Digital Health: Emerging States

On a recent walk about to get up to speed in the rapidly changing field of digital health, we biopsied the latest thinking by many of the most engaged minds in order to develop a strategic map of promising innovation and investment entry opportunities. Our stops included: Qualcomm Digital Health Summit, the Samsung Developers Conference, Singularity University’s exponential health leaders, Johns Hopkins Bloomberg School of Public Health mHealth program, JPMorgan Life Sciences Meeting, Rock Health, Citrix Accelerator, Leavitt Partners and AMA Summit on Digital Health, the Digital Health Track of BIO 2015, MIT Hack@Medicine event, UCSF Digital Health Summer Summit, IMEC Technology Partners and CEO conference, and the Data Sciences program at the Jet Propulsion Lab at CalTech. And you think YOUR feet are tired!

We met with management of leading entrepreneurial companies including LinkedIn, Welldoc, Teledoc, Doctor on Demand, Doximity, Health Engine and FitBit; leading health IT investors in our ecosystem at numerous venture capital firms; key management and board members at Merck, JNJ, Lilly, Novartis; health insurer Aetna; medtechs from BD and BSX; execs at providers Mayo Clinic, Geisinger Health, JHU, Stanford, The Methodist Hospital, USC, Kaiser Permanente; and Milken Institute Foundation.

So that you don’t have to retrace our steps, we’ll share some highlights here.

Digital Medicine vs. Digital Health: Yes, Virginia, there is a difference. In fact, there’s a significant distinction between Digital Medicine and Digital Health. Digital Medicine requires an evidence base and is data-driven. Doctors engage, use and prescribe these tools to improve health outcomes, to pursue value-based reimbursement and to gain the benefits of stickiness and retention for their patients/consumers. And what happens when we aggregate data and get a glimpse into never-seen-before information? We arrive at insights that address the triple aim of better care, lower cost, and higher quality, in pursuit of better value. That, in a nutshell, is Digital Medicine. Digital Health is, well, everything else.

Capital Flows: Digital Health is coming of age. Starting with capital flows, 1H 2015 venture dollar flows were summarized by PWC Money Tree, NVCA, Thomson Reuters and Rock Health. In 2014, venture firms in Digital Health invested $4.3B, and that flow continues apace in 2015. In fact, 9% of all venture capital invested in 2014 poured into Digital Health. (FYI, that’s more than the previous three years combined). Investment returns are beginning in the sector as the J curve is reached and sizable IPO exits (five in 2014 and five so far in 2015) have materialized, among them Fitbit and Teledoc. It’s interesting how Fitbit won in only five years, reaching $1B in revenue, an operating profit, and an installed base of >20 million by taking a narrow fitness focus, addressing the fit and the worried well. While one-dimensional, when its qualitative trend data is combined with smart phone data, EHRs, and more, a powerful network effect is realized. Fitbit’s opportunity now is to figure out how to engage next; hiring a Chief Medical Officer isn’t a bad idea. In telemedicine, Teledoc floated its IPO and reached a valuation of >$1B. When investing, the only return that counts is the one you realize. Well, these firms are rewarding investors with returns and the market with innovation and value.

Deal Flow: We heard from established venture firms active in the sector that they are seeing two or more digital health startups/week (and some 600 each in the past 18 months). In some ways, it’s a massive failure of the market. IMS reported that they count 16,000 apps addressing healthcare, depending on how you define healthcare, and >1000 wearables. That poses two big challenges: 1) how does one sort the useful from the frivolous; and 2) how do we get the useful ones to the right people?

Design: Jawbone designer Yves Behar emphasized that when the design doesn’t force users to change habits or workflow, the product can create efficiency, adoption and delight, and unlock pent-up latent demand (i.e., new categories of explosively growing markets). At MIT Hack@Med, we learned about powerful design and ideation methods to explore patient and consumer engagement. Many now appreciate that design using behavioral economics incentives can make a significant contribution to improved health outcomes. A popular use case with data to support it is pre-diabetes and the management of diabetic patients.

Stay tuned in the coming months for more, centered on teams, business models and curating. In the meantime, we’ll leave you with our overall observation that the promise of Digital Medicine is starting to become reality. Some great minds out there are finding new ways to equip doctors and enhance the patient-doctor-provider-community relationship.

Spurring Innovation in Value-Based Health Care

The health care industry is undergoing a fundamental shift by moving from fee-based to value-based care. As we explained in our most recent blog post, the focus of value-based care is not on volume, but on the quality of services provided — and ultimately, better health outcomes. And it cannot come soon enough.

