This post was written by Adam Rosenberg, CEO of Rodin Therapeutics, as part of the From The Trenches feature of LifeSciVC.
Those of us in biotech tend to focus our attention on drug discovery and development, but it is also important to take note of important advances in orthogonal areas, such as digital health.
My last blog post (here) focused on the use of digital health technologies to help optimize clinical trial design and management, with an emphasis on CNS diseases. Given the high cost and high failure rate in clinical trials (true for all areas, and perhaps especially CNS), digital health holds the promise of deeper data collection and better understanding of pharmacological activity. This may result in a better success rate, given the high placebo effect (again, especially in CNS). At minimum, and presuming clinical validation, digital health can reduce the cost of trial
and burden of clinic visits – thus increasing recruitment rates and hopefully lowering costs.
Digital health is a broad sector, addressed from many modalities, perspectives and technology solutions. To better unpack the opportunities and challenges in the space, it helps to focus on specific applications, or on high-level trends. The last post focused on a specific application (clinical trial optimization). In this post, I’ll step back and look at a broader, yet still very relevant trend – the convergence of consumer-oriented technology and utilization in the more traditionally defined healthcare ecosystem, and whether it should be feared or embraced (or a little bit of both).
Even since my June blog post, there have been encouraging signs of increasing digital health adoption and investment. As just a few examples:
- eClinicalHealth and Sanofi announced successful completion of the first “fully remote” clinical trial
- FitBit hired a head of digital health to focus on partnering with pharma in clinical trials
- Rumors are emerging that Apple plans to launch a new health-focused device in 2017, along with the new iPhone, that will be “packed with sensors” to collect blood sugar levels and other vitals.
As broadly defined, the digital health sector is booming, at least in terms of dollars invested. In 2015, healthtech saw 265 completed VC deals, a much higher total than the 59 deals completed just five years earlier, according to the PitchBook Platform. And in the first half of 2016, digital health companies reported raising almost $4 billion, according to StartUp Health.
There is still considerable hype in the sector. Some of it is warranted, while some is overdone. Categorizing digital health into specific applications – and looking for trends – helps to separate the signal from the noise.
Defining Digital Health
It is tempting to categorize digital health into 2 main categories:
- fitness / wellness (such as FitBit or Strava)
- clinical / medical (such as remote monitoring of chronic diseases)
These categories generally hold, despite the many obvious nuances. One is consumer-driven, while the other requires multiple stakeholders (payor, provider, pharma, patient etc). Thinking about the digital health category in this way can help influence business model, product design, reimbursement strategy and numerous other key considerations.
And of course there is overlap – fitness and wellness can lead to disease prevention, and in some cases, to symptomatic improvement.
Exercise and Disease Prevention
Many leading clinicians, payors and even pharma are becoming more intrigued by moving “beyond the pill,” encouraging patients to adopt a more unified and holistic approach to healthcare and disease management.
This supports the potential for convergence of consumer devices and clinical interventions, with exercise a primary example.
Recent papers support the idea that exercise can help, among other things:
If exercise (or even basic measures of activity) can help delay or prevent costly and difficult human conditions, and digital health can help track and encourage exercise, convergence of consumer-oriented devices and clinical care seems inevitable.
Exercise as A Therapeutic Intervention
Even post-diagnosis, certain disease areas require coordinated behavioral and therapeutic interventions to achieve desired patient outcomes.
If a patient takes a statin to lower cholesterol, for example – but still eats a 4-egg lobster omelet for breakfast every morning and 20-ounce ribeye steak for dinner every night – results are likely to be less impressive than for someone who chooses a somewhat more balanced nutritional approach to go along with their daily pill.
For these disease areas – say, diabetes or obesity – a coordinated approach that includes activity tracking and other wireless behavioral data points make perfect sense.
And for other diseases – such as Parkinson’s disease and Multiple Sclerosis – movement itself is a clearly defined endpoint, and also a potential intervention.
An example is Theracycle, a somewhat low-tech but also low-risk and high-value stationary bike with an assisted motor, built for people living with movement disorders and injuries. This is not a typical digital health company, but rather an example of how exercise can help with a multi-modality disease management strategy, and provide more power to therapeutic interventions, physical therapy and the like. In fact, researchers at the Cleveland Clinic showed that forced, assisted exercise improves motor function in Parkinson’s patients.
