8th Pharma Tech IT congress 16sep10

1. The Pistoia SESL
Project
An Emerging Vehicle for SESL Pilot
Pistoia Alliance Collaboration:
TheBiomedical Brokering Service
for a Pistoia Alliance
Ian Harrow, Wendy Filsell, Dietrich Rebholz Schuhmann
8th PharmaTech IT Congress http://pistoiaalliance.org
16th Sept 2010

2. Presentation Outline
• Pistoia Background
• SESL: Biomedical Knowledge Brokering
• The Knowledge Service Framework
• The Pilot
• Minimal configuration to test a brokering service
• SESL user interface Mock Up
• Project Timelines
• Summary
• Acknowledgements

3. Pistoia Background – How it all started
2007 2008 2009 2010 Now
Informal Met in Create Pistoia as Not Official 7 / 10 top Pharma as members
meeting Pistoia for profit company Launch 33 members
Stanhope Gate Domains Established
Pistoia
Lhasa Curzon
Informal Collaborations Collaboration/project meeting
Pistoia Description History
The primary purpose of the Pistoia Alliance is to
Initial Meeting with GSK, AZ,
streamline non-competitive elements of the life Pfizer and Novartis – outlined
science workflow by the specification of common similar challenges and
standards, business terms, relationships and frustrations in the Informatics
sector of Discovery
processes
Pistoia Goals The advent of Web Services and Web 2.0 allow for
decoupling of proprietary data from technology
• to allow this framework to encompass/support
most pre-competitive work between the Publicly available structural and biological DBs allow
organisations for a non-IP related analysis and as a scientific test
suite.
• to support life science workflow prior to
submission Sponsorship from R&D IS heads within Life Science
• to work with other Standards organisations industry

4. Pistoia Domains
Pistoia Domains group areas of interest, scope and deliver projects
Pistoia Domain – high level collection
Pistoia Groups – as of Working Groups with common themes
External
Groups
defined in byelaws Domain Allows governance across outside of
Steering a domain using Working
Pistoia
Board of Groups Group chairs and
Technical Committee reps
Directors Could:
• join Pistoia
Working The main project delivery • influence Pistoia
Working mechanism in Pistoia. All
Officers Groups members
Groups standards will be • influence through
(Operational delivered by WGs other standards
Team) groups and activities
Provide expertise for WGs • Collaborate on
and running Pistoia standards’ feasibility
Technical Pistoia Define: studies
•Requirements • Collaborate through
Committee Members •Technical Standards non-Pistoia
•Service Standards Standards initiatives

5. Pistoia Domains
Pistoia Domains focus on business workflows /supply chains
Enabling Knowledge and Information Services
Vocabulary
Visualisation
Application Integration
Workflow
Others Biology Chemistry Translational
Data Data Data
Services Services Services

6. SESL: Biomedical Knowledge Brokering
• Challenge:
– No single system for retrieving gene to disease relationships contained in
both published & biological database content
– Need a ‘push model’ for biomedical knowledge access: the current model
requires the consumer to search 1000’s of content sources
• Opportunity: Pilot Project with key stakeholders
– Pilot a ‘push model’ for biomedical knowledge brokering
– Engage multiple consumers, content providers and a single, public group to
develop the necessary infrastructure to explore the standards required for
the model to work in production
• History:
– May 2008: Common Disease Knowledge Environment (CDKE) IMI call drafted
– Sep 2008: postponed call publication
– Jan 2009: x-pharma meeting in London on how to progress CDKE
– Apr 2009: CDKE presented at SESL workshop
– Oct 2009: SESL Pilot meeting (funders)
– Jan 2010: Pilot launch

7. The Knowledge Service Framework
Multiple
Consumers
‘Consumer’
Disease Dossier Knowledge
Firewall Applications
Service Layer Std Public Common
Open Assertion & Meta Data Mgmt Vocabularies Service
Stds Transform / Translate Business Broker
Integrator Rules
Supplier
Firewall Content
Suppliers
Db 2
Effort required
Db 4 to fit DBs to
Corpus 1 service layer
Db 3 Corpus 5
7

