3 golden rules for health tech entrepreneurs

If the last 10 years practicing family medicine have taught me anything, it’s that there is a desperate need for innovation in healthcare. I don’t just mean in terms of medical treatments or protocols, but really in every aspect. As a physician, I’ve worked with my fair share of “the latest and greatest” innovations both in my outpatient practice and at hospitals.

As I shifted into my current position, I’ve come across some products that were distinguished winners, eventually going on to become not just highly successful but the new gold standard in the industry. Others, unfortunately, never even got off the ground. Often, in the back of my mind, I felt like I could always tell which ones had the staying power to transform healthcare the way it needed to be transformed.

When it comes to ensuring the success of your product, service or innovation, following these three golden rules will put you on the right track.

When it comes to ensuring the success of your product, service or innovation, following these three golden rules will put you on the right track. It’s no guarantee, but without getting these three things right, you’ve got no shot.

Design for outcomes first

Stephen Covey coined the phrase: “Begin with the end in mind.” It’s the second of his 7 Habits. But he could have also been writing about habits for health tech innovators. It’s not enough to develop a “new tool” to use in a health setting. Maybe it has a purpose, but does it meaningfully address a need, or solve a problem, in a way that measurably improves outcomes? In other words: Does it have value?

When the COVID-19 pandemic hit, pharmaceutical and research firms set out upon a global mission to develop safe and effective vaccines, to bring the virus under control and return life around the world to something approaching “normal” … and quickly. In less than a year, Pfizer and Moderna crossed the finish line first, bringing novel two-jab mRNA vaccines to market with extraordinary speed and with an outstanding efficacy rate.

Vaccine makers started with an outcome in mind and, in countries with plentiful vaccine access, are delivering on those outcomes. But not all outcomes need be so lofty to be effective. Maybe your innovation aims to:

  • Improve patient compliance with at-home treatment plans.
  • Reduce the burden of documentation on physicians and scribes.
  • Increase access to quality care among underserved, impoverished or marginalized communities.

For example, Alertive Healthcare, one of our portfolio companies, wanted to meaningfully improve round-the-clock care for when patients couldn’t get in to see their physicians and developed a platform for clinical-grade remote patient monitoring. Patients download an easy-to-use app that sends intelligent alerts to providers, reducing documentation and decreasing time to treatment. Patients enrolled in the app reduce their risk of heart attack and stroke by 50%. That’s compelling value and an example of designing for outcomes.

When designing for outcomes, it’s also important to know precisely how you’ll measure success. When you can point toward quantifiable metrics, you’re not only giving yourself goals in your product design and development, you’re also establishing the proof points that sell your product into the market. Make them as meaningful and measurable as possible, as soon as possible.

The human-focused startups of the hellfire

Disasters may not always be man-made, but they are always responded to by humans. There’s a whole panoply of skills and professions required today to respond to even the tiniest emergency, and that doesn’t even include the needs during pre-disaster planning and post-disaster recovery. It’s not a very remunerative industry for most and the mental health effects from stress can linger for decades, but the mission at the core of this work — to help people in the time of their greatest need — is what continues to attract many to partake in this never-ending battle anyway.

In the last three parts of this series on the future of technology and disaster response, I’ve focused on, well, technology, and specifically the sales cycle for new products, the sudden data deluge now that Internet of Things (IoT) is in full force, and the connectivity that allows that data to radiate all around. What we haven’t looked at enough so far is the human element: the people who actually respond to disasters as well as what challenges they face and how technology can help them.

So in this fourth and final part of the series, we’ll look at four areas where humans and technology intersect within disaster response and what future opportunities lie in this market: training and development, mental health, crowdsourced responses to disasters, and our doomsday future of hyper-complex emergencies.

Training in a hellfire

Most fields have linear approaches to training. To become a software engineer, students learn some computer science theory, add in some programming practice, and voilà (note: your mileage may vary). To become a medical doctor, aspiring physicians take an undergraduate curriculum teeming with biology and chemistry, head to medical school for two deadened years of core anatomy and other classes and then switch into clinical rotations, a residency, and maybe fellowships.

But how do you train someone to respond to emergencies?

From 911 call takers to EMTs and paramedics to emergency planning officials and the on-the-ground responders who are operating in the center of the storm as it were, there are large permutations in the skills required to do these jobs well. What’s necessary aren’t just specific hard skills like using call dispatch software or knowing how to upload video from a disaster site, but also critically-important softer skills as well: precisely communicating, having sangfroid, increasing agility, and balancing improvisation with consistency. The chaos element also can’t be overstated: every disaster is different, and these skills must be viscerally recombined and exercised under extreme pressure with frequently sparse information.

A whole range of what might be dubbed “edtech” products could serve these needs, and not just exclusively for emergency management.

Communications, for instance, isn’t just about team communications, but also communicating with many different constituencies. Aaron Clark-Ginsberg, a social scientist at RAND Corporation, said that “a lot of these skills are social skills — being able to work with different groups of people in culturally and socially appropriate ways.” He notes that the field of emergency management has heightened attention to these issues in recent years, and “the skillset we need is to work with those community structures” that already exist where a disaster strikes.

As we’ve seen in the tech industry the last few years, cross-cultural communication skills remain scarce. One can always learn this just through repeated experiences, but could we train people to develop empathy and understanding through software? Can we develop better and richer scenarios to train emergency responders — and all of us, really — on how to communicate effectively in widely diverging conditions? That’s a huge opportunity for a startup to tackle.

Emergency management is now a well-developed career path. “The history of the field is very fascinating, [it’s] been increasingly professionalized, with all these certifications,” Clark-Ginsberg said. That professionalization “standardizes emergency response so that you know what you are getting since they have all these certs, and you know what they know and what they don’t.” Certifications can indicate singular competence, but perhaps not holistic assessment, and it’s a market that offers opportunities for new startups to create better assessments.

