Presentation to the California Emerging Technology Fund Board on June 21st Regarding Digital Disruption of Health Care

1. Quan%fying
Health:
Digitally
Disrup%ng
the
Health
Care
System
Jerry
Sheehan,
Chief
of
Staff
California
Ins%tute
for
Telecommunica%ons
and
Informa%on
Technology
[Calit2]
Presenta%on
to
California
Emerging
Technology
Fund
Board,
June
22nd,
2012

2. My
Car:
An
Analogy

3. Calit2’s Digitally Enabled Genomic Medicine View of The Future
is Emerging
July/August 2011 February 2012

4. Quan%fying
My
Weight
Technology
used,
Withings
Scale,
see
hLp://www.withings.com

5. Quan%fying
My
Ac%vity
and
Caloric
Intake
Source:
Bodymedia,
see
hLp://www.bodymedia.com

6. Quan%fying
My
Sleep
Technology
used,
Zeo,
see
hLp://myzeo.com

7. Making
a
Game
of
My
Measurements
Technology
used,
Nike+Fuel
Band,
see
hLp://www.nike.com/fuelband

8. Data
Fuels
Scien%fic
Discovery

9. Many
Users,
Rich
Data,
Big
Data
Challenges
• 23&Me:
– 150,000
Users
• Nike+
Users:
– +5M
Users
Source:
BodyMedia
Blog

10. The
World’s
Most
Self-­‐Aware
Man?:
The
Atlan%c
July-­‐August
2012
July-­‐August
2012
hLp://www.theatlan%c.com/magazine/archive/2012/07/the-­‐measured-­‐man/9018/?single_page=true

11. A
Quick
Message
from
the
Measured
Man

12. The
Exposome
“Genes
load
the
gun,
Environment
pulls
the
trigger”
–
Francis
Collins,
MD,
PhD

13. The
Exposome
Historical
approaches
to
measuring
environmental
exposures
and
behaviors
-­‐
• Self
report
via
quesEonnaires
every
few
day
or
months
(if
that…)
• Biomarkers
(e.g.
blood,
urine)
of
exposure,
some
good
but
others
that
are
oNen
indirect
and
imprecise
or
focused
on
only
one
or
two
outcomes.
• Direct
measurement
of
the
environment
across
a
broad
geographic
area
yielding
only
crude
inferences
about
person-­‐
level
exposures
in
Eme
and
space.
Moreover,
these
are
almost
always
focused
only
on
air
and
water.
Dr.
Kevin
Patrick,
UC
San
Diego
BUT…MILLIONS
OF
NEW
SENSORS
AND
DEVICES
CHANGE
THIS
AND
CREATE
UNPRECDENTED
OPPORTUNITIES
FOR
POPULATION
LEVEL
SENSING
AND
INTEVENTION

14. PALMS
Personal
AcEvity
LocaEon
Measurement
System
• Funded
by
NIH/NCI
Grant
1
U01
CA130771-­‐01
Genes,
Environment
and
Health
Ini%a%ve
(GEI)
• Kevin
Patrick,
Jacqueline
Kerr,
Fredric
Raab,
Greg
Norman,
Barry
Demchak,
Ingolf
Krueger,
Suneeta
Godbole

15. PALMS
Fuses
Physical
Ac%vity
Data
with
GPS:
Showing
How
and
Where
PA
Occurs
Heart
rate
shown
in
Google
Earth
resting
light
moderate
vigorous

16. PALMS
Can
Place
These
Data
Within
GIS
To
Provide
CONTEXT
Heart
Rate
Fused
with
Land
Use
from
ESRI
ArcGIS
Heart rate
shown in
ESRI ArcGIS
against land use

17. K.
Patrick
|
Slide
17
Determine
Indoor
/
Outdoor
Research
QuesEon:
Is
Time
Spent
Outdoors
Related
To
Cancer
Outcomes,
Mental
Health
Status
Or
PolluEon
Exposures
Of
Interest?
Tracking indoor
and outdoor time
30 second epoch
Indoors
Outdoors

18.
Merged
GPS
&
AcEvity
Data
Research
QuesEon:
Which
Park
Features
Support
the
Most
Physical
AcEvity?
Sedentary
Light
Moderate

19. PALMS
Users
Worldwide
((5
–
7
days
of
data
for
1800+
par%cipants)
As
of
6/1/2012

20. Ci%Sense
Always-­‐on
Par%cipatory
Sensing
for
Air
Quality
Principal
Inves%gator:
Bill
Griswold,
Computer
Science
&
Engineering,
UC
San
Diego
Co-­‐Inves%gators:
Sanjoy
Dasgupta,
Tajana
Rosing,
Ingolf
Krueger,
Hovav
Shacham,
Kevin
Patrick

21. Measuring
Air
Quality
in
San
Diego
10
EPA
Sensors
3.1
Million
Residents
4000
Square
Miles

22. The
Ci%Sense
Project:
A
UCSD/NSF
Project
contribute
Ci%Sense
EPA
distribute

23. Ci%Sense
Hardware
The
Sensor
Smart
Phones
for
Data
Storage/Analysis
Temperature,
Humidity,
Barometric
Pressure
3
Electrochemical
gas
sensors:
CO,
NO2,
Ozone

24. Aggregated
User
Data
&
User
Feedback
“I
guess
I
always
just
thought
of
the
atmosphere
as
being
evenly
mixed
but
it
is
not”,

25. The
Looming
Data
and
Computa%onal
Challenge
In
Health

26. You
Are
A
Superorganism:
Your
Body
Has
Ten
Microbes
For
Every
Human
Cell!
Firmicutes
Are
the
Dominant
Phyla
in
the
Human
Microbiome
Source:
Science
v.330,
p.
1619
(2010)

27. Integra%ve
Personal
Omics
Profiling:
1000x
the
Leading
Edge
of
Data
Today
Cell
148,
1293–1307,
March
16,
2012
• Michael
Snyder,
Chair
of
Genomics
Stanford
Univ.
• Genome
140x
Coverage
• Blood
Tests
20
Times
in
14
Months
– tracked
nearly
20,000
dis%nct
transcripts
coding
for
12,000
genes
– measured
the
rela%ve
levels
of
more
than
6,000
proteins
and
1,000
metabolites
in
Snyder's
blood

28. UCSD
Next
Genera%on
Sequencer
Example:
Professor
Trey
Idekar
Leichtag/Sequencer
Storage
Skaggs/Users
Next
Gen
Sequencers
Generate
~1TB/Run
Calit2/Storage
SDSC/Triton
Source:
Chris
Misleh,
Calit2/SOM

29. New
NCBC:
integra%ng
Data
for
Analysis,
Anonymiza%on,
and
SHaring
(iDASH)
• Data
Exported
for
Computa%on
Elsewhere
– Users
download
data
from
iDASH
• Computa%on
Comes
to
the
Data
– Users
access
data
in
iDASH
– Users
upload
algorithms
into
iDASH
Private
Cloud
at
SD
Supercomputer
Center
Medical
Center
Data
HosEng
• iDASH
Exportable
Cyberinfrastructure
HIPAA
cerEfied
facility
– Users
download
infrastructure
–
Source:
Lucila
Ohno-­‐Machado,
UCSD
SOM
29
funded
by
NIH
U54HL108460

30. The
Future
of
Health
is
Understanding
Networks
Source:
New
England
Journal
of
Medicine,
Network
Medicine-­‐From
Obesity
to
the
Diseasome”,
July
2007
Editorial
by
Dr.
Albert-­‐Laszlo
Barbasi