mHealth Israel_ Digital Medicine_Whitepaper_The Digital Medicine Chrystal Ball

1
Unlocking the Future of Real-Time,
Precise, Effective Healthcare
THE
DIGITAL
MEDICINE
CRYSTAL
BALL:
PRODUCED BY:
IN COLLABORATION WITH HOGAN LOVELLS & EVIDATION HEALTH

2
DIGITAL MEDICINE
IS THE FUTURE THAT
THE HEALTH INDUSTRY
HAS BEEN WAITING FOR
TO REALIZE THE NEXT
HEALTH REVOLUTION.
ABOUT THE AUTHOR:
Nicole Fisher is the founder and CEO of HHR Strategies, a healthcare and human rights focused advising firm. She is also
a senior policy advisor on Capitol Hill. Fisher runs a Health Innovation and Policy page at Forbes, highlighting ideas and
advising companies and people that are changing the health landscape, and is Executive Director of the nonprofit Global
Brain Health Coalition, while in tandem pursuing a doctoral degree in health policy at the University of North Carolina.
hhrstrategies.com

3
TABLE OF
CONTENTS
SECTION 1/
The New Frontier.: A Boundless Value Proposition....................................PG. 5
SECTION 2/
Emerging Models and Partnerships Are Worth the Risk...........................PG. 11
SECTION 3/
The Regulatory Environment’s Crystal Ball..............................................PG. 18
SECTION 4/
The Future Is Here.................................................................................PG. 22
REFERENCES........................................................................................PG. 27

4
While buzz phrases such as big data, population health, the
Internet of Things (IoT) and even digital health have been
snagging headlines and attracting investment dollars, we are
entering a space where data collection, biopharma products,
medtech and utilization of these technologies can facilitate the
creation of new business models, markets, revenue streams
and standards of care. All of this can improve health outcomes
and lower healthcare costs, but will also require new
regulations, agency approvals and health system integrations.
The convergence of new technologies, medications, therapies,
digital fields and the health ecosystem is reshaping the entire
landscape of healthcare—domestically and abroad. Thanks
to computers and technology, novel digital tools are
transforming the way we gather and store information, as well
as generating new kinds of medical knowledge. In fact, right
now, it is estimated that 6.4 billion internet-connected devices
are in use, up 30% from 20151
. Additionally, it is projected
that by 2020, more than 25 billion devices will be connected
to the internet2
. These tools are already turning personal and
clinical data, whether quantitative or qualitative, into entirely
new breeds of medical information that will transform disease
management and alter business models across industries.
In developed countries, we are on the brink of having real-time,
precise, effective medicine and healthcare practices.
Experimental and democratized information can now be
shared to improve health outcomes like never before.
Currently, 1 in 20 Google searches is now health related,
meaning the barriers to access health information are at an
all-time low, and indicating how engaged consumers are
becoming in their own health3
. However, the field of digital
medicine is still new, and has to be better understood before
it can thrive in current and future regulatory environments, as
well as deliver upon its potential of advancing clinical and
patient-centric care. While the field appears to become
more saturated each day, the business environment is still
emerging, and stakeholders must come together to create
partnerships and practices that execute on the potential.
Contrary to many of the terms used recently, such as
“mobile health” and “population health” which were ill-
defined and lacked standardization, digital medicine is
technology and products that are undergoing rigorous
clinical validation and/or that will ultimately have direct
impacts on diagnosing, preventing, monitoring or treating a
disease, condition or syndrome4
. Further, the last five years
have seen a shift from all things that fall into biotech and life
sciences to a more refined explanation of how to harness
data for cost-effective health services. We now enter a world
where digital medicine has begun to provide individualized
treatment through technological advancements such as
genomics, proteomics, metabolomics, biomarkers, sensors,
software and data collection methodology, promoting an
entirely new wave of health and care—one that will continue
to evolve and become increasing regulated in the coming
years5
. Digital medicine is therefore a more focused subset
of products with near-term potential in disease management.
Unlike digital health, a widely used term encompassing all
kinds of activity trackers, smart devices and wearable tech
that do not require clinical validation or U.S. Food and Drug
Administration (FDA) approval, digital medicine is more
narrowly focused on the rigorous clinical validation and
health system disruption by products and technologies6
.
These can be found throughout the ecosystem as
pharmaceuticals, medical devices, software, commercialized
goods or products still in trials.
THE DIGITAL MEDICINE
CRYSTAL BALL:
Unlocking the Future of Real-Time,
Precise, Effective Healthcare
It is time we agree on defining and refining the meaning of digital medicine, particularly as it pertains to the toys versus the
tools that will usher in a new age of healthcare. This will determine how the proper tools can lead to the most efficient and
effective R&D process, strengthen the patient-physician relationship, and simultaneously enable individuals to become
the CEO of their own health. We must join forces across public companies and private organizations to secure early
stage investments, maximize research and development (R&D) opportunities, and empower true innovation to prevail.

