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June 25, 2019
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Biofourmis raises $35M to develop smarter treatments for chronic diseases

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Biofourmis, a Singapore-based startup pioneering a distinctly tech-based approach to the treatment of chronic conditions, has raised a $35 million Series B round for expansion.

The round was led by Sequoia India and MassMutual Ventures, the VC fund from Massachusetts Mutual Life Insurance Company. Other investors who put in include EDBI, the corporate investment arm of Singapore’s Economic Development Board, China-based healthcare platform Jianke and existing investors Openspace Ventures, Aviva Ventures and SGInnovate, a Singapore government initiative for deep tech startups. The round takes Biofourmis to $41.6 million raised to date, according to Crunchbase.

This isn’t your typical TechCrunch funding story.

Biofourmis CEO Kuldeep Singh Rajput moved to Singapore to start a PhD, but he dropped out to start the business with co-founder Wendou Niu in 2015 because he saw the potential to “predict disease before it happens,” he told TechCrunch in an interview.

AI-powered specialist post-discharge care

There are a number of layers to Biofourmis’ work, but essentially it uses a combination of data collected from patients and an AI-based system to customize treatments for post-discharge patients. The company is focused on a range of therapeutics, but its most advanced is cardiac, so patients who have been discharged after heart failure or other heart-related conditions.

With that segment of patients, the Biofourmis platform uses a combination of data from sensors — medical sensors rather than consumer wearables, which are worn 24/7 — and its tech to monitor patient health, detect problems ahead of time and prescribe an optimum treatment course. That information is disseminated through companion mobile apps for patients and caregivers.

Bioformis uses a mobile app as a touch point to give patients tailored care and drug prescriptions after they are discharged from hospital

That’s to say that medicine works differently on different people, so by collecting and monitoring data and crunching numbers, Biofourmis can provide the best drug to help optimize a patient’s health through what it calls a ‘digital pill.’ That’s not Matrix-style futurology, it’s more like a digital prescription that evolves based on the needs of a patient in real-time. It plans to use a network of medical delivery platforms, including Amazon-owned PillPack, to get the drugs to patients within hours.

Yes, that’s future tense because Biofourmis is waiting on FDA approval to commercialize its service. That’s expected to come by the end of this year, Singh Rajput told TechCrunch. But he’s optimistic given clinical trials, which have covered some 5,000 patients across 20 different sites.

On the tech side, Singh Rajput said Biofourmis has seen impressive results with its predictions. He cited tests in the U.S. which enabled the company to “predict heart failure 14 days in advance” with around 90 percent sensitivity. That was achieved using standard medical wearables at the cost of hundreds of dollars, rather than thousands with advanced kit such as Heartlogic from Boston Scientific — although the latter has a longer window for predictions.

The type of disruption that Biofourmis might appear to upset the applecart for pharma companies, but Singh Rajput maintains that the industry is moving towards a more qualitative approach to healthcare because it has been hard to evaluate the performance of drugs and price them accordingly.

“Today, insurance companies are blinded not having transparency on how to price drugs,” he said. “But there are already 50 drugs in the market paying based on outcomes so the market is moving in that direction.”

Outcome-based payments mean insurance firms reimburse all outcomes based on the performance of the drugs, in other words how well patients recover. The rates vary, but a lack of reduction in remission rates can see insurers lower their payouts because drugs aren’t working as well as expected.

Singh Rajput believes Biofourmis can level the playing field and added more granular transparency in terms of drug performance. He believes pharma companies are keen to show their products perform better than others, so over the long-term that’s the model Biofourmis wants to encourage.

Indeed, the confidence is such that Biofourmis intends to initially go to market via pharma companies, who will sell the package into clinics bundled with their drugs, before moving to work with insurance firms once traction is gained. While the Biofourmis is likely to be bundled with initial medication, the company will take a commission of 5-10 percent on the recommended drugs sold through its digital pill.

Biofourmis CEO and co-founder Kuldeep Singh Rajput dropped out of his PhD course to start the company in 2015

Doubling down on the US

With its new money, Biofourmis is doubling down on that imminent commercialization by relocating its headquarters to Boston. It will retain its presence in Singapore, where it has 45 people who handle software and product development, but the new U.S. office is slated to grow from 14 staff right now to up to 120 by the end of the year.

“The U.S. has been a major market focus since day one,” Singh Rajput said. “Being closer to customers and attracting the clinical data science pool is critical.”