In January, we saw UnitedHealth’s move from fee-based to value-based payments to the tune of $43B+; now Anthem is making a $40 billion commitment to increase value-based payments to medical care providers. But, for every health care giant making a positive change, there are hundreds sticking their heads in the sand. It might surprise you to know that the U.S. currently spends 17.9% of its GDP on healthcare — more than any other country in the world— yet underperforms relative to other countries when it comes to health outcomes, access, efficiency, and equity. Fee-based medicine is no panacea.

Now, it’s not necessarily about spending less. There is a case to be made for paying an even greater percentage of U.S. GDP to health care. Better investment in the health and well-being of our nation’s population should lead to longer, more productive lives, which could accelerate overall GDP growth: a win-win scenario. But it’s not just about investment. We will need to do a number of things differently to really embrace and promote value-based medicine.

To spur health care innovation in the U.S., we must take a systematic approach to the problem. Let’s cover four steps of the process:

Step 1 — Go wherever the best people are. Design is a people business, and this interdisciplinary field applies to health care as well. The best people work in high-density innovation ecosystems, actively experiment, and are consistent risk takers. Most work in proximity to venture capital, which offers multiple benefits: access to hands-on assistance and networking; local competitive strategy experts; and multiple firms that are leaders in strategic partnering. Six of the top 10 innovative firms are located in the Bay Area and two are in New York City; given the high-density ecosystems where they work, they readily acquire innovation that internal R&D departments may miss. As a result, innovation can rapidly reach scale and make the leap from output to outcome.

Step 2 — Use design principles to build prototypes of disruptive products and services. Design thinking is a formal method for practical, creative resolution of problems and creation of solutions, with the intent of an improved future result. It is a form of solution-based, or solution-focused thinking that begins with a goal (a better future situation) instead of solving a specific problem. We would do well to employ design thinking to accelerate innovation in value-based medicine.

Step 3 — Understand the physician, patient, family, and community relationship and then optimize the customer experience for usability, desirability, and satisfaction. In other words, create solutions that are empathetic to the needs of both doctors and patients.

Step 4 — Move quickly from research to product development. Develop revenue and scale rapidly, while committing to shorter innovation cycle times.

Step 5 — Rinse and repeat.

Now, Let’s walk in an institutional investor’s shoes for a moment. Due diligence isn’t practiced one investment opportunity at a time. Constant surveillance of companies and awareness of emerging trends is necessary to achieving the best deal flow. Of course, dealmakers place a lot of bets, so it’s important to ensure that many bets “fail fast” so they can concentrate their resources on the emerging winners. More often than not, those winners are the ones that innovate better and tie their solutions to what turn out to be really large markets and investment returns. Deciding which winners to “double down” on requires a quantitative, objective, hard-nosed project assessment, not a qualitative, subjective project assessment. There is no room for resource gaps, irreparable weakness, or a structural inability to achieve/maintain market leadership. This is investment, not gambling, so innovators must manage forward each design prototype through the gauntlet of a milestone driven, progressive risk reduction product development plan, to eventual liquidity or stop. Achieving optimal returns on investment portfolios require stepping away from ideas that fail to meet projections or critical milestones.

We, for one, embrace Google’s 10X thinking: it’s easier to make something 10X better than 10% better. This approach inspires creative thinking and reaching beyond status quo assumptions. 10X solutions are far more likely to attract risk and growth capital, revolutionize markets, and create entirely new product categories that can scale. And this is exactly the type of thinking we need to bring measurable disruption at the system level to health care delivery in the U.S.

Let’s get started putting more value in value-based medicine.

Big Data and the Shift Towards Value-Based Health Care

A properly designed health care system should deliver value for patients: high-quality, cost-effective care that includes both preventative medicine and treatment. Unfortunately, medical care today all too often rewards providers, payers, and biopharma for quantity, not quality. The more services doctors perform, the more money doctors and hospitals earn. And pharma earns a paycheck even if outcomes, side effects, or adherence is poor. This model yields more patient visits, more tests, and more procedures, but not necessarily better health outcomes. Case in point: the U.S. spends more per capita on health care than any other developed country yet has notoriously poor health outcomes.

The sad truth is, fee-based medicine isn’t just inefficient: it’s completely broken.

We know that throwing money at the problem isn’t working. We have to buck the status quo and move towards a value-based health care model. Value-based health care is aligned with the patient’s interests: providing high-value care, with the greatest possible health outcomes, at the lowest possible cost.

