TranSMART: How open source software revolutionizes drug discovery through cross-pharma collaboration

TranSMART:

how
open
source
so3ware

revolu6onizes
drug
discovery

through
cross-‐pharma
collabora6on

Kees
van
Bochove,
CEO
The
Hyve

October
23,
2013,
Princeton

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

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

OpenStack
Contribu6ons

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

How
does
open
source
work
with

scien6sts
in
academia?

Let’s
zoom
in
on
a
well-‐known

bioinforma6cs
problem

In
2003…

(Ancient
history;
before
Facebook)

Yet
Another
‘New’
Web-‐based
Solu6on
for

the
Management
of
Microarray
Data
?!

Not
Invented
Here
Syndrome

Image
from
Rob
Hoo3,
CTO
Netherlands
Bioinforma6cs
Centre

hfp://nothinkingbeyondthispoint.blogspot.nl/2011/11/decision-‐tree-‐for-‐scien6ﬁc.html

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.

share

reuse

specialize

Sharing?!

Pharma
IT
as
the
proverbial
fortress.

• Browse
clinical
Brials
clinical
trials

•  trowse

• Import
/
load
• Import
rial
data

clinical
t /
load
clinical
trial
data

• Deﬁne
virtual
• Deﬁne
virtual
cohorts

cohorts

• Perform
exploratory
analy6cs

• Perform
exploratory
analy6cs

• Search
/
view
• Search
/
vanalysis
results
nalysis
results

published
iew
published
a
• Support
for
'omics'
data
or
'omics'
data

• Support
f
• Load
public
data
-‐
TCGA,
1000
G-‐
TCGA,
1000
Genomes

• Load
public
data
enomes

$$
$$
$$
$$
$$
$$
$$
$$
$$
$$

$$

$$

$$$$$$$$$$$
$$$$$$$$$$$

There
has
to
be
a
befer
way.

February
2012

Janssen
makes
a
bold
move.

is
now
Open
Source!

No-‐brainer,
zero
cost!

Ehm..
wait
a
minute…

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

Amsterdam,
June
2013:
tranSMART
Workshop
Afendees
from
10
Pharma
companies,
11
University

Medical
Centers
and
12
IT
companies

Recombinant
/ Deloitte

CDISC

Thomson
Reuters

Pfizer

Astra
Zeneca

VUmc
The Hyve

Sanofi
Johnson &
Johnson

Philips

University
of Michigan

hfp://lanyrd.com/2013/transmart

University of
Luxembourgh

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

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

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

TraIT February 2013: 26 partners

EUR
16
million
/
4
years

Growing
TraIT
project
team

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

TraIT
‘Founda6on
Team’

2 FTE
4 FTE
2 FTE

•  Core
infrastructure

development:
adopt
&

adapt
tranSMART,

Galaxy,
OpenClinica,

BMIA,
etc.

•  Distributed
Scrum

Team

TraIT
tools
&
applica6ons:
the
landscape

Hospital
(IT)

Transla6onal
Research
(IT)

data
domains

HIS

PACS

LIS

Samples
(IT)

BIMS

Public
Data

P
s
e
u
d
o
n
y
m
i
z
a
t
i
o
n

clinical
data

integrated

data

OpenClinica

transla<onal

analy<cs

workbench

imaging
data

tranSMART/

cohort
explorer

NBIA
+
AIM

biobanking

CBM-‐NL

tranSMART/i2b2

datware
house

R

experimental
data

e.g.

PhenotypeDB,

e.g.

Annai
Systems

Galaxy,
Chipster

Galaxy

Day
to
day
virtual
collabora6on

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…

So…
is
open
source
a
silver
bullet
to

make
so3ware
collabora6ons
work?

Let’s
look
at
a
couple
other
projects.

What
about
all
these
great
FP6,

FP7,
IMI,
…
projects?

Source
code
of
major
projects
is

readily
available
on
GitHub

That’s
great!

But…
I’m
afraid
it’s
s6ll
up
to
you

and
me
to
put
the
pieces
together.

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

R
and
Bioconductor

Who
doesn’t
love
R?

Website
looks
as
if
dates
from
Stone
Age.

Must
be
those
LaTeX-‐loving
physicists.

Very
ac6ve
community,
and…

lots
of
packages.

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

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.

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.

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

App
inside
hospital
ﬁrewall:
Cardiac
Risk

•  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

TranSMART: How open source software revolutionizes drug discovery through cross-pharma collaboration

What
do
all
these
success
stories

have
in
common?

Bioconductor
Packages

Galaxy
Toolshed

Plone
Collec6ve

Drupal
Modules

SMART
Apps

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!

• 
• 
• 
• 
•

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