8. A Production Service vision...
Consumer
Side Exemplar
Disease Dossier Application
License
Service Layer Std Public Service Layer Std Public Service Layer Std Public Service Layer Std Public
Vocabularies Vocabularies Vocabularies Vocabularies
Assertion & Meta Data Mgmt Assertion & Meta Data Mgmt Assertion & Meta Data Mgmt Assertion & Meta Data Mgmt
Transform / Translate Business Transform / Translate Business Transform / Translate Business Transform / Translate Business
Rules Rules Rules Rules
Integrator Integrator Integrator Integrator
Broker Org #1 Broker Org #2 Broker Org #3 Internal Broker
License
Corpus 1 Db 3 Corpus 5 Db 7 Corpus 9 Db 11 Corpus 13 Db 15
Corpus 4 Corpus 8 Corpus 12 Corpus 16
Db 2 Db 6 Db 10 Db 14
Supplier
Side

9. The technology is coming here

10. The Pilot
• Deliverables:
– Publication of standards & recommendations for service implementation
– Pilot implementation of service for a single disease (assertions from pre-defined
document sets & databases)
– Establish ways of working pre-competitively across industry/vendor/academia
– Dialogue and assessment of cost / value, with key content suppliers in moving to
such a push model for content (viability of moving to production)
• Status:
– AZ, Pfizer, GSK, Roche, Unilever, EBI, NPG, OUP, Elsevier & RSC
– 12 month project, £200K direct funding (+ PM & Architecture support)
– Contract between Pistoia & EBI signed 20th January 2010 for 1 year
• Scope:
– Development of an assertion database in combination with a user interface and
associated web services for one disease/indication/phenotype of broad interest:
Type II Diabetes
– Assertional content derived from 3 structured data sources and limited Journal
content (co-occurrence & statistical derivation from full text)
– Assertional evidence for filtering and drill down to primary data.
– Limited vocabulary development for area of focus: Type II Diabetes

11. Minimal configuration to test a
Brokering Service
Interface
User Interface Layer
at consumer org’n
Condition:
Service Layer
Assertion & Meta Data Mgmt
Std Public
Vocabularies
Service Layer
Assertion & Meta Data Mgmt
Std Public
Vocabularies Brokering service
Identical structure.
Different content
Transform / Translate Query Transform / Translate Query Layer
templates templates
which can overlap. Triple store 1 Triple store 2
at EBI
Broker #1 Broker #2
Primary source
Elsevier RSC Layer
corpus corpus NPG
corpus
OUP
corpus
at provider org’n
EBI Swissprot EBI Ensembl EBI Array EBI Swissprot
database gene Express database
database

12. SESL user interface mock-up: Query
Gene: abc
Relationship: Any
Disease: Diabetes
Constraint: Species: Any
Tissue: Any

13. SESL user interface mock-up: Results
Gene R’ship Disease Species Evidence
1 abc1 Co-occurs Diabetes Mus Paper UID:1234
2 abc1 Up-Reg Diabetes Homo ArrayExpress: XXX
3 abc2 Co-occurs Diabetes Homo Paper UID:1344
4 abc13 Co-occurs Diabetes Mus Paper UID:1314
5 abc7 Mutation Diabetes Rattus OMIMI: XXX
6 abc1 Co-occurs Diabetes Mus Paper UID:45643
7 abc1 Co-occurs Diabetes Homo Paper UID:2143
8 abc1 Co-occurs Diabetes Mus Paper UID:1204