Last week Congress passed MACRA, repealing the flawed sustainable growth rate for Medicare payments to providers and paving the way to value-based medicine. And the movement is gathering steam; UnitedHealth Group recently announced it will increase value-based payments to doctors and hospitals by 20%, to over $43 billion. Detractors argue that value-based medicine, while good for patients, is not good for the health care system’s bottom line. Well, whether you like it or not, value-based medicine is definitely catching on, and it will disrupt all parties involved — physicians, patients, providers, insurers, technology innovators, and government agencies at the local, state, and federal levels.

So the real question becomes, “Is there a way to make value-based medicine benefit both patients and health care providers?” The answer is yes, thanks to data-driven discovery.

The data explosion in the health care industry gives us increasingly valuable insights that can spur innovation and create better outcomes. Let’s take the Human Genome Project: an international collaborative project to map the complete DNA sequence of human genetic information. By learning more about individual genes, researchers gained an understanding of why certain treatments work better for some people than others and how genes affect the way people respond to drugs (aka, pharmacogenomics). This paves the way toward truly personalized medicine, where patients receive highly targeted treatments that take their unique genome into account.

In search of other examples of Big Data being applied to medicine, we recently traveled to NASA’s Jet Propulsion Lab (JPL). JPL is a fellowship of 6,500 rocket scientists propelling technology forward that just added health care as an area of focus. The effort holds great promise: personalized medicine and cancer research are early waypoints on their exploratory roadmap. JPL’s researchers are experts in leveraging analytics to produce insights and innovations from complex data streams. What’s more, JPL’s approach focuses on “end-to-end observational systems” (i.e., the understanding of data at the time and place you can use it, and how to extract value in real-time from a cacophony of data streams).

Just imagine where this caliber of predictive analytics could take the mission of value-based medicine!

The amount of data on the Internet doubles every three years, so inventing and reinventing new paradigms of information and data science will be imperative. The health care data ecosystem is literally an ever-expanding treasure trove of opportunity. Instead of limiting ourselves to a laboratory-focused “bench to bedside” approach, we must now think “outside to bedside,” using constantly developing sources of rich, complex data to drive health care forward.

Of course, the JPL team doesn’t know how to bring a MVP (minimum viable product) to help a community oncologist make better decisions for her patients and achieve the outcomes of an academic medical center team. Needless to say, we have our own prospecting list of high-impact and high-priority health care data challenges for our design colleagues to rapid-cycle prototype and test.

We see a future that preserves the centrality of the doctor-patient relationship, where doctors continue as thought leaders in health care, with information at their fingertips that can drive new understanding of how to prevent and treat disease. We just have to figure out what to do first, and how to make our foresight actionable.

Leveraging data-driven discovery in pursuit of value-based health care success should yield many attractive investment opportunities. In our opinion —and for all of our sakes —it can’t happen fast enough.

JP Morgan 2015 and the “Failure Age”

Last month, the industry kicked off 2015 with the 33rd Annual JP Morgan Life Sciences Conference in San Francisco.  In our opinion, there is no international calendar event that rivals it for attracting execs from leading companies, entrepreneurs, investors, bankers, VCs and PE firms alike.  We all assemble to renew industry relationships, refresh our industry perspective, share ideas, and learn new things. Who could have foreseen that Genentech’s IPO would herald a new age of biology, biotech innovation, advances significantly helping patients, and a population of biotech billionaires in less than a generation? Reconvening each year enables us to reflect on our impact as well as the fortunes gained (and lost) since last we met, learn which predictions came true (and which did not), and discover who the emerging leaders are as ever shortening cycles of innovation and new product development ambush market incumbents.

What became clear at this year’s gathering is that biopharma is polishing breakthroughs across many disciplines: neuroscience; immuno-oncology (CAR-T); cell and gene therapy; gene editing; and addressing disease with new found success, including orphan diseases, Alzheimer’s disease, and drug-resistant infectious diseases.  One source credited 2014 with more than 900 M&A and IPO events for private companies in life sciences with a value exceeding $109B, and 167 exits for VC-backed healthcare businesses. By any account that’s a big year.

And then there’s the topic of new venture funding. According to analysts at PWC, NVCA, and Thomson Reuters, new venture biotech funding reached $5.96B in 2014, the largest in 20 years — with $2B of that occurring in the fourth quarter. People are placing big bets in life sciences once again it seems. Our Apple iPhone 6s and Samsung Galaxy 4s chronicled our daily activity (Doug averages 15,000 steps) as we raced from meeting to meeting.