While he praised Singapore and said the company remains committed to the country — adding EDBI to its investors is certainly a sign — he admitted that Boston, where he once studied, is a key market for finding “data scientists with core clinical capabilities.”

That expansion is not only to bring the cardio product to market, but also to prepare products to cover other therapeutics. Right now, it has six trials in place that cover pain, orthopedics and oncology. There are also plans to expand in other markets outside of the U.S, and in particular Singapore and China, where Biofourmis plans to lead on Jianke.

Not lacking in confidence, Singh Rajput told TechCrunch that the company is on course to reach a $1 billion valuation when it next raises funding, that’s estimated as 18 months away and the company isn’t saying how much it is worth today.

Singh Rajput did confirm, however, that the round was heavily oversubscribed, and that the startup rebuffed investment offers from pharma companies in order to “avoid a conflict of interest and stay neutral.”

He is also eying a future IPO, which is tentatively set for 2023 — although by then, Singh Rajput said, Biofourmis would need at least two products in the market.

There’s a long way to go before then, but this round has certainly put Biofourmis and its digital pill approach on the map within the tech industry.

These Johns Hopkins students are slashing breast cancer biopsy costs

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Over 2 million women were diagnosed with breast cancer in 2018. And while the diagnosis doesn’t have to be a death sentence for women in countries like the United States, in developing countries three times as many women die from the disease.

Breast cancer survival rates range from 80% or over in North America, Sweden and Japan to around 60% in middle-income countries and below 40% in low-income countries, according to data provided the World Health Organization.

And the WHO blames these low survival rates in less developed countries on the lack of early detection programs, which result in a higher proporation of women presenting with late-stage disease. The problem is exacerbated by a lack of adequate diagnostic technologies and treatment facilities, according to the WHO.

A group of Johns Hopkins University undergraduates believe they have found a solution. The four women, none of whom are over 21-years-old, have developed a new, low-cost, disposable core needle biopsy technology for physicians and nurses that could dramatically reduce cost and waste, thereby increasing the availability of screening technologies in emerging markets.

They’ve taken the technology they developed at Johns Hopkins University and created a new startup called Ithemba, which means “hope” in Swahili, to commercialize their device. While the company is still in its early days, the women recently won the undergraduate Lemelson-MIT Student Prize competition, and has received $60,000 in non-dilutive grant funding and a $10,000 prize associated with the Lemelson award.

Students at Johns Hopkins had been working through the problem of developing low-cost diagnostic tools for breast cancer for the past three years, spurred on by Dr. Susan Harvey, the head of Johns Hopkins Section of Breast Imaging.

While Dr. Harvey presented the problem, and several students tried to tackle it, Ithemba’s co-founders — the biomedical engineering undergrads Laura Hinson, Madeline Lee, Sophia Triantis, and Valerie Zawicki — were the first to bring a solution to market.

Ithemba co-founders Laura Hinson, Madeline Lee, Valerie Zawicki and Sophia Triantis

The 21-year-old Zawicki, who grew up in Long Beach, Calif., has a personal connection to the work the team is doing. When she was just five years old her mother was diagnosed with breast cancer, and the cost of treatment and toll it took on the family forced the family to separate. “My sister moved in with my grandparents,” Zawicki says, while her mother underwent treatment. “When I came to college I was looking for a way to make an impact in the healthcare space and was really inspired by the care my mom received.”

The same is true for Zawicki’s co-founder, Triantis.

“We have an opportunity to  solve problems that really need solving,” says Triantis, a 20-year-old undergraduate. “Breast cancer has affected so many people close to me… It is the most common cancer among women [and] the fact that women in low resource settings do not have the same standard of diagnostic care really inspired me to work on a solution.”

What the four women have made is a version of a core-needled biopsy that has a lower risk of contamination than the reusable devices that are currently on the market and is cheaper than the expensive disposable needles that are the only other option, the founders say.

We’ve designed a novel, disposable portion that attaches to the reusable device and the disposable portion has an ability to trap contaminants that would come back through the needle into the device,” says Triantis. “What we’ve created is a way to trap that and have that full portion be disposable and making the device as easy to clean as possible… with a bleach wipe.”

Ithemba’s low-cost reusable core-needle biopsy device

The company is currently in the process of doing benchtop tests on the device, and will look to file a 510K to be certified as a Class 2 medical device. Already a clinic in South Africa and a hospital in Peru are on board as early customers for the new biopsy tool.