Like many of us, responders get used to doing the same thing over and over again, and that can make training for new skills even more challenging. Michael Martin of emergency data management platform RapidSOS describes how 911 call takers get used to muscle memory, “so switching to a new system is very high-risk.” No matter how bad existing software interfaces are, changing them will very likely slow every single response down while increasing the risk of errors. That’s why the company offers “25,000 hours a year for training, support, integration.” There remains a huge and relatively fragmented market for training staff as well as transitioning them from one software stack to another.

Outside these somewhat narrow niches, there is a need for a massive renaissance in training in this whole area. My colleague Natasha Mascarenhas recently wrote an EC-1 on Duolingo, an app designed to gamify and entrance students interested in learning second languages. It’s a compelling product, and there is no comparative training system for engaging the full gamut of first responders.

Art delaCruz, COO and president of Team Rubicon, a non-profit which assembles teams of volunteer military veterans to respond to natural disasters, said that it’s an issue his organization is spending more time thinking about. “Part of resilience is education, and the ability to access information, and that is a gap that we continue to close on,” he said. “How do you present information that’s more simple than [a learning management system]?” He described the need for “knowledge bombs like flash cards” to regularly provide responders with new knowledge while testing existing ideas.

There’s also a need to scale up best practices rapidly across the world. Tom Cotter, director of emergency response and preparedness at Project Hope, a non-profit which empowers local healthcare workers in disaster-stricken and impoverished areas, said that in the context of COVID-19, “a lot of what was going to be needed [early on] was training — there were huge information gaps at the clinical level, how to communicate it at a community level.” The organization developed a curriculum with Brown University’s Watson Institute in the form of interactive PowerPoints that were ultimately used to train 100,000 healthcare workers on the new virus, according to Cotter.

When I look at the spectrum of edtech products existing today, one of the key peculiarities is just how narrow each seems to focus. There are apps for language learning and for learning math and developing literacy. There are flash card apps like Anki that are popular among medical students, and more interactive approaches like Labster for science experiments and Sketchy for learning anatomy.

Yet, for all the talk of boot camps in Silicon Valley, there is no edtech company that tries to completely transform a student in the way that a bona fide boot camp does. No startup wants to holistically develop their students, adding in hard skills while also advancing the ability to handle stress, the improvisation needed to confront rapidly-changing environments, and the skills needed to communicate with empathy.

Maybe that can’t be done with software. Maybe. Or perhaps, no founder has just had the ambition so far to go for broke — to really revolutionize how we think about training the next generation of emergency management professionals and everyone else in private industry who needs to handle stress or think on their feet just as much as frontline workers.

That’s the direction where Bryce Stirton, president and co-founder of public-safety company Responder Corp, has been thinking about. “Another area I am personally a fan of is the training space around VR,” he said. “It’s very difficult to synthesize these stressful environments,” in areas like firefighting, but new technologies have “the ability to pump the heart that you need to experience in training.” He concludes that “the VR world, it can have a large impact.”

Healing after disaster

When it comes to trauma, few fields face quite the challenge as emergency response. It’s work that almost by definition forces its personnel to confront some of the most harrowing scenes imaginable. Death and destruction are given, but what’s not always accounted for is the lack of agency in some of these contexts for first responders — the family that can’t be saved in time so a 911 call taker has to offer final solace, or the paramedics who don’t have the right equipment even as they are showing up on site.

Post-traumatic stress is perhaps the most well-known and common mental health condition facing first responders, although it is hardly the only one. How to ameliorate and potentially even cure these conditions represents a burgeoning area of investment and growth for a number of startups and investors.

Risk & Return, for instance, is a venture firm heavily focused on companies working on mental health as well as human performance more generally. In my profile of the firm a few weeks ago, managing director Jeff Eggers said that “We love that type of technology since it has that dual purpose: going to serve the first responder on the ground, but the community is also going to benefit.”

Two examples of companies from its portfolio are useful here to explore as examples of different pathways in this category. The first is Alto Neuroscience, which is a stealthy startup founded by Amit Etkin, a multidisciplinary neuroscientist and psychiatrist at Stanford, to create new clinical treatments to post-traumatic stress and other conditions based on brainwave data. Given its therapeutic focus, it’s probably years before testing and regulatory approvals come through, but this sort of research is on the cutting-edge of innovation here.

The second company is NeuroFlow, which is a software startup using apps to guide patients to better mental health outcomes. Through persistent polling, testing, and collaboration with practitioners, the company’s tools allow for more active monitoring of mental health — looking for emerging symptoms or relapses in even the most complicated cases. NeuroFlow is more on the clinical side, but there are obviously a wealth of wellness startups that have percolated in recent years as well like Headspace and Calm.

Outside of therapeutics and software though, there are entirely new frontiers around mental health in areas like psychedelics. That was one of the trends I called out as a top five area for investment in the 2020s earlier this year, and I stand by that. We’ve also covered a startup called Osmind which is a clinical platform for managing patients with a psychedelic focus.

Risk & Return itself hasn’t made an investment in psychedelics yet, but Bob Kerrey, the firm’s board chairman and the former co-chair of the 9/11 Commission as well as former governor and senator of Nebraska, said that “it’s difficult to do this if you are the government, but easier to do this in the private sector.”

Similar to edtech, mental health startups might get their start in the first responder community, but they are hardly limited to this population. Post-traumatic stress and other mental health conditions affect wide swaths of the world’s population, and solutions that work in one community can often translate more broadly to others. It’s a massive, massive market, and one that could potentially transform the lives of millions of people for the better.

Before moving on, there’s one other area of interest here, and that is creating impactful communities for healing. First responders and military veterans experience a mission and camaraderie in their service that they often lack once they are in new jobs or on convalescence. DelaCruz of Team Rubicon says that one of the goals of bringing veterans to help in disaster regions is that the veterans themselves “reconnect with identity and community — we have these incredible assets in these men and women who have served.” It’s not enough to just find a single treatment per patient — we oftentimes need to zoom out to the wider population to see how mental health ripples out.

