Acurable<\/a> has gained FDA clearance for a novel wireless diagnostic device for remote detection of obstructive sleep apnea (OSA). A formal launch into the U.S. market is slated to follow this summer. Its wearable is already being used by a number of hospitals in the U.K. (where it launched in 2021) and in the European Union, after obtaining local regulatory clearances in the region.<\/p>\nThe startup, which was founded back in 2016, is the brainchild of Imperial College professor Esther Rodriguez-Villegas, director of the university\u2019s Wearable Technologies Lab, who spent some 1.5 decades conducting research into using acoustic sensing for tracking respiratory biomarkers to diagnose cardiorespiratory conditions \u2014 work that underpins the commercial hardware.<\/p>\n
The London-based startup raised an \u20ac11 million Series A round (~$11.8 million) back in October with its eye on the U.S. launch. Prior to that it received \u00a31.8 million (~$2.2 million) across three different grants from Innovate U.K., a national body which supports product commercialization. Private investors in the medtech startup include Madrid-based Alma Mundi Ventures, London\u2019s Kindred Capital and KHP Ventures, a healthcare-focused venture fund also in the U.K. which is a collaboration between two NHS Hospital Trusts (King\u2019s College and Guy\u2019s and St Thomas\u2019) and King\u2019s College London.<\/p>\n
OSA refers to a chronic respiratory condition characterized by pauses in breathing caused by the person\u2019s upper airway being obstructed during sleep. It\u2019s thought to affect a small percentage of adults \u2014 around 1.5 million adults in the U.K.; and some 25 million in the U.S. (with many more people affected across the world) \u2014 and while not immediately life-threatening it can be linked to<\/span> serious health implications since it can contribute to conditions such as cardiovascular disease, diabetes, dementia and even heart attacks, making treatment or management important.\u00a0<\/span><\/p>\nHealthcare services often struggle to manage chronic conditions, given the expense of long term monitoring. But Rodriguez-Villegas explains that in the case of sleep apnea there is even a challenge for healthcare services to diagnose the condition \u2014 since traditional polysomnography tests are inconvenient and\/or costly. (The patient is either asked to sleep overnight at a special center, where they\u2019re fitted out with a bunch of wired sensors. Or else they are trained how to fit the various electrodes themselves at home, with the associated risk that the test will have to be repeated if sensors are incorrectly fitted or get detached during sleep.)<\/p>\n
Acurable\u2019s tiny, self-applied wearable has been designed to offer a far more patient-friendly (and cost effective way) for diagnosis of the condition \u2014 allowing for the testing to be both remote (in patients\u2019 homes) and super simple so patients can self-administer it.<\/p>\n
One early adopter of Acurable\u2019s product \u2014 Dr Michael Harrison, a professor of surgery and pediatrics at the Children\u2019s Hospital at UCSF \u2014 offers strong praise, writing in a supporting statement that the device has been \u201cgame-changing for our patients, as it is a much simpler and comfortable experience\u201d, as well as talking up how it \u201cenables clinicians to conduct multiple night studies at a time, improving patient outcomes by giving them a much speedier diagnosis\u201d.<\/p>\n
For her part, Rodriguez-Villegas says she saw a role for developing technologies to solve problems with a significant social impact by addressing healthcare bottlenecks associated with chronic (and often under-diagnosed) respiratory conditions, starting with sleep apnea. So the plan is for her startup to bring more wearables to market in future, for other respiratory conditions, such as COPD and asthma \u2014 all based on the core acoustic sensing IP developed for the first device.<\/p>\n
\u201cWhat I realised early on was that [chronic cardiorespiratory conditions] will not be something that could be solved if we continue with [traditional healthcare] processes \u2014 that it\u2019s not a matter of pumping money into the system. Because there is also human resources. So you need the clinicians, the nurses, you need to understanding. So that\u2019s where my journey started with tech,\u201d she tells TechCrunch. \u201cDeciding how do we create techs that can solve the bottlenecks and make patients\u2019 lives better?\u201d<\/p>\n