5
SECTION 1/
The New Frontier:
A Boundless Value
Proposition

6
Increasing access to preventative care, diagnostics and
treatments can drastically reduce healthcare costs. Although
the field of digital medicine is still in the early stages of
development, remote monitoring, telehealth, behavior
modification and screening through predictive analytics are
poised to change patient-provider relationships. In fact,
Goldman Sachs predicts that the United States alone could
save $305 billion in health spending by adopting digital
technologies that eliminate unnecessary or repetitive care,
especially those in office. They further claim that as much
as $200 billion of that cost savings will come solely from
the management of chronic diseases7
.
It is believed that diagnosing the top chronic diseases
(including diabetes, depression, heart failure, Alzheimer’s,
and obesity), then genotyping to understand which drugs
will work for an individual and monitoring them using
wireless technologies, will dramatically improve patient care.
Additionally, hundreds of major diseases have already been
deciphered through genomic understanding, and the ability
of healthcare providers to utilize this kind of information over
the last six years has begun to change society’s broader
understanding of the underpinnings of disease. Simple,
wearable technology has also empowered individuals to better
understand their daily activities and behaviors, leading to
sought-after changes in behavior that support better health.
As these tools and treatments become smarter and more
widely disseminated, costs will decrease and incorporation
into daily routines will become easier.
So, while the early 2000s saw increased technological costs
as one of the main drivers of health expenditures in the US,
many competitors for experimentation, best practices and
preferred equipment will ultimately streamline current inclusion
into practice and enable cost-effective solutions8
. According
to John Nosta, a thought leader in the digital space, “The
future of medicine is less about a single technological
advance but more related to a converging of multiple and
essential issues that are touching one another today. From
advances in diagnostic modalities to empowerment of patients
and caregivers, we stand at a true inflection point in human
history and clinical care. And grand unification theory of this
point is a dramatic shift from control in hands of few to the
engaged collaboration of multiple stakeholders driven by
technology, wisdom and human emotion9
.”
However, it is important to remember that technologies will
only be as successful as the people who use them and the
processes that enable them. Because of that, the Group
Managing Director of EBD Group Anna Chrisman contends
that, “The convergence of digital technologies and healthcare
opens up huge opportunities for partnering in the life sciences
that will result in innovative solutions with the aim of improving
patients’ lives. For several years, we have seen an increase in
partnering activity among traditional biopharmacos. And, we
anticipate that this trend will apply to digital medicine, as the
society demands for new solutions increases.”
Digital Medicine’s Impact on Clinical Trials and
Buying Technology
Inclusion of new technology and tools is gaining momentum
daily. But processes throughout the medical world are changing.
One of the biggest modifications occurring is in clinical trial
procedures. At the federal level, the Department of Health and
Human Services (HHS) has recently begun stressing the
importance of pragmatic trials over traditional randomized
clinical trials. These compare two or more treatments instead
of a treatment and a control group. Additionally, with the
introduction of new drug developments like biomarkers,
web-based trials and outsourcing patient testing, the
understood FDA process of the past has many new avenues,
all of which are designed to be faster, easier and cheaper.
Evidation Health, a US-based company focused on bringing
digital health—and primarily medical—solutions and
predictive analytics to the masses, claims that virtual clinical
trials are one of the best ways to see increases in speed and
massive reductions in costs, partially from better recruiting and
retaining of participants. In addition to virtual trials reducing
investments of time and money, they also reduce selection
biases associated with clinical trial sites. According to
Evidation President Christine Lemke, “There are actually things
we can fix, things we can democratize, to really help people.
And we can do this through digital advancements while still
respecting clinical guidelines.10
” She believes in a world where
we are less reliant on medications alone. By combining
technology to enable and empower people, with data
collection to connect with clinicians in unique ways, we can
drive behavior changes that lead to different outcomes. Being
able to execute trials and secure patents in countries around
the world also means more investment dollars and public
distribution before approval in the United States takes place.
Research and development (R&D) is similarly experiencing a
small revolution, as mergers and acquisitions (M&A) are
SECTION 1: THE NEW FRONTIER: A BOUNDLESS VALUE PROPOSITION

7
beginning to outpace R&D11,12
. This means a significant dollar
and focus shift is occurring for academic medical centers,
pharmaceutical companies and medical device developers.
Because in-house costs of experimentation, failure, and production
are so high, it has become easier to purchase successes and
work them into an existing portfolio. Simply put, it is much
cheaper to commercialize a product than build it from the
ground up.
M&A VERSUS R&D
Not so long ago, the health sector viewed mergers and acquisitions (M&A) as game changing. But over
the last few years, large organizations—public and private—have begun to see this as status quo. In pharma
alone, there was a 94% increase in deals between 2014 and 2015, resulting in 2015 seeing almost $60 billion
in deals13
. This is also being seen across innovative companies like Google (creator of Verily) and Apple, who
just announced their acquisition of Gliimpse14
.
The spike in M&A comes from drastic increases in research and development (R&D) costs that require many
experts, expensive labs and years of clinical trials. Instead, an organization can purchase an existing smaller
company, focusing on commercializing their work and integrating it into the existing platform15
. Further,
according to those in the pharma and device space, the ability to create the next “blockbuster” innovation
(those valued at over $1 billion) is getting more and more difficult.
But the merging of the old and the new can be exceptionally
difficult. We see this regularly in hospitals, clinics and biotech
companies around the US—many of which are experiencing
rapid M&A as larger organizations purchase their smaller
competitors as well as those who have met a need of theirs—
both within and between neighboring states. Hospitals have
struggled to integrate new software into their medical
practices, just as large corporations have struggled to
assimilate startup technology into their practices. Often this is
due to technological issues with merging systems. But other
times, it is due to push back from providers and staff. Learning
how to use new apps, equipment and log data is cumbersome
and consumes time—something doctors and nurses do not
have. Further, it has been challenging over the last decade to
Source: Rock Health tracking and analysis based on news reports
Note: M&A transactions totals and lists are not meant to be comprehensive; deals through June 30, 2016
https://rockhealth.com/reports/digital-health-funding-2016-midyear-review/

8
find common ground on what software systems to use with
competitive hospitals, health systems and the government
as a whole since the rise of electronic health records. Not to
mention the frustrations that occur when existing and actionable
information exists, but no two entities, providers or payers agree
on how to utilize the information16
.
Cost-savings and lives saved will be the ultimate metrics of
success for new tools and technologies in the health space, but
investment dollars can also tell us a lot about what the old and
new markets are interested in. For example, fundraising in
healthcare has always been difficult, as investors and venture
capitalists are risk averse, and we do not generally value health
the way we do other things17
. Despite that, Rock Health found
that, “The first half of 2016 came out on top in one aspect—a
record-breaking 151 companies raised more than $2M18
.” So
there is plenty to be optimistic about19
.
Economic Implications
Investment into digital tools and companies continues at a rapid
pace. According to a StartUp Health report, in the first six months
of 2016, investments were the strongest they have ever been,
with about $3.9 billion total invested compared to the previous
record of $3.5 billion in the first half of 201420
. Yet, the areas
of primary focus have not changed for the last few years. Patient
and consumer experience tops the list of investment markets,
followed closely by tools that aim to improve overall wellness and
those that target personalized medicine. The areas that have seen
the least amount of funding most recently include research and
population health.
While the last few years have seen overall positive trends,
investors in the health space have remained risk averse. This
is because return on investments can be exceptionally tricky in
health and the exorbitantly high costs associated with R&D. For
those who invest in digital and health spaces, not only is there risk
in return on investments, but also in uncertainty over the severity
of illness and effectiveness of treatment21
. This means that while
health-related investors are wary, they are interested in pursuing
products, technologies or companies that they believe offer a
high likelihood of success—and in many cases this means those
that are part of a large, more well-known organization.
HEALTH INVESTMENTS NOT SLOWING