As usual, our confirmation bias was in full motion. We spent most of our time talking about our winners, burying our losers, celebrating the unique diversity of our community and its prospects for incredible net growth, and hoping our insights and hard work will lead us to be the winners everyone talks about at next year’s conference.

It was truly energizing to see many in our global network, attend interesting sessions, crystalize new ideas, and make plans to catch up in more detail in the near future—the great dividend earned for participating in a vibrant marketplace. Of course, as heady and valuable as all that industry interaction is, we’ve found that some of the greatest learnings and insights accrue from post-event reflection.

In other words, “Wait, not so fast.”

Our industry, like most, is intent on focusing on the one shiny side of the coin (success), but the other side (failure) plays a role every bit as important. As a sanity check, we recommend everyone review the November New York Times piece by Adam Davidson, “Welcome to the Failure Age!” In this engaging article chronicling innovation from the industrial revolution forward, Davidson acknowledges the uncomfortable reality that success and innovation are unavoidably tied with failure.  He cites the Silicon Valley used equipment consolidator, Weird Stuff, as an illustration of this truth; the company recycles and resells materials from both successful and failed startups.

The life sciences industry is not exempt from this phenomenon. When products do make it out of the lab, as chronicled in the record 40+ FDA pharmaceutical approvals in 2014, they often fail expectations at market introduction, or as soon as a better product comes along.  When products do win, they often create broad failure among the competition. New technologies, such as DNA sequencing, genomics, data analytics, 3Dprinting, robotics, and digital medical records, make it easier and faster to displace the latest product introduction, leading to even more failure. So, as paradoxical as it may sound, the faster we succeed, the more failure we are bound to create as well. Our innovation economy depends on it.

Traditional pharma industry market leaders have seen steep declines in product development productivity because speed in innovation matters more than ever. We’re finding that corporate core competencies in the innovation that underpins growth now primarily reside in external networks — the seedlings are growing quickly everywhere, and big companies find themselves in the role of buying what they missed.

All this to say that we think 2015 promises to be a very interesting year for those capable of resilience in facing the vicissitudes of the innovation economy.  But first, we’re going to celebrate the efforts of some of the failures out there by visiting Weird Stuff to do some discount shopping.

How to Win the War Against Infectious Diseases like Ebola and the Flu

Ironically infectious diseases are better at waging war with human host resistance than humans have proven at wiping them out. Urbanization and near instantaneous population mobility are turning emerging pathogens like Ebola and ubiquitous pediatric enterovirus strains like EV-D68 into imminent global threats. And then there are the infectious disease killers — like flu — that many people think of as benign, despite CDC reports that 200,000 hospitalizations and 3,000 to 49,000 deaths each year in the U.S. stem from influenza.

Not that this is new news. Civilizations have been shaped over the millennia by waves of deadly pandemics caused by the black plague (Yersinia pestis), smallpox and influenza, as well as the crippling of polio and morbidity of malaria and dengue fevers. We just aren’t old enough to remember them.

 

The path to better outcomes in the war against infectious diseases requires focus on four things: investment, economics, collaboration, and risk management.

  • Investment — Achieve a reliable level of public support: for basic research; for the current generation of young scientists who invent and design the discovery platforms that precede product development; and for public health infrastructure, as Research!America advocates.
  • Economics — Develop sustainability principles in public policy, including incentives and value pricing for the field so the product engine can take off.
  • Collaboration — Develop the triple helix environment of collaboration between industry, academia and government labs, leaving ROI, mission and public incentives intact and leveraging each other’s skills and risk capital.
  • Risk Management — Insist on a de-politicized and sound regulatory process that effectively manages risk without strangling innovation (i.e., let them do their jobs).

While 5,000+ people in West Africa have died thus far from Ebola, that number pales in comparison to the 50 million deaths that occurred during the 1918 Spanish flu pandemic — and we have no assurance that such a superbug won’t reappear. We must get serious about vanquishing infectious diseases, and that means doing things differently. Humanity’s future depends on it. Join me.

The World of Nano in Medicine

As our team participates this week in some fascinating roundtable workshops at the 7th annual NanoGagliato conference in Italy — a wonderfully intimate gathering of thought leaders and creative thinkers committed to working together to solve crucial problems in health care — we’re struck by the immense value in multidisciplinary collaboration. Surrounded by thought leaders in the areas of nanomedicine, ethics, entrepreneurship and design, it’s amazing how many fresh, innovative ideas get generated in our working group discussions.