At the heart of the new tool is a mechanism which prevents blood from being drawn back into a needle. The team argues it makes reusable needles much less susceptible to contamination and can replace the disposable needles that are too expensive for many emerging market clinics and hospitals.

Zawicki had been working on the problem for a while when Hinson, Lee, and Triantis joined up. “I joined the team when the problem was presented,” says Zawicki. “The project began with this problem that was pitched three years ago, but the four of us are really those that have brought this to life in terms of a device.”

Crucially for the team, Johns Hopkins was fully supportive of the women taking their intellectual property and owning it themselves. “We received written approval from the tech transfer office to file independently,” says Zawicki. “That is really unique.” 

Coupled with the Lemelson award, Ithemba sees a clear path to ownership of the intellectual property and is filing patents on its device.

Zawicki says that it could be anywhere from three to five years before the device makes it on to the market, but there’s the potential for partnerships with big companies in the biopsy space that could accelerate that time to market.

“Once we get that process solidified and finalize our design we will wrap up our benchtop testing so we can move toward clinical trials by next summer, in 2020,” Zawicki says.

Consumer-focused healthcare can save lives by focusing on changing behavior

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Everything we do in the $3 trillion healthcare market today only affects 10% of outcomes to premature death.

You read that right. All of that, for just 10% of outcomes:

That 10% exists for a reason. Genetic predisposition is hard to change. So, unfortunately, are social circumstances and environmental behavior. But that 40% of behavioral patterns — why can’t we tackle that? This is what real prevention would look like: nothing comes even close to mattering as much towards whether you will die prematurely as your behavior does.

We can do better than simply focusing on that small 10% slice of the pie; in fact, we’re looking in the wrong place. Doctors, entrepreneurs and founders need to be thinking (and treating with) lifestyle as medicine. Because behavioral change is the best and most powerful way to impact that whopping 40% slice.

Too often we think of this as the “just eat right and exercise” problem. As we know very well, that platitude will not solve our healthcare problem. The true problem is the difficulty of modifying behavior. We know this, because the platitude doesn’t work. We like to eat what we want, to exercise or not exercise if we choose. In short, humans like our patterns. They’re hard to change.

Tech, on the other hand, modifies behavior very well. Just look at the phone you’re probably reading this on, which has foundationally changed the way we communicate — along with huge other swaths of human behavior, in both positive and negative ways — from the ability to call a ride service in practically any city at any time to tracking your health to screen addiction. We know technology modifies behavior; we live this every day. So the question is, how can we target this superpower ability of tech to have 4x the ability to impact that the $3 trillion healthcare budget does?

How does it work?

Let’s think about why technology actually does work for modifying behavior. For one, it’s always there, thanks to the leap in mobile tech, whether that be phones or fitness trackers. Second, technology’s ability to do constant A/B testing essentially enables RCTs, or Randomized Clinical Trials, every moment that technology is present and being used. These RCTs are invaluable laboratories for learning about what is effective therapeutic behavior modification, or improving efficacy — and it’s not toxic. Most medical products are released and then rarely get updated (think about how old the stethoscope is!). Rolling out new versions of products has been difficult and expensive. But that no longer has to be true. The same kind of A/B testing that Amazon does, for example, to optimize ecommerce — everything from the look of the website to the flow of the experience to the nature of the shipping that you get — can be now applied to behavior modification for health. Comparing the immediate efficacy of two algorithms for lifestyle behavior modification on two different populations can happen not just over years or months — as a RCT would have to be — but over weeks and even days, improving our responses and lifestyles that much faster.

Second, applying Machine Learning to vast amounts of new data is identifying all kinds of nuances of human behavior that we aren’t nearly as good, as humans, at noticing. For example, correlating patterns with data like where you shop, when you eat lunch, what activities do you do, what shows you watch, what your exercise routine has been, how much you sleep, even perhaps whether you remember to charge your phone. Identifying the clues in our behavior that eventually add up to significant lifestyle risk is the first step towards changing and improving that behavior. Like it or not, we live our lifestyles now through our phones — ML allows us to learn from it.

And last, technology allows us to scale existing therapies in new orders of magnitude.  Programs which have proven extremely effective at behavior modification through personal interaction — such as Diabetes Prevention Program for Type 2 Diabetes — have been by definition hard to scale; computation can extend their reach into the billions. Or take for another example depression, a complex disease where the molecules involved are poorly understood: drug therapies have been challenging, but therapy, specifically CBT, has a very strong track record, and computational CBT — ie, CBT scaled with technology — the strongest.

