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  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  

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

There  has  to  be  a  befer  way.  

is  now  Open  Source!  

No-­‐brainer,  zero  cost!  

Ehm..  wait  a  minute…  

February  2012  

Janssen  makes  a  bold  move.  

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  

VUmc

Sanofi

Recombinant / Deloitte

University of Michigan

Thomson Reuters Pfizer Astra

Zeneca

CDISC

University of Luxembourgh

Philips Johnson & 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  

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  

eTRIKS  Consor6um  

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

Growing  TraIT  project  team  

EUR  16  million  /  4  years  

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  

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)  

Pseudonymization

Public  Data  

BIMS  

Day  to  day  virtual  collabora6on  

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  

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.  

Galaxy  Toolshed  

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  

Pa6ent  Level  View  

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  

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!