So, wearable fitness and wellness devices (including watches and other wrist monitors, chest heart-rate-monitors, and even smart clothes) – or fitness apps, such as Strava – may all play a role in a coordinated disease management strategy.
It therefore makes perfect sense that over time, we will continue to see consumer and clinical applications converge. This makes some healthcare professionals uncomfortable, however…and while it is typically easier to be skeptical than to embrace the risk and uncertainty of new approaches, the discomfort is not without some merit.
Concerns – Accuracy, Marketing and the Deluge of Data
Accuracy remains a key issue around digital health devices – especially for drug developers and regulators considering adoption of new devices and approaches. As noted in my last blog, confidence continues to lag around data collection accuracy, and multiple studies have confirmed legitimate questions about device reliability.
Given their scale and resources, the reality is that big companies have an inherent advantage in securing clinical validation, as evidenced by Philip’s recent launch of a connected suite of remote monitoring devices. More validation is needed, before healthcare will truly embrace convergence.
But just like BYOD (bring your own device) eventually won out in the corporate smartphone world, convergence is inevitable. And just as consumer device manufacturers need to recognize the need for clinical-level validation, once accuracy is established, healthcare professionals need to be willing to consider new approaches.
Anyone with healthcare familiarity knows that consumer-oriented companies looking to enter the healthcare market need to be exceptionally careful about the claims they make around their product. There are more examples here than can, or need to be, listed.
The easiest way for consumer-oriented companies to successfully market is simple; just don’t make claims suggesting that your product can predict, prevent or cure disease.
Strava for example has done a great job building a community around its exercise tracking, and has now expanded to include a GPS tracking service geared towards safety, so that friends and family can check in on a runner or cyclist’s location. As cycling has recently been suggested to extend lifespan, could Strava partner with leading academic medical centers to help power longitudinal studies? Sure. But I think they are much better off continuing to deepen and refine their core customer offering; the jumping off point to clinical applications then becomes that much more compelling.
FitBit is another good case study here. By starting with a consumer focus, they’ve now built a recognized brand and platform to enable potential expansion to clinical healthcare. Had they initially attempted to win both markets, one or the other side would have surely suffered – a less attractive form factor in an attempt to build in more clinical utility, for example.
Healthcare remains an enigma for consumer-oriented companies, and ratcheting back on hype can seem counter-intuitive to a consumer-focused marketer. But in healthcare, there is clearly greater risk from both a regulatory and adoption perspective in over-selling, or over-promising. Thoughtful and limited marketing is much more likely to lead to eventual buy-in.
- More Data ≠ Better Data
Many clinicians report being inundated with a deluge of data in digital health pilots. Thus, solutions need to be consolidated and presented in a thoughtful and actionable way. Meaningful and actionable outputs, precise analytics, a clean user interface – the layer on top of the data needs to be robust and reliable, and reflect the needs of both the user and the other stakeholders.
Applied to the convergence of consumer and clinical, this means that simply generating more data is not enough. In the consumer world, one might be able to look at a number of steps taken per day, and consider behavioral modification without much (if any) data analytics. In the healthcare professional world, there needs to be more inputs, and more of a clear and demonstrable tie to the desired health outcome. Again – there are many more stakeholders, and a consumer device cannot simply be picked up and implemented in a clinical setting…it needs to evolve towards more of a traditional medical device or diagnostic, supported by an analytical layer that makes sense across the full healthcare ecosystem.
Summary – Should We Fear or Embrace Convergence?
So we must continually work towards validation for reliable data collection, thoughtful marketing practices and robust yet actionable analytical tools. But assuming such a baseline, the convergence of consumer and clinical applications is a good thing for the digital health sector, and for healthcare more broadly.
Like any change in healthcare, it will take time, and there are sure to be some bumpy patches – with device accuracy likely to drive the most turbulence.
But as further evidence of convergence, or at least the perception of market opportunity made possible by convergence, Apple CEO Tim Cook recently suggested that patient-focused, non-reimbursed digital health “may even make the smartphone market look small” (here).
So, undoubtedly healthcare will look different 20 years from now, with hopefully greater adoption and coordination of accurate digital technologies. In the meantime, the benefits of digital technology should be increasing available across multiple healthcare sectors. And so long as market participants adopt reasonable controls and best practices, this should be embraced.
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