Even conditions as mysterious and difficult as cognitive decline can be treated much more effectively with technology. This is another fascinating example where the biology is so complex at the molecular level that breakthroughs have been far and few between. On the other hand, cognitive is painfully clear at the behavior level. And it is also very clear that behavioral treatment in the form of cognitive stimulation helps significantly. In this study, for example, the auditory memory and attention capability of patients who received cognitive stimulation training 1 hour per day, 5 days per week, for 8 weeks improvement was significantly greater than those who did not.

These are big challenges to meet. Behavior is the result of thousands of small decisions at every moment of every day: do I sit or do I stand? Do I drink this beer? Even, do I take regular deep breaths? One of the biggest challenges to face is how we ‘read’ this behavior and turn it into reliable data. There’s also the issue of small sample sizes: in order to narrow down to a meaningful experiment, you need, at the moment, to have very clear definitions of behavior, which often means small sample sizes of people who always do X in Y conditions. The science of behavior and decision making itself is complex, debatable, and often evolving. And there’s the company building practicalities: to build a company in this space, you need to find people who understand clinical science, data science, experimentation approaches, behavioral science *and* product and UI.

But that’s exactly the opportunity. These things are coming; we understanding more about behavior every day, as devices enter our daily lives and health data becomes more and more fine-grained. New conceptions of roles that blend behavioral science and product design are clearly emerging. All of these means are not exclusive and can be combined into powerful ways of modifying behavior for health. Those that can connect all these dots have the ability to build companies that can take a giant bite out of that 40% — and have tremendous impact on mortality for huge swaths of the population.

There’s an old joke that plumbers have saved more lives than doctors, because improving sewers and sanitation (and eradicating the disease that went along with that) was so impactful on longevity for humans. By cleaning up the modern day ‘sewers’ of our lifestyles — not through magical drugs, complex procedures, or platitudes about prevention — but through a real infrastructure of technology that is being built right now — technology will bring an analogous impact.

Healthcare by 2028 will be doctor-directed, patient-owned and powered by visual technologies

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Visual assessment is critical to healthcare – whether that is a doctor peering down your throat as you say “ahhh” or an MRI of your brain. Since the X-ray was invented in 1895, medical imaging has evolved into many modalities that empower clinicians to see into and assess the human body.  Recent advances in visual sensors, computer vision and compute power are currently powering a new wave of innovation in legacy visual technologies(like the X-Ray and MRI) and sparking entirely new realms of medical practice, such as genomics.

Over the next 10 years, healthcare workflows will become mostly digitized, with wide swaths of personal data captured and computer vision, along with artificial intelligence, automating the analysis of that data for precision care. Much of the digitized data across healthcare will be visual and the technologies that capture and analyze it are visual technologies.

These visual technologies traverse a patient’s journey from diagnosis, to treatment, to continuing care and prevention.They capture, analyze, process, filter and manage any visual data from images, videos, thermal, x-ray’s, ultrasound, MRI, CT scans, 3D, and more. Computer vision and artificial intelligence are core to the journey.

Three powerful trends — including miniaturization of diagnostic imaging devices, next generation imaging to for the earliest stages of disease detection and virtual medicine — are shaping the ways in which visual technologies are poised to improve healthcare over the next decade.

Miniaturization of Hardware Along with Computer Vision and AI will allow Diagnostic Imaging to be Mobile

Medical imaging is dominated by large incumbents that are slow to innovate. Most imaging devices (e.g. MRI machines) have not changed substantially since the 1980s and still have major limitations:

  • Complex workflows: large, expensive machines that require expert operators and have limited compatibility in hospitals.

  • Strict patient requirements: such as lying still or holding their breath (a problem for cases such as pediatrics or elderly patients).

  • Expensive solutions: limited to large hospitals and imaging facilities.

But thanks to innovations in visual sensors and AI algorithms, “modern medical imaging is in the midst of a paradigm shift, from large carefully-calibrated machines to flexible, self-correcting, multi-sensor devices” says Daniel K. Sodickson, MD, PhD, NYU School of Medicine, Department of Radiology.

MRI glove-shaped detector proved capable of capturing images of moving fingers.  ©NYU Langone Health

Visual data capture will be done with smaller, easier to use devices, allowing imaging to move out of the radiology department and into the operating room, the pharmacy and your living room.