Helping people find purpose may not be the easiest challenge to solve as a startup, but it’s certainly a major challenge for many, and an area fermenting with new approaches now that the the social networking wave has reached its nadir.

Crowdsourcing disaster response

Decentralization has been all the rage in tech in recent years — just mention the word blockchain in a TechCrunch article to get at least 50 PR emails about the latest NFT for a toilet stain. While there is obviously a lot of noise, one area where substance may pan out well is in disaster response.

If the COVID-19 pandemic showed anything, it was the power of the internet to aggregate as well as verify data, build dashboards, and deliver highly-effective visualizations of complex information for professionals and laypeople alike. Those products were developed by people all around the world often from the comfort of their own homes, and they demonstrate how crowds can quickly draft serious labor to help respond to crises as they crop up.

Jonathan Sury, project director at the National Center for Disaster Preparedness at the Earth Institute at Columbia University, said that “COVID has really blown so much of what we think about out of the water.” With so many ways to collaborate online right now, “that’s what I would say is very exciting … and also practical and empowering.”

Clark-Ginsberg of RAND calls it the “next frontier of disaster management.” He argues that “if you can use technology to broaden the number of people who can participate in disaster management and respond to disasters,” then we might be reaching an entirely new paradigm for what effective disaster response will look like. “Formal structures [for professional frontline workers] have strengthened and that has saved lives and resources, but our ability to engage with everyday responders is still something to work on.”

Many of the tools that underpin these crowdsourced efforts don’t even focus on disasters. Sury pointed to Tableau and data visualization platform Flourish as examples of the kinds of tools that remote, lay first responders are using. There are now quite robust tools for tabular data, but we’re still relatively early in the development of tools for handling mapping data — obviously critical in the crisis context. Unfolded.ai, which I profiled earlier this year, is working on building scalable geospatial analytics in the browser. A lot more can be done here.

Oftentimes there are ways to coordinate the coordinators. Develop for Good, which I looked at late last year, is a non-profit designed to connect enterprising computer science students to software and data projects at non-profits and agencies that needed help during the pandemic. Sometimes these coordinators are non-profit orgs, and sometimes, just very active Twitter accounts. There’s a lot more experimentation possible on how to coordinate efforts in a decentralized way while still engaging with professional first responders and the public sector.

Speaking of decentralization, it’s even possible that blockchain could play a role in disaster and crisis response. Many of these opportunities rest on using blockchain for evidence collection or for identity. For example, earlier this week Leigh Cuen took a careful look at an at-home sexual assault evidence collection kit from Leda Health that uses the blockchain to establish a clear time for when a sample was collected.

There is a lot more potential to harness the power of crowdsourcing and decentralization, and many of these projects have applications far outside disaster management itself. These tools not only solve real problems — they provide real community to people who may not be related to the disaster itself, but are enthusiastic to do their part to help others.

The black swans of black swans

In terms of startups, the three markets I identified — better training, better mental health, and better crowdsourcing collaboration tools, particularly around data — collectively represent a very compelling set of markets that will not only be valuable for founders, but can rapidly improve lives.

In his book Normal Accidents, Charles Perrow talks about how an increasing level of complexity and coupledness in our modern technical systems all but guarantee disasters to occur. Add in a warming world as well as the intensity, frequency, and just plain unusualness of disasters arriving each year, and we are increasingly seeing entirely novel forms of emergencies we have never responded to before. Take most recently the ultra-frigid conditions in Texas that sapped power from its grid, leading to statewide blackouts for hours and days in some parts of the state.

Clark-Ginsberg said, “We are seeing these risks emerge that aren’t just typical wildfires — where we have a response structure that we can easily setup and manage the hazard, [we’re] very good at managing these typical disasters. There are more of these atypical disasters cropping up, and we have a very hard time setting up structures for this — the pandemic is a great example of that.”

He describes these challenges as “trans-boundary risk management,” disasters that cross bureaucratic lines, professions, societies, and means of action. “It takes a certain agility and the ability to move quickly and the ability to work in ways outside typical bureaucratic structures, and that is just challenging full stop,” he said.

The Future of Technology and Disaster Response

Even as we begin to have better point solutions to the individual problems that disasters and their responses require, we can’t be remiss in neglecting the more systematic challenges that these emergencies are bringing to the fore. We have to start thinking about bringing humans together faster and in more novel ways to be the most effective, while coupling them flexibly and with agility to the best tools that meet their needs in the moment. That’s probably not literally “a startup,” but more a way of thinking about what it means to construct a disaster response fresh given the information available.

Amanda Levin, a policy analyst at the Natural Resources Defense Council, said that “even if we mitigate, there are huge pressures and huge impacts today from a warming world … even if we stop emissions today, [they] will still persist.” As one of my interviewees in government service who asked to go unnamed noted about disaster response, “You always are coming up short somewhere.” The problems are only getting harder, and we humans need much better tools to match the man-made trials we created for ourselves. That’s the challenge — and opportunity — for a tough century ahead.

Longevity startup Gero AI has a mobile API for quantifying health changes

Sensor data from smartphones and wearables can meaningfully predict an individual’s ‘biological age’ and resilience to stress, according to Gero AI.

The ‘longevity’ startup — which condenses its mission to the pithy goal of “hacking complex diseases and aging with Gero AI” — has developed an AI model to predict morbidity risk using ‘digital biomarkers’ that are based on identifying patterns in step-counter sensor data which tracks mobile users’ physical activity.

