How wearables and mobile health tech are reshaping clinical trials

How wearables and mobile health
tech are reshaping clinical trials
April 17, 2015 | Guest post by Mike Capone
Life science companies are continuously looking for
ways to advance clinical research while simultaneously
improving the understanding of drugs they are
developing. One of the biggest issues for researchers
is the high failure rate of new drugs during clinical
development. The stakes are high in a global pharma
market that is expected to exceed $1.2 trillion by 2018.
The average cost of bringing a drug from development
to FDA approval is over $2.5 billion, according to a
recent study by The Tufts Center for the Study of Drug
Development. This figure includes costs for the drugs
that don’t make it through to the approval phase, and
the Tufts Center notes that higher drug failure rates
contribute significantly to increases in R&D costs.
But there’s a big opportunity here: If life science
companies can get enough insight early in
development, they can create a more efficient drug
development process and prioritize resources for the
most promising therapies. Big data analytics and new
clinical technology — such as mobile health solutions
and wearable devices — promise to significantly
change how trials are conducted and increase the value
of the data and insights that come out of these trials.
Advancements in computing power and predictive
analytics tools enable us to process vast amounts of
information and develop insights in mere seconds.
Technology’s role is to bring together disparate data
sources so the industry can share data and use
advanced analytics to make better decisions — all with
the goal of getting effective drugs to market faster.
For example, 23andMe, the Silicon Valley maker of
personalized genetic tests, has hired Genentech R&D
executive Richard Scheller to lead a new therapeutics
group that will use the company’s archived genetic
data to find correlations and patterns across different
disease states in an effort to develop its own therapies.
And other industry partners are already working
together to figure out how to best deploy wearable
devices to patients and link the data from these
devices to traditional clinical data to measure
changes in patient behavior and use the information
for regulatory-acceptable decision-making. Recently,
Medidata (my company) and Garmin worked together
to incorporate activity trackers into clinical trials.
Garmin’s activity tracker measured steps taken,
distance, calories burned, and hours slept to capture
patient data during clinical trials 24/7, without the
clinic visits. And companies like Vital Connect have
received FDA clearance to use their biosensors to
capture clinical-grade biometrics.
A patient’s health is traditionally measured in the
clinic, but the life science industry is approaching an
age where it can connect to a new class of behavioral
data that has never before been accessible. Both of
the above examples have led to increased patient
engagement during clinical trials and ultimately bigger
and smarter data, all of which are crucial to discovering
groundbreaking treatments.
When you ask a patient how they feel, you get subjective
responses. Subjective data is useful in science, but
objective data is always better. The life science industry
can now gather new kinds of objective data through
mobile devices and activity trackers. This provides a
real-world, real-time measure of patient physiology
and how a drug affects quality of life — an increasingly
important measure for pharmaceutical companies,
regulators, and insurance companies.
This is evident in something as simple as the six-minute
walk test, which has been used for years in clinical trials
involving cardiovascular, respiratory, and central nervous
system diseases as a valid proxy for disease severity.
There is nothing mathematically or scientifically wrong
with the test, but with new technology we can capture
a more comprehensive measurement of patient health.
Instead of putting patients in front of a doctor for a
six-minute snapshot of their ability to walk, patients
can now wear a device that continuously measures their
activity and provides a complete picture of movement
without visiting the doctor’s office. Patients don’t have
to disrupt their day, and physicians and researchers can
be armed with much richer, more nuanced data than a
six-minute test.
Apple’s recent unveiling of ResearchKit that will use iOS
apps for medical research signals an interest across
industries in the value of patient-direct data.
Mobile devices and big data analytics can also
significantly diminish the burden on patients. Wearable
devices can reduce the number of times patients
need to go to a clinic and can provide a better, fuller
picture of physiological data needed to measure
a drug’s impact, minimizing needless testing on
patients. GlaxoSmithKline, for example, spoke at the
South by Southwest conference last month about its
interest in the use of biosensors for clinical trials to
improve data quality. Implementing these biosensors
would not only lead to increased data but would also
reduce interruptions in a patient’s day through remote
monitoring. Technology could therefore improve the
patient experience in clinical trials at large.
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Ultimately, if life science companies can show not only
that their drug is effective in treating a condition but
that it also dramatically improves a patient’s quality
of life, it can help regulators make better decisions
about which drugs to accelerate to market and can help
differentiate a drug from other “me too” compounds.
But we’ll only see this change if there is buy-in from all
key stakeholders. When regulators are more comfortable
with new approaches to clinical development, pharma
companies will be more likely to use new technology and
big data analytics in their studies. In parallel, regulators
will show more willingness to accept these approaches
when pharma shows a commitment to introducing
standardized approaches backed by strong scientific
evidence.
Mike Capone is Chief Operating Officer at Medidata,
where he plays a central role in product and solution
development, professional services, go-to-market and
day-to-day operations. Before Medidata, Mike spent
25 years with ADP — one of the world’s largest B2B
software providers — where he held positions in product
development, information technology, and operations.
This article originally appeared on VentureBeat.