14. Diabetes genes in SESL prototype
Primary data sources SESL project
Gene symbols UNIPROT Involvement in OMIM in ArrayExpress Atlas? SESL? SESL co-occurence SESL OMIM SESL Arrayexpress
diabetes type 2? diabetes? in Full Text diabetes? Atlas?
literature?
ABCC8 Y - NIDDM Y Y Y Y Y N
ADIPOQ Y - NIDDM Y Y Y Y N N
ALMS1 Y - NIDDM N Y Y Y N N
BLK Y - MODY11 Y Y Y Y N N
CAPN10 Y - NIDDM Y Y Y Y Y N
CEL Y - MODY8 Y Y Y Y Y N
ENPP1 Y - NIDDM Y Y Y Y Y N
GCK Y - MODY2 Y Y Y Y Y N
HNF1A Y - MODY3 Y Y Y Y Y N
HNF1B Y - MODY5 Y Y Y Y Y N
HNF4A Y - MODY1 Y Y Y Y Y N
INPPL1 Y - NIDDM N Y N
INS Y - MODY10 Y Y Y Y N N
IRS1 Y - NIDDM Y Y Y Y N N
KCNJ11 Y - NIDDM Y Y N
KLF11 Y - MODY7 Y Y Y Y Y N
LIPC Y - NIDDM Y Y Y Y Y N
MAPK8IP1 Y - NIDDM Y Y Y Y Y N
MCF2L2 Y - NIDDM N Y N
NEUROD1 Y - MODY6 Y N Y Y Y N
PAX4 Y - MODY9 Y Y Y Y Y N
PDX1 Y - MODY4 Y Y Y Y N N
PPARG Y - NIDDM Y Y Y Y Y N
PPP1R3A Y - NIDDM Y Y Y Y N Y
SLC30A8 Y - NIDDM Y Y Y N Y N
TCF7L2 Y - NIDDM Y Y Y Y Y N
UCP1 Y - NIDDM N Y Y Y N N
WFS1 Y - NIDDM Y Y Y Y Y N

15. Timelines: Development Phase
Task/Deliverable Phase Type Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 Feb-11
Month 0 Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8 Month 9 Month 10 Month 11 Month 12
Finalised Technical Specification Deliverable

^
document (Month 4) 1
Build vocabularies within scope Development Task 2

RDF data export from UniProt Development Task 3
and Ensembl 
RDF data export of Array Express Development Task 4

Extract literature assertions for Development Task 6
T2DB from publishers’ content 
Develop RDF triple store schema Development Task 7
and demonstrator 
Develop query definitions Development Task 8

Establish API services for remote Development Task 9
access 
Develop simple user interface for Development Task 10
demonstrator (based on mock-
up)

Write documentation that Development Task 11
defines the standard framework
Access to early prototype Deliverable
demonstrator and report
(Month 7 & 8)
2&3 ^^ 
Final prototype demonstrator, Deliverable
recommendations post-pilot, 4&5
^ ^^
report (Month 11 & 12) and
public launch

16. Timelines:
Testing and Communication Phase
Task/Deliverable Phase Type Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 Feb-11
Month 0 Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8 Month 9 Month 10 Month 11 Month 12
Tests of the demonstrator (full Testing and Task 12
private and limited public communication
instance)
Deploy publc demonstrator Testing and Task 13
communication
Write publication for standard Testing and Task 14
definition communication
Develop recommendations for Testing and Task 15
post-pilot project communication
Final prototype demonstrator, Deliverable
recommendations post-pilot 4&5 ^ ^
and report (Month 11 & 12)
Public release of limited Deliverable
demonstrator (Month 13) 6 ^

17. Summary of Accomplishments
• Significant progress to towards realising
the technical goal of knowledge brokering
– Can a push model work? A hyperstandard?
• A unique consortium from three cultures:
industry, publishers and academia
– Working together – sharing costs and risks
• Business opportunities and concerns
– For data providers and consumers?

18. Acknowledgements
Industry Publishers EMBL-EBI
Mike Westaway Claire Bird – OUP Christoph Grabmueller
Ian Stott Richard O’Bierne – OUP Silvestras Kavaliauskas
Peter Woollard Jabe Wilson – Elsevier Roderigo Lopez
Nigel Wilkinson Bradley Allen – Elsevier Dominic Clark
Catherine Marshall Colin Batchelor – RSC Jo McEntyre
Ian Dix Richard Kidd – RSC Janet Thornton
Nick Lynch David Hoole – NPG Cath Brooksbank
Michael Braxenthaler Alf Eaton - NGP
Ashley George