A simple measure of ‘steps’ isn’t nuanced enough on its own to predict individual health, is the contention. Gero’s AI has been trained on large amounts of biological data to spots patterns that can be linked to morbidity risk. It also measures how quickly a personal recovers from a biological stress — another biomarker that’s been linked to lifespan; i.e. the faster the body recovers from stress, the better the individual’s overall health prognosis.

A research paper Gero has had published in the peer-reviewed biomedical journal Aging explains how it trained deep neural networks to predict morbidity risk from mobile device sensor data — and was able to demonstrate that its biological age acceleration model was comparable to models based on blood test results.

Another paper, due to be published in the journal Nature Communications later this month, will go into detail on its device-derived measurement of biological resilience.

The Singapore-based startup, which has research roots in Russia — founded back in 2015 by a Russian scientist with a background in theoretical physics — has raised a total of $5 million in seed funding to date (in two tranches).

Backers come from both the biotech and the AI fields, per co-founder Peter Fedichev. Its investors include Belarus-based AI-focused early stage fund, Bulba Ventures (Yury Melnichek). On the pharma side, it has backing from some (unnamed) private individuals with links to Russian drug development firm, Valenta. (The pharma company itself is not an investor).

Fedichev is a theoretical physicist by training who, after his PhD and some ten years in academia, moved into biotech to work on molecular modelling and machine learning for drug discovery — where he got interested in the problem of ageing and decided to start the company.

As well as conducting its own biological research into longevity (studying mice and nematodes), it’s focused on developing an AI model for predicting the biological age and resilience to stress of humans — via sensor data captured by mobile devices.

“Health of course is much more than one number,” emphasizes Fedichev. “We should not have illusions about that. But if you are going to condense human health to one number then, for a lot of people, the biological age is the best number. It tells you — essentially — how toxic is your lifestyle… The more biological age you have relative to your chronological age years — that’s called biological acceleration — the more are your chances to get chronic disease, to get seasonal infectious diseases or also develop complications from those seasonal diseases.”

Gero has recently launched a (paid, for now) API, called GeroSense, that’s aimed at health and fitness apps so they can tap up its AI modelling to offer their users an individual assessment of biological age and resilience (aka recovery rate from stress back to that individual’s baseline).

Early partners are other longevity-focused companies, AgelessRx and Humanity Inc. But the idea is to get the model widely embedded into fitness apps where it will be able to send a steady stream of longitudinal activity data back to Gero, to further feed its AI’s predictive capabilities and support the wider research mission — where it hopes to progress anti-ageing drug discovery, working in partnerships with pharmaceutical companies.

The carrot for the fitness providers to embed the API is to offer their users a fun and potentially valuable feature: A personalized health measurement so they can track positive (or negative) biological changes — helping them quantify the value of whatever fitness service they’re using.

“Every health and wellness provider — maybe even a gym — can put into their app for example… and this thing can rank all their classes in the gym, all their systems in the gym, for their value for different kinds of users,” explains Fedichev.

“We developed these capabilities because we need to understand how ageing works in humans, not in mice. Once we developed it we’re using it in our sophisticated genetic research in order to find genes — we are testing them in the laboratory — but, this technology, the measurement of ageing from continuous signals like wearable devices, is a good trick on its own. So that’s why we announced this GeroSense project,” he goes on.

“Ageing is this gradual decline of your functional abilities which is bad but you can go to the gym and potentially improve them. But the problem is you’re losing this resilience. Which means that when you’re [biologically] stressed you cannot get back to the norm as quickly as possible. So we report this resilience. So when people start losing this resilience it means that they’re not robust anymore and the same level of stress as in their 20s would get them [knocked off] the rails.

“We believe this loss of resilience is one of the key ageing phenotypes because it tells you that you’re vulnerable for future diseases even before those diseases set in.”

“In-house everything is ageing. We are totally committed to ageing: Measurement and intervention,” adds Fedichev. “We want to building something like an operating system for longevity and wellness.”

Gero is also generating some revenue from two pilots with “top range” insurance companies — which Fedichev says it’s essentially running as a proof of business model at this stage. He also mentions an early pilot with Pepsi Co.

He sketches a link between how it hopes to work with insurance companies in the area of health outcomes with how Elon Musk is offering insurance products to owners of its sensor-laden Teslas, based on what it knows about how they drive — because both are putting sensor data in the driving seat, if you’ll pardon the pun. (“Essentially we are trying to do to humans what Elon Musk is trying to do to cars,” is how he puts it.)

But the nearer term plan is to raise more funding — and potentially switch to offering the API for free to really scale up the data capture potential.

Zooming out for a little context, it’s been almost a decade since Google-backed Calico launched with the moonshot mission of ‘fixing death’. Since then a small but growing field of ‘longevity’ startups has sprung up, conducting research into extending (in the first instance) human lifespan. (Ending death is, clearly, the moonshot atop the moonshot.) 

Death is still with us, of course, but the business of identifying possible drugs and therapeutics to stave off the grim reaper’s knock continues picking up pace — attracting a growing volume of investor dollars.

The trend is being fuelled by health and biological data becoming ever more plentiful and accessible, thanks to open research data initiatives and the proliferation of digital devices and services for tracking health, set alongside promising developments in the fast-evolving field of machine learning in areas like predictive healthcare and drug discovery.

Longevity has also seen a bit of an upsurge in interest in recent times as the coronavirus pandemic has concentrated minds on health and wellness, generally — and, well, mortality specifically.

Nonetheless, it remains a complex, multi-disciplinary business. Some of these biotech moonshots are focused on bioengineering and gene-editing — pushing for disease diagnosis and/or drug discovery.

Plenty are also — like Gero —  trying to use AI and big data analysis to better understand and counteract biological ageing, bringing together experts in physics, maths and biological science to hunt for biomarkers to further research aimed at combating age-related disease and deterioration.

