Latest news: AI in medical devices

Women’s healthcare company Cercle has raised $6m in seed funding to advance its AI-driven health data platform.  

Cercle’s platform uses AI to organise large amounts of de-identified healthcare data, currently focusing on fertility.  

Since its inception in November 2023, the platform – dubbed the Cercle Biomedical Graph – has been used by US Fertility, Boston IVF, and Eurofins Genoma.  

According to the company, the platform is consistent with US Food and Drug Administration (FDA) guidelines and maintains data privacy and security under HIPAA standards. 

San Francisco-headquartered Cercle said the funding will be used to support expansion beyond the fertility market, develop the platform, and enhance its large language model (LLM) capabilities. The company aims to broaden its customer base across a range of women’s healthcare spaces, including menopause, women’s oncology, and rare diseases that disproportionately impact women. 

The $6m seed round was led by the Outsiders Fund, with additional participation from FemHealth Ventures, CGHealth Ventures and Rogue Women’s Fund. It also received investment from former Meta executive Sheryl Sandberg and her husband Tom Bernthal’s venture fund, which led Cercle’s $4.2m pre-seed round when it launched in November 2023.  

The space that has become popularly known as “femtech” encompasses software and services that use technology tailored towards women's health. The industry has historically seen a lack of innovation and funding due to low awareness and investment. 

However, awareness and investment in this space are on the rise. Investment in women’s health increased by 350% between 2020 and 2023, highlighting the growing interest in the market in recent years. In February 2024, the US White House and Dr Jill Biden released $100m in federal funding towards women’s health as part of the White House Initiative on women’s health research.  

Cercle’s chief operations officer Ashley Finch said: “Women’s healthcare is under-researched, underfunded, and underserved. Our mission at Cercle is simple and clear: to leverage the power of AI to generate insights from women’s health data to drive efficiencies for providers, develop drugs faster, and improve care for patients.” 

According to a report on GlobalData’s Medical Intelligence Center, AI in the medical market was worth $336m in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 29.1% to $1.2bn by 2027. 

The US Food and Drug Administration (FDA) has granted 510(k) clearance for Avicenna.AI’s CINA-CSpine tool. 

This AI solution is developed to automatically detect and prioritise life-threatening conditions, assess them for severity, and seamlessly notify clinicians. 

CINA-CSpine is engineered to aid in the detection and triage of cervical spine fractures from computed tomography (CT) images. 

These fractures, often resulting from traumatic injuries, can lead to severe neurological damage or paralysis if not treated promptly. The tool's purpose is to enhance outcomes and reduce long-term complications by accelerating the detection process and facilitating timely treatment. 

The AI tool works by flagging suspected positive findings that are compatible with acute cervical spine fractures, thereby alerting radiologists with their existing systems. 

Avicenna.AI co-founder and CEO Cyril Di Grandi said: “Cervical spine fractures are serious injuries that require prompt and appropriate medical attention, especially if the spinal cord is involved, so accurate diagnosis is essential. 

“With CINA-CSpine, we aim to help reduce the delay between scan and interpretation, which is critical in the treatment of this condition.” 

Avicenna.AI’s CINA-CSpine was validated using more than 300 non-contrast CT scans from the US and Europe, taken from 36 different scanner models across five vendors. 

It demonstrated overall sensitivity and specificity of 90.3% and 91.9%, respectively. 

In June 2024, Avicenna.AI received 510(k) clearance from the FDA for its AI tool CINA-VCF, which is designed to detect vertical compression fractures. 

Avicenna.AI's portfolio features seven other AI tools, including solutions for the prevention and detection of intracranial haemorrhage, pulmonary embolism, vertical compression fractures, and the ASPECT Score for stroke severity quantification. 

San Francisco start-up SoundHealth has launched an artificial intelligence (AI) powered app to enable allergy sufferers to get ahead of an attack. 

Dubbed SONUcast, the application predicts a user’s susceptibility to allergies based on the dimensions of a person’s nasal cavity and sinuses. It also uses patented AI algorithms to scan a user’s face and produce a real-time, personalised forecast of their allergy symptoms based on their location by using real-time meteorological data to warn a user of the likelihood of an impending allergic reaction to air-based particulates such as pollen. 