While core research underpinning the product has taken well over a decade, designing, prototyping and building the actual product took around six or seven years, according to Rodriguez-Villegas \u2014 so working on things like miniaturizing the hardware and designing a UX with high accessibility so it\u2019s easy for patients of all ages (and tech abilities) to use which she says was a huge priority for her.<\/p>\n
\u201cThe app is designed so that there is no room for a stress or failure,\u201d she says, explaining how she pushed her design team to avoid assuming users would know how to navigate traditional software menu structures. \u201cI had had to have lots of conversations with my UI people in the beginning because they couldn\u2019t understand where I was coming from.\u201d<\/p>\n
<\/p>\n
A patient self-administering the AcuPebble with guidance from the app. Photo Credits:<\/strong> Acurable<\/p>\n<\/div>\nAs for the hardware, the startup\u2019s one-shot sensing device, which is called the AcuPebble, looks a bit like a coffee pod that\u2019s been colored an Apple-esque shade of shiny white. So sleek and minimalist looking is it that it resembles some kind of consumer device, rather than a medical instrument, with no utility grey plastic or scary bundles of cables in sight.<\/p>\n
This purist look is entirely by design \u2014 reflecting Acurable\u2019s overarching mission to rethink a convoluted diagnostic bottleneck using sensor-driven automation.<\/p>\n
Patients use the AcuPebble at home where it\u2019s worn overnight stuck to the the skin of their neck (using a patented adhesive). It\u2019s also a single-use medical device \u2014 gathering and uploading enough data across one night\u2019s tracking of the sleeper\u2019s breathing to produce a diagnosis. (So to borrow another piece of Apple lore, you could say it\u2019s designed to \u2018just work\u2019.)<\/p>\n
The kit works by using tiny, high performance piezoelectric MEMS microphones to \u2014 in simple terms \u2014 listen to the patients breathing as they sleep. Although Rodriguez-Villegas is guarded with the exact details of how it works, saying the product is only partially patented so protecting IP remains a concern.<\/p>\n
Acoustic sensing as a diagnostic tool in healthcare is of course nothing new \u2014 just think of the stethoscope. But what\u2019s novel here is the understanding of the sonic landscape associated with cardiorespiratory conditions that Acurable has been able to develop through years of research to isolate relevant biomarkers.<\/p>\n
\u201cThe hardware is designed to detect particular biomarkers we are looking for and those biomarkers are very different to the conventional ones. And how do we know this? It\u2019s again because it\u2019s been almost two decades in the making,\u201d says Rodriguez-Villegas.<\/p>\n
The data the device captures is uploaded the cloud where it\u2019s processed by Acurable whose algorithms produce an automated diagnosis which is sent to (human) clinicians for review. So much of the research which underpins the hardware was focused on understanding the specific \u2018signal in the noise\u2019 of the human body by winnowing down noisy human biology into the respiratory biomarkers of interest for diagnosing the particular cardiorespiratory conditions it\u2019s focusing on.<\/p>\n
The algorithms it\u2019s using for diagnosis of sleep apnea are not machine learning or any other form of artificial intelligence. Nor is its approach data driven, per Rodriguez-Villegas, who emphasizes it\u2019s using algorithms that are \u201cfully traceable\u201d. Although she does not entirely rule out using AI in the future \u2014 but is categorical that AI is unnecessary for this product and, indeed, that explainability in healthcare is an essential component; that there must be no black boxes for medical diagnostics.<\/p>\n
\u201cIn this product \u2014 and the product in the market now \u2014 there is no AI. This is physiological signal processing based on very unique physiological modelling that we are experts on,\u201d she says. \u201cEverything in the algorithms happens for a known reason so the algorithms are fully traceable\u2026 Again, this is based on the research that we did in respiration for many years. That led us to that. It is not data driven. It\u2019s really not data driven. I cannot really tell you exactly what it is. Because that\u2019s part of the computational IP.<\/p>\n
\u201cBut I do understand that everybody nowadays because AI is in everybody\u2019s mind it\u2019s almost like that is the default thought, right, that things are AI or they are data driven. No, no. We know why every single thing is happening. So in the same way, as you might know, you know, why your heart beats and [the steps in the cardiac cycle that take place around that] this is gonna be like that.\u201d<\/p>\n