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UK startup Oviva, which sells a digital support offering, including for Type 2 diabetes treatment, dispensing personalized diet and lifestyle advice via apps to allow more people to be able to access support, has closed $80 million in Series C funding — bringing its total raised to date to $115M.
The raise, which Oviva says will be used to scale up after a “fantastic year” of growth for the health tech business, is co-led by Sofina and Temasek, alongside existing investors AlbionVC, Earlybird, Eight Roads Ventures, F-Prime Capital, MTIP, plus several angels.
Underpinning that growth is the fact wealthy Western nations continue to see rising rates of obesity and other health conditions like Type 2 diabetes (which can be linked to poor diet and lack of exercise). While more attention is generally being paid to the notion of preventative — rather than reactive — healthcare, to manage the rising costs of service delivery.
Lifestyle management to help control weight and linked health conditions (like diabetes) is where Oviva comes in: It’s built a blended support offering that combines personalized care (provided by healthcare professionals) with digital tools for patients that help them do things like track what they’re eating, access support and chart their progress towards individual health goals.
It can point to 23 peer-reviewed publications to back up its approach — saying key results show an average of 6.8% weight loss at 6 months for those living with obesity; while, in its specialist programs, it says 53% of patients achieve remission of their type 2 diabetes at 12 months.
Oviva typically sells its digitally delivered support programs direct to health insurance companies (or publicly funded health services) — who then provide (or refer) the service to their customers/patients. Its programs are currently available in the UK, Germany, Switzerland and France — but expanding access is one of the goals for the Series C.
“We will expand to European markets where the health system reimburses the diet and lifestyle change we offer, especially those with specific pathways for digital reimbursement,” Oviva tells TechCrunch. “Encouragingly, more healthcare systems have been opening up specific routes for such digital reimbursement, e.g., Germany for DiGAs or Belgium just in the last months.”
So far, the startup has treated 200,000 people but the addressable market is clearly huge — not least as European populations age — with Oviva suggesting more than 300 million people live with “health challenges” that are either triggered by poor diet or can be optimised through personalised dietary changes. Moreover, it suggests, only “a small fraction” is currently being offered digital care.
To date, Oviva has built up 5,000+ partnerships with health systems, insurers and doctors as it looks to push for further scale by making its technology more accessible to a wider range of people. In the past year it says it’s “more than doubled” both people treated and revenue earned.
Its goal is for the Series C funding is to reach “millions” of people across Europe who need support because they’re suffering from poor health linked to diet and lifestyle.
As part of the scale up plan it will also be growing its team to 800 by the end of 2022, it adds.
On digital vs face-to-face care — setting aside the potential cost savings associated with digital delivery — it says studies show the “most striking outcome benefits” are around uptake and completion rates, noting: “We have consistently shown uptake rates above 70% and high completion rates of around 80%, even in groups considered harder to reach such as working age populations or minority ethnic groups. This compares to uptake and completion rates of less than 50% for most face-to-face services.”
Asked about competition, Oviva names Liva Healthcare and Second Nature as its closest competitors in the region.
“WW (formally Weight Watchers) also competes with a digital solution in some markets where they can access reimbursement,” it adds. “There are many others that try to access this group with new methods, but are not reimbursed or are wellness solutions. Noom competes as a solution for self-paying consumers in Europe, as many other apps. But, in our view, that is a separate market from the reimbursed medical one.”
As well as using the Series C funding to bolster its presence in existing markets and target and scale into new ones, Oviva says it may look to further grow the business via M&A opportunities.
“In expanding to new countries, we are open to both building new organisations from the ground up or acquiring existing businesses with a strong medical network where we see that our technology can be leveraged for better patient care and value creation,” it told us on that.
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You’ve just sat down to dinner, and your wearable device reminds you to get up and get in your steps for the day. Maybe the app has a point, but odds are, you’ll push the notification to the side. The founders of Sweetch, an Israeli company creating its own AI-driven behavior change app, are betting that if you got that notification in a different way, you’ll be more likely to take its advice.