The app uses the company’s Sonuband device which the company states is the world's first US Food and Drug Administration (FDA) approved device for the treatment of nasal allergies. The device uses acoustic resonance therapy to force open airways to allow for better breathing and treat the symptoms of allergic rhinitis, including nasal congestion, rhinorrhoea and nasal itching. 

Paramesh Gopi, founder and CEO of SoundHealth, said: “Existing apps use an imprecise, one-size-fits-all approach. Our breakthrough AI and deep clinical science personalise predictions based on an individual's facial structure – and are poised to transform patient care by empowering patients to take control of their allergies. With the SONU band and SONUCast, SoundHealth enables patients to potentially avoid allergy attacks with therapy that is FDA-approved and as effective as nasal steroids for the treatment of rhinitis.” 

The company says that Sonucast has been trained on data from thousands of human subjects and hundreds of CT scans, making it the first-ever AI to be used for allergy forecasting and acoustic resonance therapy (ART). The company also claims that a randomised controlled trial of its Sonuband device resulted in 80% of users seeing significant clinical improvement over two weeks. 

Jayakar Nayak, associate professor of otolaryngology at Stanford Otolaryngology-Head and Neck Surgery, said: “Our nasal anatomy is the silent architect of respiratory health in many individuals, and can dictate how we respond to environmental triggers. SoundHealth’s SONUCast represents a major step forward for patients as it can empower them to more effectively predict and therefore manage their nasal allergies. The data and clinical science behind SONUCast are quite groundbreaking and may set a new standard for both prediction and treatment of nasal congestion due to allergies.” 

Elsewhere in the field of allergy treatment, French company Crossject has secured €6.9m in funding to advance the development of ZENEO Epinephrine, its prefilled needle-free platform and treatment for severe allergic reactions. Meanwhile, AliveDx has obtained the European In Vitro Diagnostic Device Regulation (IVDR) CE mark for its microarray immunoassay in allergy diagnostics. 

Researchers at Kings College London have built an AI model that can accurately predict who is at a high risk of developing sight-threatening diabetic retinopathy (DR) up to three years in advance. 

Diabetes patients aged 12 and older in the UK are asked to attend an annual eye check, which tests for DR. Called the NHS Diabetic Eye Screening Program (DESP), approximately 3.2 million people are screened each year, and it costs the health service £85m per year in England, according to the announcement. 

Image data from the UK’s National Health Service (NHS) was used to develop the tool, which can predict if someone is at low or high risk of developing sight-threatening DR in one year, two years or three years using images from the back of the eye. 

To develop the new AI tool, researchers utilised over a million retinal images from diabetes patients in the Southeast London DESP. The model’s accuracy was validated using a dataset of 70,000 images from the INSIGHT health data research hub. 

INSIGHT is an NHS-led initiative housing retinal images linked to clinical data. The images are routinely collected from patients in Moorfields Eye Hospital and University Hospitals Birmingham NHS Foundation Trust. The dataset includes contributions from over 200,000 patients enrolled in the Birmingham, Solihull and Black Country DESP, the largest urban screening programme in Europe. 

The NHS said that if implemented, this AI-based technique could reduce the screening burden for people at low risk of vision loss, while ensuring individuals at a high risk of vision loss are seen urgently, saving the NHS millions of pounds, and thousands of appointments every year. 

The research team now plans to conduct a prospective clinical trial to assess if the AI model is safe, efficacious, and cost-effective for use within DESP. The trial – which aims to include data from over 50,000 diabetes patients – could provide evidence to support the implementation of predictive AI in the NHS DESP. 

In the announcement accompanying the study, Pearse Keane, director of INSIGHT and professor of artificial medical intelligence at UCL’s Institute of Ophthalmology, said: “This is an exciting use case for the value of curated NHS eye data in research for the benefit of patients and the wider healthcare system. Although there are AI models that can detect the presence of diabetic eye disease with the accuracy of a retinal specialist, this new model breaks ground in predicting the risk of developing sight-threatening diabetic eye disease up to three years in the future.”