9
Despite funding increases in digital medicine, it is important
to note that the number of deals is decreasing. This is due
to a couple of factors, but primarily driven by deals themselves
becoming larger. For example, a patient-scheduling app in
China, PingAn, has already secured a half billion dollar deal
in 2016, and New York insurance provider Oscar has secured
a $400 million deal. Mergers and acquisitions are also
driving the trend, because of the increasing costs of research
and development. Instead of spending more on R&D,
pharmaceutical and medical device companies can cheaply
acquire startups with good technology and integrate them into
their offerings. This lowers the number of competitors and
increases the cost of investment.
Human talent and workforce are also strongly influencing and
being influenced by digital medicine. While the US continues to
see San Francisco and New York City as the hotbeds of health
technology and innovation, new hubs are beginning to emerge
in this space such as San Diego, Boston, Minneapolis and
Chicago. Globally, we are also seeing rapid growth in large
countries like China and India, as well as smaller countries
like Germany and The Netherlands.
Source: PwC MoneyTree (latest available is through Q1 only); digital health data based on Rock Health data.
Note: Digital health only includes U.S. deals >$2M

10
Competitive Considerations
In addition to quality of and access to care, returns on
investments are a vital part of health care advancements
measure of success. This means that for returns on investments
and mass utilization, we need to lower the costs associated
with R&D and production, while simultaneously increasing the
depth and breadth of services provided. It also means that
we must find new ways to bridge the fast-paced world of
technological commercialization and the snail-like pace of
medical regulatory hurdles. Some of this can be done through
better business practices. In 2015, Nature Biotechnology
tackled the issue of how to build a better business model in
digital medicine22
. Their research highlights the unique role
that customization and personalization in health will have
on businesses and products. They note that the ability to use
algorithms in the tech space is old news (think Pandora music
playlists and Google ads), but that the health sector has
primarily focused on mass adoption as opposed to
customization. And that is changing quickly.
Because data can also be gathered at such a fast pace and
in high volumes, the cost of individual data collection is being
drastically lowered. This means that scaling the data we have
can help improve disease diagnostics, monitoring, tracking,
and treatments—all at much lower costs. For example, when
the first genome was sequenced in September 2001, the
cost was estimated to be $95 million23
. Fifteen years later in
September 2016, the cost is now less than $5,000, leaving
the market wide open for competition and paving the way for
novel advancements throughout the human body24
.
Despite greater access to data and patient willingness to
share information to become more active participants and
consumers of health, there is no one business model to
address the various demands in biopharma, medical device,
software and commercialization. What is consistent across the
health landscape is that those looking for future triumphs in
digital medicine must be experts in their technology as well
as the health need that is being met, and understand exactly
how the customer—patient or provider—will use it. They must
also have a delivery model that allows complete ease in the
consumer’s hands, all while collecting future data about the
user25
. Lastly, there has to be a feasible economic model that
works with the complicated validation and reimbursement
structures in the US government.
A RESEARCH LAB ON YOUR PHARMACY SHELVES
23andMe, a leading personal genetics company, has been on the forefront of meeting consumer needs
in an ever-changing health environment. Their company not only managed to market its genetic testing kit
directly to consumers in retail chains across the United States, but partnered with dozens of
other companies to generate and study the massive amounts of data it acquires26
. For example, partners
like Genentech and Pfizer use a research portal to access 23andMe data to study conditions such as
lupus, Parkinson’s disease and even asthma.

11
SECTION 2: EMERGING MODELS AND PARTNERSHIPS ARE WORTH THE RISK
SECTION 2/
Emerging Models
and Partnerships Are
Worth the Risk

12
Feasibility/preclinical
Tech
development
path
Medical
development
path
Digital
medicine
path
Digital Medicine
business model
Validation/clinical Market
Agile
Subjective success
metrics
Focus on ﬁnding users
Linear
Objective success
metrics
Little business model
exploration
Clinical-risk driven
Expensive
Science-driven
Regulated
Little business model
exploration
Few business models
Less market risk
Prototype and iterate
to gauge compliance
and patent routine
Embrace clinical path but
leverage cheaper data,
remote monitor for
speed and efficiency
Exploit post-market data
for product improvement,
potential revenue source
Creative business
models
Expensive
High market risk
Competitive
User-driven
Rapid and iterative
Business model
exploration
The flood of connected devices around the globe is changing
the interactions of consumers, patients, providers and payers—
each demanding more and more digital collaboration.
Interpretation and formation of conclusions from the massive
amounts of data will become vital for both real-time individual
care, as well as connectivity among the patients, providers and
payers. At present, not many medical or research organizations
are well equipped for the assault of data that will soon be at
their fingertips. However, creative advances are coming from
many new industries. And with increasing frequency, we are
seeing that the organizations poised to drive the future of digital
medicine are those that are looking into new business models
and seeking out nontraditional partnerships27
.
We are beginning to see industries of all kinds use health tools
and data to improve their performance and offerings. Sports
businesses like Major League Baseball (MLB) approved
multiple new technologies for players this year. The Motus
Baseball Sleeve will be worn to measure stress on elbows and
the Zephyr Bioharness will monitor heart and breathing rates28
.
Google is continuing its exploration into new realms that include
partnering with Novartis to create contact lenses that to help
manage diabetes29
.
EBD Group’s Anna Chrisman says, “Data analytics, predictive
analytics, and precision medicine have transformed the way
we approach patient care. Creating a viable regulatory and
commercial infrastructure for these technologies through key
partnerships and life science companies, government agencies,
investors, the patient community, and other stakeholders is
critical in moving towards the new era of digital healthcare.” She
adds that, “There are real partnering opportunities available for
biopharma and investors to get in on the ground floor,” and she
hopes to continue facilitating those who are doing so to develop
novel techniques.
NEW BUSINESS MODELS EMERGE
Source: Steinberg, D., Horwitz, G., & Zohar, D. Building a business model in digital medicine
Nature Biotechnology 33, September 2015: 910-920

