How pre-competitive collaboration in the pharmaceutical sector through open source platforms enables joint innovation of academics, pharma, SMEs and non-profits.

1. TranSMART:
how
open
source
so3ware
revolu6onizes
drug
discovery
through
cross-­‐pharma
collabora6on
Kees
van
Bochove,
CEO
The
Hyve
October
23,
2013,
Princeton

2. The
Open
Source
Defini6on
1.
Free
Redistribu6on
2.
Availability
of
Source
Code
3.
Allow
Derived
Works
4.
Integrity
of
The
Author's
Source
Code
5.
No
Discrimina6on
Against
Persons
or
Groups
6.
No
Discrimina6on
Against
Fields
of
Endeavor
7.
Redistribu6on
of
License
8.
License
Must
Not
Be
Specific
to
a
Product
9.
License
Must
Not
Restrict
Other
So3ware
10.
License
Must
Be
Technology-­‐Neutral

3. Open
Source
• Source
code
for
so3ware
is
openly
accessible
and
reusable
for
everyone
• Contrasts
with
tradi6onal
IT
business
model:
selling
so3ware
‘in
a
shrink-­‐wrapped
box’
• For
IT
vendors,
revenue
is
earned
with
services
rather
than
with
products
• Example
of
well-­‐known
open
source
products:
Linux
(e.g.
RedHat,
Ubuntu,
Android),
Firefox,
WordPress,
OpenOffice,
VLC,
OpenStack

4. OpenStack
Contribu6ons
Source:
Bitergia,
hfp://blog.bitergia.com/2013/10/17/the-­‐openstack-­‐havana-­‐release

5. How
does
open
source
work
with
scien6sts
in
academia?
Let’s
zoom
in
on
a
well-­‐known
bioinforma6cs
problem

6. In
2003…
(Ancient
history;
before
Facebook)

7. Yet
Another
‘New’
Web-­‐based
Solu6on
for
the
Management
of
Microarray
Data
?!

8. Not
Invented
Here
Syndrome
Image
from
Rob
Hoo3,
CTO
Netherlands
Bioinforma6cs
Centre
hfp://nothinkingbeyondthispoint.blogspot.nl/2011/11/decision-­‐tree-­‐for-­‐scien6fic.html

9. Different
Non-­‐Func6onal
Requirements
• Bioinforma6cian
in
academics:
solve
a
novel
problem
or
at
least
create
a
novel
solu6on
that
has
publica6on
value
– So3ware
should
demonstrate
working
principle
• Bioinforma6cian
/
IT
Services
in
pharma/clinic:
– So3ware
should
allow
tes6ng
of
hypotheses,
and
should
be
well
tested,
maintainable,
extensible,
scalable
etc.

10. share
reuse
specialize

11. Sharing?!
Pharma
IT
as
the
proverbial
fortress.

12. • Browse
clinical
trials
• Import
/
load
clinical
trial
data
• Define
virtual
cohorts
• Perform
exploratory
analy6cs
• Search
/
view
published
analysis
results
• Support
for
'omics'
data
• Load
public
data
-­‐
TCGA,
1000
Genomes
$$
$$
$$
$$
$$
$$
• Browse
clinical
trials
• Import
/
load
clinical
trial
data
• Define
virtual
cohorts
• Perform
exploratory
analy6cs
• Search
/
view
published
analysis
results
• Support
for
'omics'
data
• Load
public
data
-­‐
TCGA,
1000
Genomes
$$
$$
$$
$$
$$
$$
$$$$$$$$$$$
$$$$$$$$$$$

13. There
has
to
be
a
befer
way.

14. is
now
Open
Source!
No-­‐brainer,
zero
cost!
Ehm..
wait
a
minute…
February
2012
Janssen
makes
a
bold
move.

15. TranSMART
Open
Source
History
• February
2012:
J&J
releases
tranSMART
as
open
source
on
GitHub
under
GPL
v3
• December
2012:
CTMM
TraIT
project
decides
to
use
tranSMART
as
core
infrastructure
component
• January
2013:
IMI
eTRIKS
starts,
uses
tranSMART
as
core
infrastructure
component
• February
2013:
kickoff
of
tranSMART
Founda6on,
U.
Michigan
publishes
PostgreSQL
port
• March
2013:
IMI
EMIF
kickoff,
tranSMART
is
used
as
data
integra6on
component

16. VUmc
Sanofi
Recombinant
/ Deloitte
University
of Michigan
Thomson
Reuters Pfizer
Astra
Zeneca
CDISC
University of
Luxembourgh
PhilipsJohnson &
Johnson
The Hyve
Amsterdam,
June
2013:
tranSMART
Workshop
Afendees
from
10
Pharma
companies,
11
University
Medical
Centers
and
12
IT
companies
hfp://lanyrd.com/2013/transmart

17. TranSMART
in
a
nutshell
• Datawarehouse
bringing
together
scien6sts
from
clinical
sciences,
preclinical
research
and
discovery
–
around
the
data
• Combina6on
of
internal
datasets
and
documents
with
public
datasets
and
knowledge
• Tailored
to
both
biologists/clinicians
and
bioinforma6cians
• Dual
nature:
in
use
for
transla6onal
research
in
both
pharma
and
hospitals/clinic

18. eTRIKS
Consor6um

19. tranSMART
Founda6on
Board
Brian
Athey,
PhD,
University
of
Michigan
Michael
Braxenthaler,
PhD,
Roche,
Pistoia
Alliance
Kevin
Smith,
MSIS,
University
of
Michigan
Ashley
George,
PhD,
GlaxoSmithKline,
Pistoia
Alliance
Keith
Elliston,
PhD,
Seneca
Creek
Research
Yike
Guo,
PhD,
Imperial
College
London

