
UK data suggests up to 4 million people have moderate or severe obstructive sleep apnoea with symptoms, while an additional 6 million have mild forms of the condition. The economic burden of undiagnosed sleep apnoea is substantial, with studies indicating undiagnosed patients cost the NHS twice as much as those receiving treatment.
Angus Macfadyen, head of investment at STAC, noted the commercial potential: “With 80% of childhood sleep apnoea cases going undiagnosed worldwide and 96 million children affected by sleep disorders, there’s a compelling commercial opportunity for a solution that delivers better patient outcomes while reducing healthcare costs”.
Regulatory Pathway and International Expansion
The Glasgow validation study represents the first phase of a broader multi-site programme, with additional NHS centres expected to join by year-end. This multi-centre approach is designed to capture diverse population data reflecting wider UK demographics, helping to minimise bias in model development and ensure equitable access across communities.
Seluna targets UK Class I medical device classification by the end of 2026, enabling adoption across NHS and private healthcare settings. The company subsequently plans to pursue FDA Class II approval in the United States by 2027, supporting international expansion.
The regulatory pathway for AI-powered medical devices has evolved significantly, with recent guidance emphasising the importance of explainable algorithms and clinical validation. Seluna’s focus on interpretable AI aligns with these regulatory trends, potentially facilitating smoother approval processes.
Industry Context and Technological Advances
Seluna’s development coincides with broader advances in paediatric sleep medicine technology. Recent studies have demonstrated promising results for AI-based sleep staging, with some algorithms achieving accuracy rates comparable to human experts. However, challenges remain in paediatric applications, particularly for younger children and those with complex medical conditions.
The Royal Hospital for Children is simultaneously participating in other innovative sleep technology trials, including wireless wearable biosensors for real-time breathing analysis in infants. These parallel developments reflect growing recognition of the need for paediatric-specific sleep monitoring solutions.
The investment in Seluna represents part of a broader trend in healthcare technology focusing on underserved paediatric markets. Anne Henderson, Head of Investment at the University of Strathclyde, commented: “We are committed to addressing societal challenges through innovation, and Seluna is an excellent example of how cutting-edge research and technology can be used to transform paediatric healthcare”.