Another recent example is AI startup Deep Longevity, which came out of stealth last summer — as a spinout from AI drug discovery startup Insilico Medicine — touting an AI ‘longevity as a service’ system which it claims can predict an individual’s biological age “significantly more accurately than conventional methods” (and which it also hopes will help scientists to unpick which “biological culprits drive aging-related diseases”, as it put it).

Gero AI is taking a different tack toward the same overarching goal — by honing in on data generated by activity sensors embedded into the everyday mobile devices people carry with them (or wear) as a proxy signal for studying their biology.

The advantage being that it doesn’t require a person to undergo regular (invasive) blood tests to get an ongoing measure of their own health. Instead our personal device can generate proxy signals for biological study passively — at vast scale and low cost. So the promise of Gero’s ‘digital biomarkers’ is they could democratize access to individual health prediction.

And while billionaires like Peter Thiel can afford to shell out for bespoke medical monitoring and interventions to try to stay one step ahead of death, such high end services simply won’t scale to the rest of us.

If its digital biomarkers live up to Gero’s claims, its approach could, at the least, help steer millions towards healthier lifestyles, while also generating rich data for longevity R&D — and to support the development of drugs that could extend human lifespan (albeit what such life-extending pills might cost is a whole other matter).

The insurance industry is naturally interested — with the potential for such tools to be used to nudge individuals towards healthier lifestyles and thereby reduce payout costs.

For individuals who are motivated to improve their health themselves, Fedichev says the issue now is it’s extremely hard for people to know exactly which lifestyle changes or interventions are best suited to their particular biology.

For example fasting has been shown in some studies to help combat biological ageing. But he notes that the approach may not be effective for everyone. The same may be true of other activities that are accepted to be generally beneficial for health (like exercise or eating or avoiding certain foods).

Again those rules of thumb may have a lot of nuance, depending on an individual’s particular biology. And scientific research is, inevitably, limited by access to funding. (Research can thus tend to focus on certain groups to the exclusion of others — e.g. men rather than women; or the young rather than middle aged.)

This is why Fedichev believes there’s a lot of value in creating a measure than can address health-related knowledge gaps at essentially no individual cost.

Gero has used longitudinal data from the UK’s biobank, one of its research partners, to verify its model’s measurements of biological age and resilience. But of course it hopes to go further — as it ingests more data. 

“Technically it’s not properly different what we are doing — it just happens that we can do it now because there are such efforts like UK biobank. Government money and also some industry sponsors money, maybe for the first time in the history of humanity, we have this situation where we have electronic medical records, genetics, wearable devices from hundreds of thousands of people, so it just became possible. It’s the convergence of several developments — technological but also what I would call ‘social technologies’ [like the UK biobank],” he tells TechCrunch.

“Imagine that for every diet, for every training routine, meditation… in order to make sure that we can actually optimize lifestyles — understand which things work, which do not [for each person] or maybe some experimental drugs which are already proved [to] extend lifespan in animals are working, maybe we can do something different.”

“When we will have 1M tracks [half a year’s worth of data on 1M individuals] we will combine that with genetics and solve ageing,” he adds, with entrepreneurial flourish. “The ambitious version of this plan is we’ll get this million tracks by the end of the year.”

Fitness and health apps are an obvious target partner for data-loving longevity researchers — but you can imagine it’ll be a mutual attraction. One side can bring the users, the other a halo of credibility comprised of deep tech and hard science.

“We expect that these [apps] will get lots of people and we will be able to analyze those people for them as a fun feature first, for their users. But in the background we will build the best model of human ageing,” Fedichev continues, predicting that scoring the effect of different fitness and wellness treatments will be “the next frontier” for wellness and health (Or, more pithily: “Wellness and health has to become digital and quantitive.”)

“What we are doing is we are bringing physicists into the analysis of human data. Since recently we have lots of biobanks, we have lots of signals — including from available devices which produce something like a few years’ long windows on the human ageing process. So it’s a dynamical system — like weather prediction or financial market predictions,” he also tells us.

“We cannot own the treatments because we cannot patent them but maybe we can own the personalization — the AI that personalized those treatments for you.”

From a startup perspective, one thing looks crystal clear: Personalization is here for the long haul.

 

AI is ready to take on a massive healthcare challenge

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.

Expressable launches with millions for scalable speech therapy

Speaking isn’t simple for at least 40 million Americans, so a new Austin-based startup is scaling a solution. Expressable is a digital speech therapy company that connects patients to speech language pathologists (SLP) via telehealth services and asynchronous support, and it has raised a new $4.5 million seed round.

The early-stage startup is launching with an explicit focus on serving the approximately five million children in the United States that have a communication disorder. What might start as an occasional stutter could turn into a communication disorder over time – so the startup is looking to intervene early to get kids on a clearer path.

Launched in 2019 by married co-founders Nicholas Barbara and Leanne Sherred, Expressable has served thousands of families to date. Today, the duo announced its seed funding, co-led by Lerer Hippeau and NextView Ventures, with participation from Amplifyher Ventures. The money will be used to expand its provider network, go in-network, and focus on its edtech service.

What it does

Put simply, Expressable connects children to speech-language pathologists on a recurring basis. The therapy is done live via Zoom for Healthcare with licensed professionals that Expresssable employs full-time. Clients are matched with a therapist in their area of need, from public speaking to vocal cord paralysis. Parents are able to reach their children’s SLP through secure SMS for coordination, questions, and rescheduling throughout the week.

On top of real-time support, the virtual speech therapy provider has a suite of asynchronous services. The company is building an e-learning platform with homework assignments and lessons, prescribed by the therapist and provided via SMS, for parents to do with their children to reinforce the speech care plans.

The activities are meant to be bite-sized – used when driving to the grocery store or cooking dinner or playing in the backyard – and tailored for interaction with children. The lessons can be as simple as creating opportunities for a kid to ask for juice, or to practice two-word utterances with an imitation game.