Yossi Bahagon, the founder of Sweetch, describes the company’s approach to digital reminders as a mixture of artificial intelligence and emotional intelligence. The app will use AI to analyse “lifeprint” data picked up through a smartphone. Then it delivers messages to when you might be more likely to respond to them and in a “tone of voice” that encourages compliance.
For instance if you have meetings on Mondays between 12 and 3, but still want to get in some exercise, Sweetch won’t suggest getting a workout in during those times, or shame you for sitting through a meeting rather than getting a run in.
“It’s about ongoing hyper-personalized engagement that increases the likelihood of the patient doing what he or she needs to do,” says Bahagon.
On Monday, Sweetch announced a $20 million Series A round led by Entreé Capital. Other investors include Noaber, Kortex Ventures, Insurtech VC, Fin TLV Ventures, and existing investors Philips, OurCrowd, and Qure Ventures.
Bahagon is a family physician by training, but he’s spent the majority of his career in the digital health arena. In 2008 Bagahon founded the digital health division of Clalit Health Services, a non-profit insurance and medical services provider that currently insures 60 percent of the Israeli population. His previous company, Luminox Health, was acquired by Israeli investor platform OurCrowd in 2016, and Bahagon stayed on to manage the fund’s digital health arm.
Sweetch, which was founded in 2013, is yet another digital health venture for Bahagon – this time aimed at increased patient compliance. The app has already generated some interest, and was one of five apps selected from over 400 to participate in the Bayer G4A program, something like an accelerator developed by the pharmaceutical giant.
So far, Sweetch CEO Yoni Nevo says the app has “tens of thousands of users,” (the company would not provide a specific number).
It’s currently being used in patients with cardiovascular diseases, diabetes, obesity, hypertension, rheumatoid arthritis, inflammatory bowel disease, and, in a bit of a departure from the rest: breast cancer treatment.
Sweetch isn’t designed for users to download at will on the app store (you can download it, but won’t get far without an access code); their go-to market strategy is instead to partner with healthcare organizations, pharma companies, payers or providers. Then providers might prescribe Sweetch alongside the actual treatment to encourage them to stick with it.
There is evidence that people don’t always follow doctors’ orders – particularly when it comes to chronic conditions. One 2017 report from the CDC notes that one in five prescriptions written in the United States are never filled, and up to 50 percent of medicines were taken incorrectly (at the wrong time, wrong dose, etc).
Improving patient compliance, though, is a more complicated problem. The CDC report outlined a few solutions – some of which have more to do with the healthcare system than they do with health tech. Those include lowering economic barriers to medication, increasing team-based healthcare (your pharmacist and doctor coordinating prescription refills, for instance), and increasing access to healthcare in the first place.
The report does highlight an avenue for health information technology to help address the non-compliance problem (it specifically mentions e-prescribing software).
Tech, like Sweetch, can only address the non-compliance problem in medicine if it doesn’t have a non-compliance problem of its own. To that end, Bahagon says the app has a record of user retention. “Even after 24 months, we still see around 45% of the patients that started using the system continue to use it,” he says.
User retention is a good sign for any app developer. But in the health space, it’s more complicated. Some studies suggest that consumer ratings are poor markers of how well these apps work to improve outcomes (you might like an app and use it, but it doesn’t make you any healthier).
In that regard, Sweetch does have a trial under its belt, conducted at two sites in the Johns Hopkins Clinical Research Network.
The app was tested on 55 adults with prediabetes over the course of three months. Forty-seven of the participants finished the trial, and on average, they increased their physical activity by an average of 2.8 MET-hours (they may have actually exercised for shorter periods, but their intensity was the equivalent of 2.8 hours of work), and lost about 1.6 kilograms.
The users also lowered their A1c levels, a key measure of average blood sugar. Prediabetic adults usually have an A1c between 5.7 and 6.5 percent, and those in this trial reduced their A1c levels by about .1 percent (the study refers to that reduction as “clinically meaningful.”)