13
partneringONE®
data: 2010 – 2015.
9% INCREASE IN
MEETINGS
PER PERSON
33%INCREASE
in biopharma delegate
participation overall from
2010 to 2015
take place on average in a
three-day period at BIO-Europe®
OVER 19,000
MEETINGS
business development executives, researchers, investors, and
other stakeholders, enabling us to facilitate collaborations that will
HELP BRING NEW THERAPIES AND TOOLS TO PATIENTS.
EBD GROUP’S NETWORK COMPRISES
OVER 35,000
44% INCREASE
in the number of partnering meetings
PARTNERING TRENDS
2010 – 2015

14
Partnerships such as these are harnessing a multitude of data
to create products that meet patient and clinical demand. For
example, a new collaboration between Google (the life sciences
division that is now known as Verily) and GlaxoSmithKline (GSK)
will aim to create a bioelectronics venture called Galvani. Its
goal is the development of an implantable that will alter nerve
signals, in addition to collecting data about the body’s neural
networks that can be shared with patients in real-time30
.
Private and public companies are not the only ones
creating new competitive spaces for digital medicine innovation.
Universities and research centers are joining the fray, citing that
there are a lot of funds to be gathered by tech transfer offices,
patents, and private sector partnerships. In one such case,
Texas A&M University brought Philips on board with a health
innovation project that will result in the creation of a campus
Center for Global Health and Innovation33
. The entire
premise is to “support public-private partnerships in rapid
design and testing of new ideas.” The importance of a
partnership like this is the ability of large, international
corporations and academic institutions to bridge patient
needs, consumer demands, funding resources, academic
rigor and cross-facility collaboration.
Rachel Sha, Senior Director, Strategy & Business Development, Integrated Care at Sanofi, goes be-
yond traditional enterprises and describes the importance of relationships with academic institutions
and hospital systems. Sanofi is working with a number of academic partners as well as payer-
provider groups in evaluating technology-enabled solutions, conducting big data analytics projects.
They recently announced two different collaborations with Duke Clinical Research Institute (DCRI)
and Center for Assessment Technology and Continuous Health (CATCH) at Massachusetts General
Hospital. According to Ms. Sha, “Data today also sits in many different silos. There is now a necessity
for new and old players to work collaboratively to pool this information to provide a more
comprehensive picture of health. In the future, we see patients having a much stronger voice in their
care, in sharing their data, and to influence research and development of new products, and that’s
how we approach facilitating new collaborations32
. ”
J&J has been a worldwide leader in the health space, utilizing public-private partnerships to achieve
success across many industries. These partnerships include Cancer Institutes, neuroscience companies,
biotech firms, small startups and schools of medicine31
. According to Cris De Luca, Head of Digital
Health New Ventures for Johnson & Johnson, “large companies are partnering with startups based on
their ability to move quickly, and gain access to top talent in cutting edge platforms—whereas startups
are gaining access to expertise, healthcare channels and regulatory know-how, while gaining broad
scale distribution potential.”
But those in the innovation labs aim to use digital medicine to continue focusing on what is most
important at the end of the day: the patient and the problem being solved by each partner, whether
they are a large company, a startup, a hospital system or an individual. In fact, the head of digital
medicine new ventures highlights that in the Boston/Cambridge area there is a particularly rich
community of “Doc-preneurs” …i.e., young clinicians that expect their workflow and tools to be
connected and simple… and have become so frustrated with both the clinician and patient
experience, that they are going off and starting companies with value-based foundations.
PUBLIC-PRIVATE PARTNERSHIPS

15
Source: Connecting Companies: Strategic partnerships for the digital age, a
report from The Economist Intelligence Unit, commissioned by Telstra, 2016

17
VALIDIC’S LESSONS IN CONNECTIVITY
As the biggest startup in the connectivity space, Validic is poised to experience the good and bad of
collecting, repackaging, integrating and disseminating personal health data across the health care
ecosystem—and all the regulatory hurdles that come with it37
. But this is not seen as a challenge according
to Marc Sebes, VP of Product Management at Validic. Marc provides the product leadership for Validic’s
portfolio of SaaS and Mobile platforms and drives the strategy behind the company roadmap
for integration38
.
Marc contends that what happens outside the lab is very different than what happens inside, and those are
the things that we need to be measuring. He believes Validic will open up all new ways to quantify data. This
in turn will lead to value-based care that treats areas we have previously failed at understanding such as
mental health, stress, sleep and medical adherence.
The Future in the Cloud
While brick-and-mortar hospitals will not disappear, mobile
devices and sensors mean that much of what was previously
done in a building can now be done with portable tools and
stored almost exclusively in “the cloud.” Essentially, we are
moving away from inpatient care and more towards
outpatient care. For example, previous inpatient activities such
as monitoring blood pressure, heart rhythm and rate, oxygen
saturation in the blood, and stress levels can all be done from
the comfort of one’s home using current technology and tools.
And as smart phones in particular become more prevalent and
user friendly, the ability to measure vitals, scan images and
share data increases. Additionally, smart phones and apps
make remote monitoring easier and diagnostic medical
equipment smaller and more portable.
“The field of social computing and machines has taken us into
a new era of communication and understanding of human
behavior and interaction,” says says Cris De Luca of Johnson
& Johnson (J&J)34
. He, like many in the field, also sees that as
data and connected devices become increasingly common,
everything from face-to-face communication to drug
development strategy can be generated, stored and
shared from the cloud35
.
It is important to remember, however, that not all individuals
have equal access to digital and cellular connectivity. One
study found that 70% of homeless individuals in the US who
presented at an emergency department had cell phones36
. Yet,
the same study showed that those without stable homes were
more eager to get health information via text or phone call.
Therefore, as the cost of devices decreases and the number of
cellular smart phones increases, infrastructures around mobile
communication can make even the most vulnerable and
disconnected patients leaders in their own health and care.