20. Center for Translational Molecular Medicine
(CTMM)
• Public-private consortium
• Dedicated to the development of Molecular Diagnostics and
Molecular Imaging technologies
• Focusing
on
the
transla6onal
aspects
of
molecular
medicine.
• 120
partners
– universi6es,
academic
medical
centers,
medical
technology
enterprises
and
chemical
and
pharmaceu6cal
companies.
• Budget
300
M€
• 22
projects
/
research
consor6a
• TraIT is the Translational Research IT project supporting these
projects with a joint IT infrastructure

21. TraIT February 2013: 26 partners
Growing
TraIT
project
team
EUR
16
million
/
4
years

22. CTMM
TraIT
Goal
• To
build
an
IT
infrastructure
for
transla6onal
research
for
all
20
CTMM
disease
projects
and
other
major
Dutch
ini6a6ves
and
ins6tu6ons,
such
as
all
UMC’s,
NKI,
De
Maastricht
Studie
etc.
• Data
integra6on
and
viewing
is
done
with
a.o.
tranSMART.
• Approach:
Think
big,
start
small,
act
now

23. TraIT
‘Founda6on
Team’
2 FTE
4 FTE
2 FTE
• Core
infrastructure
development:
adopt
&
adapt
tranSMART,
Galaxy,
OpenClinica,
BMIA,
etc.
• Distributed
Scrum
Team

24. TraIT
tools
&
applica6ons:
the
landscape
Hospital
(IT)
Transla6onal
Research
(IT)
data
domains
clinical
data
imaging
data
experimental
data
biobanking
integrated
data
transla<onal
analy<cs
workbench
HIS
PACS
LIS
Galaxy
tranSMART/
cohort
explorer
R
tranSMART/i2b2
datware
house
CBM-­‐NL
OpenClinica
NBIA
+
AIM
e.g.
PhenotypeDB,
Annai
Systems
e.g.
Galaxy,
Chipster
Samples
(IT)
P
s
e
u
d
o
n
y
m
i
z
a
t
i
o
n
Public
Data
BIMS

25. Day
to
day
virtual
collabora6on

26. Day
to
day
virtual
collabora6on

27. TranSMART
seems
to
do
well
and
certainly
has
a
lot
of
momentum
at
this
point.
It
s6ll
needs
a
lot
of
work
though,
to
ensure
long
term
success…

28. So…
is
open
source
a
silver
bullet
to
make
so3ware
collabora6ons
work?
Let’s
look
at
a
couple
other
projects.

29. What
about
all
these
great
FP6,
FP7,
IMI,
…
projects?

30. Source
code
of
major
projects
is
readily
available
on
GitHub

31. That’s
great!
But…
I’m
afraid
it’s
s6ll
up
to
you
and
me
to
put
the
pieces
together.

32. Phenotype
Database
Wrifen
in
Grails,
supports
several
types
of
omics
data,
provides
data
integra6on
and
visualiza6on,
has
R,
Groovy
and
PHP
API’s.
Very
similar
to
tranSMART
hfp://phenotypefounda6on.org

33. R
and
Bioconductor
Who
doesn’t
love
R?

34. Website
looks
as
if
dates
from
Stone
Age.
Must
be
those
LaTeX-­‐loving
physicists.

35. Very
ac6ve
community,
and…
lots
of
packages.

36. Governance
of
R
community
Brian
Ripley:
“The
R
Project
is
governed
by
a
self-­‐perpetua6ng
oligarchy,
a
group
with
a
lot
of
power.
R
was
principally
developed
for
the
benefit
of
the
core
team.”
As
cited
on
hfp://blog.revolu6onanaly6cs.com/2011/08/brian-­‐ripley-­‐on-­‐
the-­‐r-­‐development-­‐process.html

37. Galaxy

38. Galaxy
is
the
most
widely
used
open
source
bioinforma6cs
web
interface
AFAIK.
Probably
in
no
small
amount
thanks
to
their
con6nuous
dedica6on
to
improving
the
UI.
But
there’s
something
else.

39. Galaxy
Toolshed

40. I2B2
(from
Harvard)
is
deployed
in
~100
medical
centers
across
U.S.
I2B2
is
clinical
and
genomics
data
repository
and
an
important
cornerstone
of
tranSMART.

41. Apps
in
a
hospital:
SMART
• SMART
=
Subs6tutable
Medical
Apps
Reusable
Technologies
• Write
app
once,
and
run
it
on
any
SMART-­‐supported
EHR
system!
•
Interfaces
with
major
EHR
vendors
to
get
a
common
Applica6on
Programming
Interface
(API)
h?p://smartplaAorms.org
hfps://www.|ordnet.com/
workdetail/harvard-­‐medical-­‐school

42. Pa6ent
Level
View

43. App
inside
hospital
firewall:
Cardiac
Risk

44. • An
open
source
CMS
(Content
Management
System)
wrifen
in
Python,
nowadays
backing
thousands
of
produc6on
grade
websites
• Started
by
2
developers
in
2000,
now
an
ac6ve
open
source
project
with
hundreds
of
ac6ve
developers
• In
2004,
the
Plone
Founda6on
was
formed
to
formalize
IP
and
secure
the
future
of
Plone
• Plone
Collec6ve
has
hundreds
of
plugins

46. What
do
all
these
success
stories
have
in
common?
Bioconductor
Packages
Galaxy
Toolshed
Plone
Collec6ve
Drupal
Modules
SMART
Apps

47. Success
factors
Lessons
learned
about
open
source
projects
• Solve
an
unmet
business
need
• Strong,
ac6ve
community
• Engage
mul6ple
vendors
• Enable
real
6me
collabora6on
• Modular
architecture:
‘app
store’,
data
marketplace
etc.
• Sustainable
funding
/
business
model
• And
some
good
luck!