Smaller sensors and computer vision-enabled image capture will lead to imaging devices that are being redesigned a fraction of the size with:

  • Simpler imaging process: with quicker workflows and lower costs.

  • Lower expertise requirements: less complexity will move imaging from the radiology department to anywhere the patient is.

  • Live imaging via ingestible cameras: innovation includes powering ingestibles via stomach acid, using bacteria for chemical detection and will be feasible in a wider range of cases.

“The use of synthetic neural network-based implementations of human perceptual learning enables an entire class of low-cost imaging hardware and can accelerate and improve existing technologies,” says Matthew Rosen, PhD, MGH/Martinos Center at Harvard Medical School.

©Matthew Rosen and his colleagues at the Martinos Center for Biomedical Imaging in Boston want liberate the MRI.

Next Generation Sequencing, Phenotyping and Molecular Imaging Will Diagnose Disease Before Symptoms are Presented

Genomics, the sequencing of DNA, has grown at a 200% CAGR since 2015, propelled by Next Generation Sequencing (NGS) which uses optical signals to read DNA, like our LDV portfolio company Geniachip which was acquired by Roche. These techniques are helping genomics become a mainstream tool for practitioners, and will hopefully make carrier screening part of routine patient care by 2028.

Identifying the genetic makeup of a disease via liquid biopsies, where blood, urine or saliva is tested for tumor DNA or RNA, are poised to take a prime role in early cancer screening. The company GRAIL, for instance, raised $1B for a cancer blood test that uses NGS and deep learning to detect circulating tumor DNA before a lesion is identified.

Phenomics, the analysis of observable traits (phenotypes) that result from interactions between genes and their environment, will also contribute to earlier disease detection. Phenotypes are expressed physiologically and most will require imaging to be detected and analyzed.

Next Generation Phenotyping (NGP) uses computer vision and deep learning to analyze physiological data, understand particular phenotype patterns, then it correlates those patterns to genes. For example, FDNA’s Face2Gene technology can identify 300-400 disorders with 90%+ accuracy using images of a patient’s face. Additional data (images or videos of hands, feet, ears, eyes) can allow NGP to detect a wide range of disorders, earlier than ever before.

Molecular imaging uses DNA nanotech probes to quantitatively visualize chemicals inside of cells, thus measuring the chemical signature of diseases. This approach may enable early detection of neurodegenerative diseases such as Alzheimer’s, Parkinson’s and dementia.

Telemedicine to Overtake Brick-and-Mortar Doctors Visits

By 2028 it will be more common to visit the doctor via video over your phone or computer than it will be to go to an office.

Telemedicine will make medical practitioners more accessible and easier to communicate with. It will create an all digitized health record of visits for a patient’s profile and it will reduce the costs of logistics and regional gaps in specific medical expertise. An example being the telemedicine services rendered for 1.9M injured in the war in Syria.4

The integration of telemedicine into ambulances has led to stroke patients being treated twice as fast.  Doctors will increasingly call in their colleagues and specialists in real time.

Screening technologies will be integrated into telemedicine so it won’t just be about video calling a doctor. Pre-screening your vitals via remote cameras will deliver extensive efficiencies and hopefully health benefits.

“The biggest opportunity in visual technology in telemedicine is in solving specific use cases. Whether it be detecting your pulse, blood pressure or eye problems, visual technology will be key to collecting data,” says Jeff Nadler, Teldoc health.

Remote patient monitoring (RPM) will be a major factor in the growth of telemedicine and the overall personalization of care. RPM devices, like we are seeing with the Apple Watch, will be a primary source of real-time patient data used to make medical decisions that take into account everyday health and lifestyle factors. This personal data will be collected and owned by patients themselves and provided to doctors.

Visual Tech Will Power the Transformation of Healthcare Over the Next Decade

Visual technologies have deep implications for the future of personalized healthcare and will hopefully improve the health of people worldwide. It represents unique investment opportunities and we at LDV Capital have reviewed over 100 research papers from BCC Research, CBInsights, Frost & Sullivan, McKinsey, Wired, IEEE Spectrum and many more to compile our 2018 LDV Capital Insights report. This report highlights the sectors that power to improve healthcare based on the transformative nature of the technology in the sector, projected growth and business opportunity.

There are tremendous investment opportunities in visual technologies across diagnosis, treatment and continuing care & prevention that will help make people healthier across the globe.