18
Toys versus Tools
Many “toys” are beginning to integrate into clinical grade
standards, however, despite some being powerful tracking or
diagnostics tools, most have not undertaken the process to
obtain FDA regulatory clearance or approval. Others are
primarily used for consumer purposes, and would never
qualify for clinical-grade usage. There are also examples that
fall into a grey area (many of which have been flooding the
market for the last few years) that track basic human behavior
such as steps and heart rate. These devices are difficult to
compare, even harder to validate and make such small
behavioral modifications that clinicians and researchers
cannot use the data to drive broader change. And the FDA
has taken notice. For example, the FDA has been honing its
approach to mobile apps by releasing documents that guide
developers. However, while these guidelines help categorize
certain applications, they are not all-encompassing of the
offerings saturating the market39
.
We are also seeing a rise in the use of these devices in fields
such as obstetrics and gynecology, where monitoring tools
for metrics like fetal heart rate or preterm contractions—that
are not quite clinical grade—are still being used to assist
underserved populations by utilizing data collection to move
towards clinical grade credentialing. While these devices are
controversial in the ever-changing government process of
approval, they are showing signs of improving care. The
data collected from such products can also be useful in
providing predictive analytics about human tendencies,
decision-making and actions, that can lead to improvements
in future products. As John Nosta puts it, “In the final analysis,
digital health devices must move from an athletic option to
a clinical imperative. We can accomplish this by the
application of simple and existing technology to more
revealing measurements—like tracking gate and tremor in
Parkinson’s disease—versus the ubiquitous and often
meaningless quantification of steps. Further, the emergence of
nanotechnology to provide systemic surveillance of real-time
physiology will transform the dust-collecting activity trackers
into lifesaving tools that will be a constant companion to
monitor and reveal a clinical crisis (MI or stroke) prior to its
overt clinical manifestation or the very early presence (stage
zero) of cancer.”
And, while the field is still very broad, distinctions will have
to be made about what the serious products that treat and
cure conditions are, and which are the novelty items that first
appeared in the market. Asher Rubin, Global Head of the
Life Sciences and Healthcare Industry Team of Hogan Lovells,
has taken a lead in helping his firm and clients make these
determinations. “We now have the ability to take the patient,
doctor, hospital, pharmaceuticals and devices, add them
together, and actually get better outcomes,” he says40
. But, he
also stresses that, “We need to put gates around the field, and
discuss what is a toy and what is real medicine.”
FITBIT: TOY, TOOL OR BOTH?
In the recent past, Fitbit activity trackers were a fun, highly commercialized product that fit into the category of
“toy” to most medical professionals. Despite their popularity for individuals and company wellness plans, the
data collected (usually a loose estimate of steps per day) was not valuable to clinicians.
However, as of March 2016, there were more than 21 clinical trials that were using Fitbit devices to measure
outcomes by control and intervention groups for a wide range of conditions41
. While the Fitbits themselves are not
regulated—nor do they diagnose or treat—they are proving to be potentially valuable tools in a third-party kind
of way. These uses might also lead to better patient adherence or advocacy. Despite these possibilities and
unknown future consumption of Fitbit data, almost all clinical and academic medical professionals still place
Fitbits in the toy category.

19
SECTION 3:
The Regulatory
Environment’s
Crystal Ball

20
STATES TAKE MATTERS INTO THEIR OWN HANDS
There are many “decision makers” and “gate keepers” in the health and technology arenas, the most
challenging of which might be the federal government. With partisanship at extreme levels, the current
political environment is placing heavy burdens on policymaking.
State-level governments have therefore begun taking matters into their own hands. For example, in early
2016 Massachusetts launched its own comprehensive digital health initiative43
. The goal was to create a
partnership between industry leaders, health leaders, state and local government that would foster better
patient care, grow the state’s health industry and hopefully enhance overall state economic development.
The current state of digital medicine is anything but static.
Connected devices and technological advancements are
quickly outpacing the regulatory bodies that oversee them, as
well as progressing on a day-to-day basis, making standards
and best practices difficult to maintain. Further, health reform
has introduced a fundamental shift into how healthcare will be
provided and paid for in the future, adding layers of
opportunity and challenges to the entire health ecosystem.
However, conversations have to begin moving away from
wearables and mobile health apps, as they are popular to
discuss in the health tech scene, but are not undergoing
clinical testing in agencies or part of the broader health policy
discussion. As digital health, medicine and data become more
sophisticated, the integration of technologies we didn’t have five
years ago will take us to a new place in care and rulemaking.
According to Unity Stoakes, Co-Founder and President of
StartUp Health, “In the recent past digital medicine was biotech
and life sciences. However, over the last five years, digital
innovation has crossed that definition into one that is very
much in the life science space and how we leverage data42
.”
And with that come entirely new processes and agency
involvement to control products and standardize care.
Yet, with all the changes on the horizon, the FDA is still the
regulatory body that looms over the digital medicine space.
FDA regulatory requirements ultimately result in each product
raising a unique set of complex questions that includes
understanding what data and evidence is needed for approval,
and how to meet those demands while making the products
work the way they are supposed to for the end user. But there
are still commonalities between tools that can serve to ease the
regulatory burden. “Whether the digital tools involve machine
learning for predictive model development based on sensor
data or simpler systems that trigger alarms and alerts based
on set thresholds for monitoring data, the ultimate goal is data
analytics,” contends Yarmela Pavlovic, member of Hogan
Lovells’ FDA medical device group. She goes on to assert that
despite how complicated things can get, “with all the different
inputs and outputs, the goal is still to predict, and ultimately
change behavior, and those commonalities can help companies
identify the right data collection and ultimately navigate the
most efficient regulatory pathway.”
Global, Federal and State…Oh My
For digital medicine to unleash its full potential and explore
unparalleled innovation, a regulatory framework must be in
place. Yet this has been exceptionally difficult in recent years
due to the speed at which technology has advanced, and the
differences in diseases and treatments. For example, breast
cancer is based on several different kinds of mutations of the
cells, as well as lifestyle factors and ethnicity44
. There is no one
solution for the disease. Therefore, research and funding that
facilitates understanding for diagnosis and treatment demands
different kinds of trials and practices. Add in that the research
and treatment for each kind of mutation may need to get
approval from a different agency—based on the specific trial or
product—and the number of decision makers adds up quickly.
SECTION 3: THE REGULATORY ENVIRONMENT’S CRYSTAL BALL