Revealing the world at nanoscale — as you can see by looking at Rita Serda’s scanning electron micrograph artwork on the pages of this site — is at once beautiful and powerful. From the discussions we’re having here at NanoGagliato, it’s clear that some interesting applications in nanomedicine are rapidly reaching commercialization —with enormous potential near-term health care benefits. We’d like to share some examples of what we believe are compelling nanomedicine applications to combat cancer:

Celgene/Abraxis BioScience has reached validation at scale for site-specific tumor drug delivery (with a form of paclitaxel albumin protein-bound particles). Antineoplastic chemotherapy drug Taxol, originally derived from the bark of the Pacific yew tree, has seen improved efficacy in some of the most common cancers — including lung, ovarian and breast cancers as well as Kaposi’s sarcoma — with a material reduction in dose limiting side effects such as lower blood counts, hair loss, temporary myalgias and peripheral neuropathy.

In the particle sciences arena, we’re encouraged to see nano iron materials that concentrate in solid tumors and can subsequently activate a tumor lytic response by a physical mode of action, targeting external NanoXray to selectively increase radiotherapy activity at the cellular level. MagForce and Nanobiotix are advancing this strategy to the clinic for enhanced delivery of targeted energy in the therapy of glioblastoma, sarcoma, head, neck and liver tumors. (Nanobiotix utilizes inorganic crystalline hafnium oxide, which readily enters tumor cells and interacts strongly with local radiotherapy while sparing the surrounding normal tissues, allowing the dose intensification needed for tumor treatment.  MagForce utilizes iron oxide nanoparticles coated with aminosilane, locally injected and locally retained, which allows thermal cell killing by repeat alternating high-frequency magnetic fields.)

Building on the work of scientists at MIT to unravel the mechanism of action (MOA) for gold particle transit into tumor cells, CytImmune and AstraZeneca are collaborating on promising product profiles. CytImmune has developed a nanomedicine platform that uses the tumor’s unique biology to gain entrance to the tumor and break down its defenses by disrupting the tumor’s blood vessel architecture, enabling other cancer therapies to reach and kill the cancer cells.

Additionally, the Houston Methodist Research Institute is doing some very interesting interdisciplinary work at the interface of engineering, math and biology where Mauro Ferrari’s team has created oncophysics-based multi-stage vectors (MSVs) to overcome tumor resistance mechanisms; they have design features that continuously bring active agents to the tumor microenvironment by creating a drug reservoir with first order delivery effects.  The strategy, based in part on silicon particles, has now reached readiness to move from bench to bedside and human translational clinical research.

We look forward to actively participating in the brainstorming sessions in the coming days at NanoGagliato. We have big, hard problems to solve, but with the right multidisciplinary collaboration, we expect we’ll make surprising progress. We’ll be sure to share insights here after the conference has concluded.

Ciao for now!

Cracking the Code

Our team recently finished Jim Mellon’s book Cracking the Code, his fourth co-researched and authored with Al Chalabi.  The premise is understanding the biotech revolution, how it is transforming our lives, and how to participate as an investor. Jim sees the context of the impact of understanding our DNA through sequencing advances and the human genome project. We couldn’t agree more, and found chapters 4 and 5 to be full of important insights.

We also see a paradox when moving from context to action. On one hand, the massive increase in sequencing speed and data analysis and the associated cost efficiencies have accelerated sustainably beyond Moore’s Law. These productivity disruptions are making the secrets of the human genome assessable. On the other hand, we in science are stunned by the newly recognized and beautiful inter-genomic complexity, its variability, the epigenetic ballet, the choreography of functional genomics, the biochemistry of the control of gene expression, DNA replication and nature’s DNA proof-reading errors known as mutations. These natural mutational experiments result in evolution, sometimes under Darwinian natural selection leading to adaptation and fitness, and sometimes just serendipity.

As the market allocates public and private capital to advance biomedical innovation, investors seek out actionable investment entry points aligned with their risk tolerance and time horizons for liquidity.  We like betting on the filters and lenses of smart, seasoned entrepreneurs who work with teams of leading biomedical, biophysical and computational medical scientists and engineers. Their insights will make sense out of nature’s “Grand Reveal” and lead to valuable products that address human goals and improve value in our healthcare economy. That’s where you’ll find us prospecting for innovation.