A mock secure SMS by Expressable. Image Credits: Expressable

This unique edtech bit of Expressable leans heavily on parent involvement in the therapy process. Parental help has been shown to increase positive outcomes, but notably it could also leave low-income, working class families out of the mix. Its price, on average, is $59 per week, and that’s currently only out of pocket rather than subsidized by insurance.

“There’s a lot of content for speech language pathologists by speech language pathologists, but not a lot of content by [SLPs] for parents, written in a way that is consumable,” Barbara said. “It just felt like a huge opportunity and market gap.”

Part of Expressable’s value is that it’s better than the status quo, which surprisingly often actually amounts to nothing. According to the National Institute on Deafness and Other Communication Disorders, about 8 to 9 percent of children have a speech sound disorder in the country — but only half actually get treatment. What might start as an occasional stutter could turn into a communication disorder over time – so Expressable wants to intervene early to get kids on the right path.

“Public schools are the number-one provider for pediatric speech but they are unfortunately notoriously underfunded,” said Sherred. Children who are lucky enough to be eligible for school services are often provided them in a group setting, she continued, which lengthens the amount of time it takes to make progress.

Sherred witnessed the “incredibly frustrating cycle” created by gaps in school intervention first-hand as a SLP. She has spent the majority of her career in in-home health, where she would work in homes and daycares directly with children.

The majority of Expressable’s user base are children, but about 35% are adults, signaling how speech issues can continue past childhood.

Meagen Lloyst, who sourced the Expressabble deal for Lerer Hippeau, is one example. Lloyst was diagnosed with a speech and voice condition in late 2020 and needed to find remote SLP therapy, which introduced her to the challenges of finding a high-quality specialized SLP.

“Before Expressable, there was no consumer-facing brand out there solving these pain points for individuals with communications disorders,” Lloyst said. “It’s evident that they’re already hiring the best SLPs out there, bringing parents and education into the process to focus on better outcomes for children, and doing so in a cost-effective and convenient way through virtual care.”

Telehealth with a twist

While telehealth usage remains above pre-pandemic levels, visits are on the decline. One challenge for any digital telehealth startup, Expressable included, is how to make a convincing pitch for moving caretaking fully-virtual in a post-pandemic context.

The Expressable co-founders pointed toward consistency, both internally and externally, as a competitive advantage.

First, speech therapy is a recurring service that many patients use once a week, every month, for years. “A lot of other telemedicine plays are these quick, convenient, and direct primary care,” Barbara said. “[We are] a longer tail of treatment plan that requires a close relationship between provider and patient.”

Second, unlike many telehealth startups, Expressable has hired its specialists full-time as W-2 employees. It’s a strategic choice to help ensure to its clients that their SLP of choice is a long-term relationship. The startup has 50 W-2 SLPs currently.

“We have built a career path for SLPs and a value proposition to speech language pathologists where they can work from home, set their own hours [get] paid above the national average, and then receive benefits that may not be obviously not common if you’re working in a contractor position.”

Not relying on the traditional contractor model might be a differentiation, but it’s also a challenge. The startup will have to rapidly (and efficiently) hire SLPs for the variety of speaking conditions out there – and in order to expand into new markets, it has to go through the arduous legal process of local licensing requirements, instead of just going to a white-label solution that helps staff similar companies while offloading individual practitioner certification.

While it has ambitions to become a national practice, Expressable currently operates in 15 states, and employs SLPs that are licensed in all the states that it operates in.

ifeel, another well-being platform that blends self-care tools with 1-2-1 therapy, scores $6.6M

If the pandemic has been good for anything it’s been good for the therapy business and for startups targeting mental health, with VCs kept very busy signing checks. To wit, here’s another one: Madrid-based ifeel has bagged €5.5 million (~$6.6M) in Series A funding, led by Nauta Capital.

The startup was founded back in 2017 — initially as a consumer-focused therapy platform — but last year it pivoted to a hybrid business model, tapping into demand from businesses to offer staff emotional support during the public health crisis. So it’s available both to individuals via monthly subscription or as part of employer’s or insurance provider’s cover

It says that pandemic pivot has resulted in 1,000% growth in its b2b business.

Companies it’s signed up to offer its platform to their staff include AXA Partners, Glovo and Gympass.

“We have a total of 400K users on the platform (b2c and b2b),” says co-founder Amir Kaplan. “We have 100,000 eligible covered who have access to ifeel as a benefit (through our insurance and wellness partners or direct with ifeel).

“The 100K grew 10x from September 2020 and is the largest trend we are experiencing these days. Employees of 100 companies use ifeel on a weekly basis.”

ifeel’s platform delivers both live therapy sessions with licensed psychologists but also provides users with self-care tool such as daily mood trackers, recommended exercises and activities to expand the support available.

“By combining self-care and guided therapies, ifeel maximises engagement and retention of its users — with 90% reporting improved emotional and mental well-being after using ifeel,” it claims.

The startup is using AI technology in the self-care portion of its platform — to recommend “the most relevant” content or exercise to its users, per Kaplan. But he also says it’s looking at using the tech to assist the therapist practice by developing dedicated tools inside the platform.

ifeel has an international founding team, hailing from three countries (Israel, Italy and Mexico), and says its main markets so far are Spain, France, Brazil and Mexico. While its b2b and insurance network coverage extends to 20 countries and four languages (English, Spanish, French and Portuguese).

With so much competition in the mental health tools space — from mindfulness apps, to internet-delivered CBT programs, to therapy platforms — how does ifeel see itself standing out?

Kaplan suggests it has an advantage of being “global from day one”, and also flags a “strong technology integration focus” which he says has allowed it to plug into insurance companies and wellness players — to become a “main service provider”.

“Very early we partnered with global leading companies and we support them in many countries (compared to specific country players like in Germany and UK,” he tells TechCrunch. “The platform approach is different from ‘online therapy’ companies or ‘mindfulness apps’.