Healthcare wearables level up with new moves from Apple and Alphabet

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Announcements that Apple has partnered with Aetna health insurance on a new app leveraging data from its Apple Watch and reports that Verily — one of the health-focused subsidiaries of Google‘s parent company — Alphabet, is developing a shoe that can detect weight and movement, indicate increasing momentum around using data from wearables for clinical health applications and treatments.

For venture capital investors, the movea from Apple and Alphabet to show new applications for wearable devices is a step in the right direction — and something that’s been long overdue.

“As a healthcare provider, we talk a lot about the important of preventative medicine, but the US healthcare system doesn’t have the right incentives in place to pay for it,” writes Cameron Sepah, an entrepreneur in residence at Trinity Ventures. “Since large employers largely pay for health care (outside of Medicaid and Medicare), they usually aren’t incentivized to pay for prevention, since employees don’t stay long enough for them to incur the long-term costs of health behaviors. So most startups in this space end up becoming an expendable wellness perk for companies. However, if an insurer like Aetna keeps its members long enough, there’s better alignment for disseminating this app.”

Sepah sees broader implications for the tie ups between health insurers and the tech companies making all sorts of devices to detect and diagnose conditions.

“Most patients relationship with their insurer is just getting paper bills/notifications in the mail, with terrible customer satisfaction (NPS) across the board,” Sepah wrote in an email. “But when there’s a way to build a closer relationship through a device that sits on your wrist, it opens possibilities to partner with other health tech startups that can notify patients when they are having mental health issues before they even recognize it (e.g. Mindstrong); or when they should get treatment for hypertension or sleep apnea (e.g. Cardiogram); or leverage their data into a digital chronic disease treatment program (e.g. Omada Health).”

Aetna isn’t the first insurer to tie Apple Watch data to their policies. In September 2018, John Hancock launched the Vitality program, which also gave users discounts on the latest Apple Watch if they linked it with John Hancock’s app. The company also gave out rewards if users changed their behavior around diet and exercise.

In a study conducted by Rand Europe of 400,000 people in the U.S., the U.K., and South Africa, research showed that users who wore an Apple Watch and participated in the Vitality benefits program averaged a 34 percent increase in physical activity compared to patients without the Apple Watch. It equated to roughly 5 extra days of working out per month.

“[It will] be interesting to see how CVS/Apple deal unfolds. Personalized health guidance based on a combination of individual medical records and real time wearable data is a huge and worthy goal,” wrote Greg Yap, a partner at the venture capital firm, Menlo Ventures . But, Yap wrote,I’m skeptical their first generation app will have enough data or training to deliver value to a broad population, but we’re likely to see some anecdotal benefits, and I find that worthwhile.”

Meanwhile the types of devices that record consumer health information are proliferating — thanks in no small part to Verily.

With the company reportedly working to co-develop shoes with sensors that monitor users’ movement and weight, according to CNBC, Verily is expanding its portfolio of connected devices for health monitoring and management. The company already has a watch that monitors certain patient data — including an FDA approved electrocardiogram — and is developing technologies to track diabetes-related eye disease in patients alongside smart lenses for cataract recovery.

It’s part of a broader push from technology companies to tie themselves closer to consumer health as they look to seize a part of the nearly $3 trillion healthcare industry.

If more data can be collected from wearable devices (or consumer behavior) and then monitored in a consistent fashion, tech companies ideally could suggest interventions faster and provide lower cost treatments to help avoid the need for urgent or emergency care.

These “top of the funnel” communications and monitoring services from tech companies could conceivably divert users and future healthcare patients into an alternative system that is potentially lower-cost with more of a focus on outcomes than on the volume of care and number of treatments prescribed.

Not all physicians are convinced that the use of persistent monitoring will result in better care. Dr. John Ioannidis, a celebrated professor from Stanford University, is skeptical about the utility of monitoring without a better understanding of what the data actually reveals.

“Information is good for you provided you know what it means. For much of that information we have no clue what it means. We have absolutely no idea what to do with it other than creating more anxiety,” Dr. Ioannidis said

The goal is to provide personalized guidance where machine learning can be used to identify problems and come up in concert with established therapeutic practices, according to investors who back life sciences starups.

“I think startups like Omada, Livongo, Lark, Vida, Virta, and others, can work and are already working on this overall vision of combining real time and personal historical data to deliver personalized guidance. But to be successful, startups need to be more narrowly focused and deliver improved outcomes and financial benefits right away,” according to Yap.

 

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