Diabetes Pro Quarterly - Spring 2017 - 7

PROFESSIONAL NEWS

Investable Opportunities: The Importance-and Challenge-of Health Care Data

The American Diabetes Association recently convened executives
with intimate knowledge of diabetes-related technology and
documented their insights on the role data will play in health
care in the coming years and how that role will affect investable
opportunities in diabetes diagnosis, management, and services.
The role of the U.S. Food and Drug Administration (FDA) in
navigating regulatory challenges alongside companies was a clear
central tenet of the discussion.
The panel included Wende Hutton, a general partner at Canaan
Partners; Ajit Singh, a general partner at Artiman Ventures;
Ruchita Sinha, director of health care ventures at GE Ventures;
and Don Turner, global head of commercialization at IBM
Watson Health. The panel was moderated by Brian Bertha, a
fellow at HITLAB and a member of the Association's National
Board and Finance Committee. The following narrative was
adapted from the discussion.

In November 2016, the American Diabetes Association convened a panel of
executives with intimate knowledge of diabetes-related technology, including
Wende Hutton, a general partner at Canaan Partners, and Don Turner, global
head of commercialization at IBM Watson Health, shown above.

Importance-and Challenge-of Health Care Data
Don Turner: At IBM, one of our focus areas is pioneering a
partnership between humanity and technology because, with the
right technological solution, we can improve lives on a global
basis. However, the inaccessibility of data impedes the delivery of
health care. It actually causes death. So, the faster we can leverage
cognitive technologies and data assets-insights, experience, care
models-the quicker we're going to make an impact on peoples'
lives. Several examples illustrate the hope for the future.
Drugs are expensive. Diabetes patients may know this better than
anybody else. And there's a reason for that: economics. Scientists
spend decades, in some cases, looking at these biochemical pathways. And, behind the scenes, financial people are running net
present value, or NPV, calculations. If it's positive, the drug gets
approved; if it's negative, it typically will not. Even if the drug
would improve peoples' lives, it doesn't get to market.
So, what are we going to do? We're actually going to create an
inflection point and positively affect that curve by introducing
advanced technology. Imagine trying to read 40 million medical
journal articles, 100 pages each-4 billion pages. It would take all

of us in this room, if we did nothing but read around the clock,
the rest of our lives. Watson can take that information and ingest,
interpret, reason, and position it for advanced insights in tens
of seconds. Tens of seconds. What typically takes many, many
years or decades can be diminished substantially. This is going to
reduce the cost structure, and it's going to improve the distribution of drugs.
Clinical trials are another very difficult area. It's difficult for
patients to find the right trial, but we have advanced analytics
technologies that can perfectly match a clinical study to a patient.
It's actually saved peoples' lives. The inverse of that is finding
patients for clinical studies. In one case I know, researchers
spent 8 months and only found two patients. That's unbelievable.
Imagine being able to find the right population in minutes by
pointing and clicking.
Another application is for doctors on the provider side. Imagine
being able to give guidance to those with diabetes or prediabetes
about what and when to eat. A lot of the ideas we heard today
are about things we actually have today. They're not perfect, but
we're also not trying to reach perfection. Instead, we set up a
learning engine. Let it go, let it learn. We work with great organizations like the Association that can truly advance the platform,
and that's why there's no doubt that we are going to materially
improve peoples' lives in early 2017 and beyond.
Hutton: In the next 10 years, data are going to lay an incredible
foundation for changes in care. Today, we still have physicians
looking at handwritten journal notes. That's inadequate. Diabetes
patients are actually awash in their own data. They're measuring
their blood glucose levels all the time. We should be able to take
the data from all the apps and devices that a patient interacts
with and pull it onto platforms that go into the right repositories-the cloud, analytics, and so forth.
Sinha: I completely agree. Today, when you log into Facebook
or Google, both of those applications are getting smarter. With
every word you type, it knows more about you; it tailors every
piece of content that is fed to you. The same thing will happen in
health care.
But first, we have to overcome the hurdles that are preventing
data sharing. It's much easier to share in the world of Facebook
or Google because the end person owns the data. In health care,
various manufacturers, pharmacies, and others own separate
pieces of that data, and they have no incentives to share it. They
are not talking to each other. So, investable opportunities exist
in tools and technologies, as well as incentive models that break
down those barriers and help accumulate these pieces of data so
that all these technologies start becoming effective.
Turner: One of my concerns is the regulatory barrier. Having
worked in a number of different industries, including banking,
which is certainly regulated, the risk aversion in life sciences and
health care is higher than any other. Obviously, we're dealing
with human lives, so it probably should be. But we're at a point
now where we're seeing data come together well. We're seeing an
continued on page 8

DIABETESPRO QUARTERLY

Table of Contents for the Digital Edition of Diabetes Pro Quarterly - Spring 2017