“We want our users to manage their emotional well being on our platform no matter the need. In this way we create millions of engagement events that are customized to the user’s needs and allow users over time to use different parts of our platform in different life situations.”

Peloton apologizes, agrees to treadmill recall

Peloton today announced that it will be cooperating with the U.S. Consumer Product Safety Commission (CPSC), agreeing to two voluntary treadmill recalls for the Tread+ and Tread versions of its home treadmill system.

Those who have purchased the systems can contact the connected fitness company for a refund. The company has also agreed to stop selling and distributing both models in the U.S. Last month, CEO John Foley said the company was “troubled” by the CPSC’s decision to go public with its findings, calling them “inaccurate and misleading.” Today’s news finds the executive offering a much more contrite statement.

“The decision to recall both products was the right thing to do for Peloton’s Members and their families,” Foley says. “I want to be clear, Peloton made a mistake in our initial response to the Consumer Product Safety Commission’s request that we recall the Tread+.  We should have engaged more productively with them from the outset. For that, I apologize. Today’s announcement reflects our recognition that, by working closely with the CPSC, we can increase safety awareness for our Members.”

The voluntary recalls are a response to on-going safety concerns around the fitness equipment. The CPSC cites more 70 incidents in total, including the death of a young child. According to the commission, “a six-year-old child recently died after being pulled under the rear of the treadmill. In addition, Peloton has received 72 reports of adult users, children, pets and/or objects being pulled under the rear of the treadmill, including 29 reports of injuries to children such as second- and third-degree abrasions, broken bones, and lacerations.”

CPSC acting chairman Robert S. Adler said in a statement, “I am pleased that the U.S. Consumer Product Safety Commission and Peloton have come to an agreement to protect users of the Peloton Tread+ and Tread products. The agreement, which the Commission voted this morning to accept, requires Peloton to immediately stop selling and distributing both the Tread+ and Tread products in the United States and refund the full purchase price to consumers who wish to return their treadmills. The agreement between CPSC and Peloton is the result of weeks of intense negotiation and effort, culminating in a cooperative agreement that I believe serves the best interests of Peloton and of consumers.”

The recall includes some 125,000 Tread+ (the older system, renamed with the arrival of a new budget device) and 1,050 Tread models in the U.S., along with an additional 5,400 in Canada. The warning issued alongside the Tread+ recalls states, “Adult users, children, pets and objects can be pulled underneath the rear of the treadmill, posing a risk of injury or death,” while the Tread’s notes, “The touchscreen on the treadmill can detach and fall, posing a risk of injury to consumers.” 

Consumers will have until November 6, 2022 for a full refund. After that, the company will only issue an undetermined partial refund.

The company’s initial pushback owed, in part, to the fact that home fitness equipment has long been known to present safety concerns — particularly with small children and pets present. It seems likely that we’ll hear more on Peloton’s stance during tomorrow’s earnings call. The company had a banner 2020, due to the pandemic, but shares have dropped 8% on the news. Today also saw some key security concerns with its platform go public earlier today.

 

4 strategies for building a digital health unicorn

It’s an entrepreneur’s market in digital health today, with startups raising record-breaking funding at soaring valuations and debuting on public markets to eager investors.

According to CB Insights, as of March 3, 2021, there are 51 healthcare unicorns — “startups” — worth $1 billion or more around the world. Global venture capital funding, including private equity and corporate VC, into digital health was the highest ever in the first quarter 2021 at $7.2 billion, according to Mercom Capital Group.

The massive influx of capital to healthcare should not be surprising; the pandemic has made it starkly clear that digital health is the future of healthcare. To that end, we should anticipate additional healthcare exits worth more than $1 billion in the near term. Which again, is great for entrepreneurs — as long as they understand how hard it is to build a unicorn in healthcare. Today, becoming a unicorn requires founders who are long on vision and operational experience.

Today, becoming a unicorn requires founders who are long on vision and operational experience.

Company founders most often turn to veteran investors for help with grand-slam strategies to create the next healthcare unicorn. That’s why many of them seek counsel from the Merck Global Health Innovation Fund: Because we have the experience, resources, successful track record and networks to build real scale in digital health.

During the pandemic, lots of investors jumped in to invest in digital health for the first time. But we’ve been investing for more than a decade. Two of our portfolio companies, Preventice Solutions and Livongo, exited last year as unicorns, rounding out the $6.2 billion in digital health market value MGHIF has exited over the last two years. And we are expecting two more unicorn exits in 2021. But we’re not stopping there; we’ll be investing our $500 million fund in drone-supported supply chain technologies, telehealth, AI, digital pathology, remote clinical trials and Internet of Medical Things (IoMT).

Given our success, here are four instrumental strategies to building a unicorn in digital health that we know work.

Raise the “right amount” of capital to build the right company

We often ask entrepreneurs: Would you rather own 20% of a $50 million company or 5% of a $1 billion company? To most, the answer is obvious. In our experience, too many entrepreneurs worry about dilution and never raise the right amount of capital.

It’s well known that companies with rapidly growing revenues are valued at a premium — but it’s important to remember that this is hard to do in healthcare. Getting to scale takes time because healthcare is so complicated and involves so many stakeholders.

This startup wants to bring clarity to the complex world of IVF

About 180 million people globally suffer from infertility. In the United States, one in eight families have trouble conceiving. The statistics are only getting worse, as male infertility and miscarriages continue to increase.

Alife Health, a San Francisco-based startup founded by Paxton Maeder-York, thinks it can help. The startup wants to use artificial intelligence to increase fertility outcomes. Specifically, it wants to optimize in vitro fertilization, a fertility treatment that requires a series of expensive and emotionally-taxing procedures with varied success rates.