21
WHITE HOUSE TACKLES PRECISION MEDICINE
With the NIH poised to drive the future of precision medicine, there are task forces and federal agency
experiments popping up every day. Eric Dishman (who recently left Intel) has taken over directorship of the
White House-sponsored Precision Medicine Initiative (PMI) through the National Institutes of Health (NIH)49
.
In his January 2015 State of the Union address, President Obama announced the initiative with the hopes of
channeling America’s best and brightest into working on the improvement of healthcare throughout the nation
through the PMI Cohort Program. The administration believes that, “through advances in research, technology
and policies that empower patients, the PMI will enable a new era of medicine in which researchers, providers
and patients work together to develop individualized care50
.”
The team at PureTech, a Boston-based R&D and venture
creation firm, has been actively pushing for logical and clear
regulatory guidelines for everything from wearable sensors to
approval of health apps45
. The company believes that disease
management has to go far beyond the hype of “mobile health”
and pills of the past, but that it cannot do so without some
oversight. However, the variation that exists between countries,
the federal government in the US and even between states
within the US highlights just how far we have to go to reach
standardization and best practices.
While the FDA has been slow to regulate requirements and
clearance procedures for certain types of products and apps,
and creating more leeway in certain kinds of clinical trials,
other agencies are quick to step in46
. For instance, outside of
FDA jurisdiction the Federal Trade Commission (FTC) has begun
cracking down on health products that make potentially false
claims. The FTC feels that it is their job to protect patients from
the snake oil, but also to try to refrain from hindering innovation.
Hogan Lovells’ Melissa Bianchi explains that the US has created
a patchwork of rules for different sectors. “The evolving nature
of digital medicine can lead to some uncertainty about which
laws apply and when, and change is likely to be slow,” she
says. The Health Information Portability and Accountability Act
(HIPAA), for example, is a law designed to protect patient health
information and records when the internet was just beginning47
.
While many organizations—old and new—hang their hats on
being HIPAA compliant, the law applies only to some digital
health products, and there can be a lack of clarity on how to
package, repackage and share health data under the varied US
laws that may apply. What adds another layer of complexity is
what other government agencies become involved with the
bundling and sharing of personal information. For example, a
new player in the digital medicine space is the Federal
Communications Commission (FCC), which is in charge of
communications through all forms of radio, television, wire,
satellite and cable, and now using their Connect2Health task
force to investigate the intersection of health and
broadband technology48
.
Privacy and Precision Meet
Although the opportunities gained through smart devices and
apps will improve individual and community health status, there
are many upcoming security and privacy concerns that will have
to be addressed. Online platforms and smart devices collect
many kinds of data from users, only some of which users are
aware of. Further, obtaining informed consent through various
new methods of information collection can be near impossible.
And, even when information is anonymized, geographic and
behavior data can be traced in ever-changing ways.
This is evidenced by the growing number of initiatives and
investments by the federal government in this space. For
example, the White House sponsored a Precision Medicine
Initiative that has rapidly grown in scope and size over the last
two years51
. In his 2016 State of the Union address, President
Barack Obama also called on Vice President Joe Biden to lead
a “moonshot” on cancer, aimed at curing cancer52
. In both

22
instances, the administration took a firm stance that the
future of healthcare can be much better than it is today.
It can be focused at the individual level, and it can be
done through digital medicine and data. The actions
also show what a priority digital medicine will be at the
federal level going forward. However, this means that
in the coming years precision medicine will need to be
better defined and understood53
. The organizations and
people working in the field will need to ensure that swift
progress is continually made, but that the movement
does not get lost in the vagueness that healthcare
often sees.
This will also help with future concerns associated with
reimbursements. A significant challenge for digital health
technologies is whether and how they will be paid for.
Melissa Bianchi notes that, “In the current environment,
even as the healthcare system is evolving, we do not know
how digital medicines will be paid for.” She poses that
one of her client’s biggest concerns is how—as we move
towards a value-based and outcome-based payment
structure—we will show value through things such as
adherence improvements, preventative medicine and
qualitative enhancements, and whether we will be able
to use the data necessary to do so.

23
SECTION 4:
The Future
Is Here

24
SECTION 4: THE FUTURE IS HERE
Digital medicine is the actual use of digital
technologies to achieve scalable medicine
enabling a new wave of solutions which
are currently on the market and specifically
targeting chronic disease and improved
outcomes. Examples range from home
diagnostics and telemedicine to artificial
intelligence and genomic manipulation to
software packages and commercialized
health tracking sensors, all of which will
require stringent—and evolving—
clinical approval.
While digital health has become a useful
term for the health and technology industries
to latch onto as a common catch word, it
has been used variably. Digital medicine
incorporates the broad use of software,
mobile, social, wearables, 3D printing,
sensors, IoT, machine learning, advanced
analytics and health informatics—packed into
tech-enabled solutions. And these products,
devices, technologies and innovations will
prove to have immeasurable improvements
for health and wellness across populations.
Digital medicine will also pose new solutions
in health system workflows and administration
that decrease costs and democratize
health information.
Emerging diagnostic and therapeutic tools
have the potential to change the entire field
of healthcare forever. Yet, as new technologies
materialize, healthcare delivery and
experiences will transform in ways that
cannot be predicted. This means that there
will continue to be vast amounts of uncertainty
in the digital medicine space. But in addition
to the uncertainty in this space, there is a
tremendous opportunity and potential.
In order for new technologies and
innovations to achieve their potential impact,
it will require all of the different stakeholders,
such as developers, clinicians, scientists,
investors, government agencies, academic
institutions and patients to collaborate in new,
meaningful ways that will ultimately benefit
us all. So while the path is unclear and the
challenges may be many, digital medicine is
the future that the health industry has been
waiting for to realize the next health revolution.