This study didn’t specifically compare Sweetch to any other prediabetes interventions. However, a study on that is upcoming. In a December 2020 interview, Bahagon noted that Sweetch had received a grant from the National Institutes of Health to continue testing Sweetch against other “gold standard” interventions for diabetes.
Nevo and Bahagon didn’t provide concrete updates on the project, but noted that “in a month or so” the company may announce updates on the NIH funding and upcoming randomized controlled trials.
In the meantime, the company plans to use the Series A funding to expand into markets in the US and Brazil, grow the user base, and enhance the platform to provide specific and tailored recommendations for even more conditions.
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Which disease results in the highest total economic burden per annum? If you guessed diabetes, cancer, heart disease or even obesity, you guessed wrong. Reaching a mammoth financial burden of $966 billion in 2019, the cost of rare diseases far outpaced diabetes ($327 billion), cancer ($174 billion), heart disease ($214 billion) and other chronic diseases.
Cognitive intelligence, or cognitive computing solutions, blend artificial intelligence technologies like neural networks, machine learning, and natural language processing, and are able to mimic human intelligence.
It’s not surprising that rare diseases didn’t come to mind. By definition, a rare disease affects fewer than 200,000 people. However, collectively, there are thousands of rare diseases and those affect around 400 million people worldwide. About half of rare disease patients are children, and the typical patient, young or old, weather a diagnostic odyssey lasting five years or more during which they undergo countless tests and see numerous specialists before ultimately receiving a diagnosis.
No longer a moonshot challenge
Shortening that diagnostic odyssey and reducing the associated costs was, until recently, a moonshot challenge, but is now within reach. About 80% of rare diseases are genetic, and technology and AI advances are combining to make genetic testing widely accessible.
Whole-genome sequencing, an advanced genetic test that allows us to examine the entire human DNA, now costs under $1,000, and market leader Illumina is targeting a $100 genome in the near future.
The remaining challenge is interpreting that data in the context of human health, which is not a trivial challenge. The typical human contains 5 million unique genetic variants and of those we need to identify a single disease-causing variant. Recent advances in cognitive AI allow us to interrogate a person’s whole genome sequence and identify disease-causing mechanisms automatically, augmenting human capacity.
A shift from narrow to cognitive AI
The path to a broadly usable AI solution required a paradigm shift from narrow to broader machine learning models. Scientists interpreting genomic data review thousands of data points, collected from different sources, in different formats.
An analysis of a human genome can take as long as eight hours, and there are only a few thousand qualified scientists worldwide. When we reach the $100 genome, analysts are expecting 50 million-60 million people will have their DNA sequenced every year. How will we analyze the data generated in the context of their health? That’s where cognitive intelligence comes in.
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In general, obesity is linked with a large range of health problems—for most people, at least. But for a substantial minority of those who are overweight, obesity is accompanied by indications of decent health, with no signs of impending diabetes or cardiovascular disease. These cases have probably received unwarranted attention; who doesn’t want to convince themselves that they’re an exception to an unfortunate rule, after all? But the phenomenon is real, and it’s worth understanding.
To that end, a large international team of researchers has looked into whether some of these cases might be the product of genetic influences. And simply by using existing data, the team found 61 instances where a location in our genomes is associated with both elevated obesity and signs of good health, cardiovascular or otherwise.
Good and bad
The team’s method of searching the genome is remarkably straightforward, and it relies on the fact that many research groups have already done so much work to look for factors associated with obesity, diabetes, and cardiovascular health. This work includes searching for areas of the genome associated with measures of obesity, like body mass index, body fat percentage, and waist-to-hip ratio. Insulin and glucose levels have also been studied genetically, as these numbers give some indication of how the body is responding to weight and food intake. Cardiovascular health measures, including things like cholesterol, triglyceride levels, and blood pressure, have also been explored.
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