Founded last year, the startup just raised a $9.5 million seed round, led by Lux Capital. Other investment firms include Amplo, IA Ventures and Springbank Collective as well as angel investors such as Anne Wojcicki, the founder and CEO of 23andMe, Fred Moll, the founder of Intuitive Surgical and Auris, and Amira Yahyaoui, the founder of Mos and Sequoia Scout.

“I personally believe that improving the quality of care through personalized treatments and reducing costs by increasing the success outcome rate can be incredibly impactful here, not just for the broader population but also specifically for minority groups,” Maeder-York said.

The founder began his career building surgical robots to fight lung cancer at Auris Health which was acquired by Johnson & Johnson in 2019. Now, he’s onto finding a way to help physicians and patients go through the process of IVF.

FYI, IVF

In vitro fertilization, or IVF, takes on average three to six cycles to get pregnant, and each cycle can cost between $10,000 to $20,000 in the United States. Every woman who goes through the process has to be injected with hormones weekly or biweekly – and even then, success is varied. And beyond steep costs and a long process, anyone who goes through the IVF process often has to endure the emotional toll.

Alife Health could alleviate some uncertainty around the complex process if it succeeds.

Currently, there are startups that focus on disrupting IVF from its cost to its accessibility. Maeder-York thinks that there is no single point solution that can fix the process, so he wants to optimize each part, step by step, from education and awareness, and clinical workflows to the actual embryo selection.

While Alife Health’s long-term goal is to use AI in all aspects of the IVF process, at this point, the technology is only used in one step for Alife Health: the embryo selection process.

Alife Health plans to begin its AI-powered IVF solution through embryo selection. During IVF, future parents might create multiple embryos. It’s then on the doctor to look at that embryo image through a microscope and figure out which is most likely to survive, taking into account patient information.

Alife Health is inserting machine learning based on a massive set of historical data it has aggregated, into the embryo selection equation. Maeder-York said that they plan to use data to understand what the “optimal order of transfer is” and then improve chances of a pregnancy, so people don’t have to go through IVF for the third or fourth time.

“It’s been trained on thousands and thousands of images, knowing that this image and this patient turned into a successful pregnancy, “he said. Once machine learning finds a pattern it can move forward with a recommendation and help future parents prioritize which embryos to transfer.

Pandemic baby

Alife Health is not alone. Two other startups,Embryonic and Mojo, claim they have the AI needed to spot a healthy embryo and improve IVF success.

Israel-based Embryonic is in the early stages of its business and has minimal efficacy proof at this point. Mojo uses microscopy hardware and AI software to focus on sperm counts and then better pick strong sperm for the IVF. Internally testing of Mojo Pro shows that the system is 97% accurate compared to manual sperm counting.

Alife Health is a hardware agnostic program so unlike Mojo, for example, a provider doesn’t need to use or buy a special microscope to use its product.

Deena Shakir, partner at Lux Capital, is joining Alife Health’s board as part of the translation. Shakir said she spent over a year meeting with the team and other IVF-focused startups to develop her thesis before eventually cutting a check. She pointed out a number of reasons that Alife Health stood out to her, primarily its focus on an end-to-end solution at the IVF process, but also its clinician-friendly approach.

“Other kludgey solutions require additional interfaces, hardware, [and] time,” she said. “Clinicians don’t have an appetite for that in their daily workflows. It needs to be intuitive.”

Deena Shakir, partner at Lux Capital, and Paxton Maeder-York, founder of Alife Health

Along with being a software-only solution, Alife Health sees part of its competitive edge as its partnerships with clinics. It has spent years cultivating a network of IVF clinics – and their data on prior cases, treatments and outcomes – to get a representative set that could be used to help any person receiving IVF treatment, it says.

“Unfortunately, women have been consistently underrepresented in research and minority women, black women have been incredibly underrepresented in research,” Maeder-York said. “The fact that our data set is so well stratified and representative of these groups means that when we [see] a patient of one off these minority groups, we’re going to be in a really unique position to give them answers and personalized care.”

Alife Health declined to release information about the efficacy of its AI, and it is still yet to get regulatory approval. Fittingly, millions of dollars should help it get to this next, and crucial phase.

Forerunner’s Eurie Kim and Oura’s Harpreet Rai discuss betting on consumer hardware

There’s a stark contrast between Oura’s deck and the others we pored through on Extra Crunch Live. The slides CEO Harpreet Rai brought to the event were the clear output of a more mature and confident company seeking out its Series B. It’s a company with a focus, aware of where it wants the product to go and do (and it went there, announcing a massive followup round on Tuesday).

Then there’s that giant image of the Duke and Duchess of Sussex, with the company’s smart ring adorning Harry’s right hand. From there, it’s a parade of celebrity faces: Will Smith, Lance Armstrong, Bill Gates, Arianna Huffington and Seth Rogen, to name a few.

It’s clearly been a wild half-dozen years since the company was founded. Rai joined up in 2018, not long before the company embarked on its $28 million Series B. Forerunner General Partner Eurie Kim got on board during the round.

“[I] enthusiastically took the meeting and Harpreet shared his story and the story of Oura. The deck is what we talked through,” says Kim. “Because I was a consumer, it was just a no-brainer that I knew what he was trying to build. So we were very excited to lead the round.”

Kim and Rai joined us on Extra Crunch Live to discuss the process of taking Oura to the next level — and beyond — as the product found a second (or third) life during the pandemic through partnerships with sports leagues like the NBA. And as we’re wont to do, we asked the pair to take a look and a handful of user-submitted pitch decks. If you’d like your deck to be reviewed by experienced founders and investors on a future episode, you can submit it here.

On the hardness of hardware

By the time Oura sought out its Series B, the startup had already progressed pretty far. Kim compares the first-generation product (circa 2016 — predating both Rai and Kim’s time with the company ) to a “Power Rangers ring.” You’ve got to start somewhere, of course — and if nothing else, the admittedly bulky original edition of the product served as a powerful proof of concept.