25
Meet innovative companies in this emerging field as well as potential
collaborators featured in this whitepaper at Digital Medicine Connect,
a one-day partnering event taking place during BioPharm America™
on September 15, 2016. Learn more
AT BIOPHARM AMERICA™

26
REFERENCES
1 Gartner, Inc. Gartner Says 6.4 Billion Connected “Things” Will Be In Use in 2016, Up 30 Percent From 2015 [Press Release]. November, 2015.
http://www.gartner.com/newsroom/id/3165317
2 Barker, Colin. 25 billion connected devices by 2020 to build the Internet of Things. ZD Net. November, 2014.
http://www.zdnet.com/article/25-billion-connected-devices-by-2020-to-build-the-internet-of-things/
3 Lovelace, Berkeley. Google to offer better medical advice when you search your symptoms. CNBC Health Care. June 2016.
http://www.cnbc.com/2016/06/20/google-to-offer-better-medical-advice-when-you-search-your-symptoms.html
4 Shaffer, D., Kigin, C., Kaput, J. and Gazelle, G. What Is Digital Medicine? Studies in Health Technology and Informatics, 80, 195–204. 2002.
http://www.ncbi.nlm.nih.gov/pubmed/12026129
5 Buell, John M. The Digital Medicine Revolution In Healthcare. Reprinted from Healthcare Executive. Jan/Feb, 2011.
https://www.ache.org/abt_ache/JF11_F3reprint.pdf
6 Elenko, Eric., Underwood, Lindsay and Zohar, Daphne. Defining Digital Medicine. Nature Biotechnology 33, May 2015: 456-461.
http://www.nature.com/nbt/journal/v33/n5/abs/nbt.3222.html
7 Roman, David H., Kyle D. Conlee, etc. The Digital Revolution comes to US Healthcare. Goldman Sachs, Internet of Things, Vol. 5. June 2015.
http://www.scbio.org/resources/Documents/Internet%20of%20Things%20-%20Volume%205%20-%20The%20Digital%20Revolution%20comes%20to%20
US%20HC%20-%20Jun%2029,%202015%5B1%5D.pdf
8 Sorenson, Corinna, Michael Drummond, and Beena Bhuiyan Khan. Medical technology as a key driver of rising health expenditure: disentangling the relationship.
Clinical Economics and outcomes research: CEOR 5. May 2013: 223. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686328/
9 Interview with John Nosta, President of NostaLab. HHR Strategies. August 2016. http://nostalab.com/
10 Interview with Christine Lemke, President of Evidation. HHR Strategies. July 2016. https://www.linkedin.com/in/cklemke
11 Mullett, Craig. Why an M&A growth strategy trumps R&D. Branison Group. July 2016.
http://branison.com/downloads/why-an-m&a-growth-strategy-trumps-r&d.pdf
12 Fisher, Nicole. Are M&A Replacing R&D in Pharma? Forbes. April 2015.
http://www.forbes.com/sites/nicolefisher/2015/04/22/are-ma-replacing-rd-in-pharma/#771ce728cb57
13 Reuters Healthcare. Sanofi chairman says acquisitions not ‘indispensable’ for future. March 2015.
http://www.reuters.com/article/sanofi-sa-ma-idUSL6N0WW0CQ20150330
14 Farr, Christina and Sullivan, Mark. Apple Acquires Personal Health Data Startup Gliimpse. Fast Company. August 2016.
http://www.fastcompany.com/3062865/tim-cooks-apple/apple-acquires-personal-health-data-startup-gliimpse
15 Fisher, Nicole and Liebman, Scott. Are M&A Replacing R&D In Pharma? Forbes. April 2015.
http://www.forbes.com/sites/nicolefisher/2015/04/22/are-ma-replacing-rd-in-pharma/#2d49d6a2cb57
16 Rhyee, Charles, Wachter, Zachary and Auh, James. Digital Medicine: Beyond The Molecule. Cowen and Company. April 2016.
file:///Users/uncsupport2/Downloads/16-04-18%20-%20Digital%20Medicine%20Ahead%20Of%20The%20Curve.pdf
17 Norris, Jonathan and Kristina Peralta. Trends in healthcare investment exits 2015. Silicon Valley Bank. 2015.
https://www.svb.com/uploadedFiles/Content/Blogs/Healthcare_Report/healthcare-report-2015.pdf
18 Mom, Mitchel and Adams, Ashlee. Digital Health Funding 2016 Midyear Review. RockHealth. July 2016.
19 Baum, Stephanie. Former Lumata COO leads pharma-backed investment firm targeting digital health startups. MedCity News, July 2016.
http://medcitynews.com/2016/07/pharma-backed-investment-firm-targeting-digital-health-startups/?rf=1
20 StartUp Health, LLC. A 2016 Midyear StartUp Health Insights Report. July 2016. http://www.startuphealth.com/content/insights-2016q2
21 Echazu, Luciana and Nocetti, Diego. Priority Setting in Health Care: Disentangling Risk Aversion from Inequality Aversion. Health Economics (22), January 2011.
https://www.researchgate.net/publication/228071416_Priority_Setting_in_Health_Care_Disentangling_Risk_Aversion_from_Inequality_Aversion
22 Steinberg, David, Horwitz, Geoffrey and Zohar, Daphne. Building A Business Model In Digital Medicine. Nature Biotechnology, 33(910-920), September 2015.
http://www.nature.com/nbt/journal/v33/n9/full/nbt.3339.html
23 President Obama’s Precision Medicine Initiative. The White House, Office of the Press Secretary, 30 January 2015.
https://www.whitehouse.gov/the-press-office/2015/01/30/fact-sheet-president-obama-s-precision-medicine-initiative
24 National Institutes of Health. National Human Genome Research Institute. DNA Sequencing Costs. May 2016.
https://www.genome.gov/sequencingcostsdata/
25 Nazar, Jason. 14 Famous Business Pivots. Forbes. October 2013.
http://www.forbes.com/sites/%20jasonnazar/2013/10/08/14-famous-business-pivots/#5867e43220ca
26 Sullivan, Mark. 23andMe has signed 12 other genetic data partnerships beyond Pfizer and Genentech. Venture Beat. January 2015.
http://venturebeat.com/2015/01/14/23andme-has-signed-12-other-genetic-data-partnerships-beyond-pfizer-and-genentech/
27 MobiHealth News. Pharma’s Digital Health Initiatives Move Into Commercialization. April 2016.
http://mobihealthnews.com/content/depth-pharma%E2%80%99s-digital-health-initiatives-move-commercialization
28 Moynihan, Tim. A Tiny Sensor Could Help End The MLB’s Epidemic Of Elbow Injuries. Wired, July 2016.
http://www.wired.com/2016/06/motus-pro-sensor-baseball-mlb/

27
REFERENCES
29 King, Leo. Google Smart Contact Lens Focuses On Healthcare Billions. Forbes, July 2014.
http://www.forbes.com/sites/leoking/2014/07/15/google-smart-contact-lens-focuses-on-healthcare-billions/#60e9b76b1dfa
30 Parmar, Arundhati. A Q&A with Verily’s CTO about the Galvani joint venture with GSK. MedCity News, August 2016.
http://medcitynews.com/2016/08/verily-gsk-galvani/?rf=1
31 Johnson & Johnson Collaborations. http://www.jnjinnovation.com/collaboration
32 Interview with Rachel Sha of Sanofi. HHR Strategies. August 2016.
33 Versel, Neil. Philips sets up global health innovation center at Texas A&M. MedCity News. June 2016.
http://medcitynews.com/2016/06/philips-health-innovation-texas-a-m/?rf=1
34 Interview with Cris De Luca of Johnson & Johnson. HHR Strategies. August 2016. http://www.jnjinnovation.com/cris-de-luca-ms
35 Baum, Stephanie. Pharma’s digital health ambitions: Where are the opportunities and what’s hindering progress? MedCity News. July 2016.
http://medcitynews.com/2016/07/pharmas-digital-health-ambitions/?rf=1
36 Post, Lori Ann, Vca, Federico, et al… New Media Use by Patients Who Are Homeless: The Potential of mHealth to Build Connectivity.
Journal of Medical Internet Research.
September 2013. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3786002/
37 Enrado, Patty. Validic’s Digital Health Platform Realizes the Promise of Digital Health Innovation through Connectivity. mHealth News. November 2014.
http://mobihealthnews.com/news/realizing-promise-digital-health-innovation-connectivity-key
38 Interview with Marc Sebes, Vice President of Product at Validic. HHR Strategies. July 2106. https://www.linkedin.com/in/marcsebes.
39 Berkery, Molly and Roher, Jed. Mobile Health Technology: It’s A Phone, It’s An App, It’s A… Medical Device? The National Law Review. August 2016.
http://www.natlawreview.com/article/mobile-health-technology-it-s-phone-it-s-app-it-s-medical-device
40 Interview with Asher Rubin, Global Head of the Life Sciences Industry division of Hogan Lovells. HHR Strategies. July 2016.
http://www.hoganlovells.com/en/asher-rubin
41 Comstock, Jonah. 21 clinical trials that are using Fitbit activity trackers right now. MobiHealth News. March 2016.
http://www.mobihealthnews.com/content/21-clinical-trials-are-using-fitbit-activity-trackers-right-now
42 Interview with Unity Stoakes, Cofounder and President of StartUp Health. HHR Strategies. July, 2016. https://www.linkedin.com/in/unitystoakes
43 Massachusetts.Gov. Office of the Governor. Massachusetts Launches Comprehensive Digital Health Initiative. January 2016.
http://www.mass.gov/governor/press-office/press-releases/fy2016/mass-launches-comprehensive-digital-health-initiative.html
44 National Cancer Institute. The Genetics of Cancer. Cancer.Net. August 2015.
http://www.cancer.net/navigating-cancer-care/cancer-basics/genetics/genetics-cancer
45 Elenko, Eric., Austin Speier and Daphne Zohar. A regulatory framework emerges for digital medicine. Nature Biotechnology 33, July 2015: 697-702.
http://www.nature.com/nbt/journal/v33/n7/full/nbt.3284.html?WT.feed_name=subjects_computational-platforms-and-environments
46 U.S. Food and Drug Administration. Mobile Medical Applications. Guidance for Industry and Food and Drug Administration Staff. February 2015.
http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM263366.pdf
47 U.S. Department of Health and Human Services. Health Information Privacy. http://www.hhs.gov/hipaa/
48 Federal Communications Commission. Connect2HealthFCC. https://www.fcc.gov/about-fcc/fcc-initiatives/connect2healthfcc
49 National Institutes of Health. Precision Medicine Initiative. January 2015. http://syndication.nih.gov/multimedia/pmi/infographics/pmi-infographic.pdf
50 National Institutes of Health. Precision Medicine Cohort Program. January 2016. https://www.nih.gov/precision-medicine-initiative-cohort-program
51 The White House. The Precision Medicine Initiative. January 2015. https://www.whitehouse.gov/precision-medicine
52 The White House. Cancer Moonshot. 2016. https://www.whitehouse.gov/CancerMoonshot
53 Yu, Jun. Precision Medicine: What do we expect in the scope of basic biomedical sciences? Genomics Proteomics Bioinformatics 14(1). February 2016: 1-3.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792840/

28
Produced by EBD Group in collaboration with Hogan Lovells and Evidation Health.
Learn more about partnering opportunities in the digital health sector
at one of EBD Group’s upcoming events:
Digital Medicine Connect // September 15, 2016 // Boston, MA
Digital Medicine Showcase // January 10–11, 2017 // San Francisco, CA

mHealth Israel_ Digital Medicine_Whitepaper_The Digital Medicine Chrystal Ball

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (19)

Ähnlich wie mHealth Israel_ Digital Medicine_Whitepaper_The Digital Medicine Chrystal Ball

Ähnlich wie mHealth Israel_ Digital Medicine_Whitepaper_The Digital Medicine Chrystal Ball (20)

Mehr von Levi Shapiro

Mehr von Levi Shapiro (20)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

mHealth Israel_ Digital Medicine_Whitepaper_The Digital Medicine Chrystal Ball