eTRIKS: A Knowledge Management Platform for Translational Research

Ian Dix, AstraZeneca R&DYike Guo, Imperial College LondonOn Behalf of eTRIKS

Ian.dix@astrazeneca.comy.guo@imperial.co.uk

Challenge of Drug Development Complex

Disease Phenotypes

2

3

How do we stratify these complex phenotypes?

WGS RNAseq Mass Spec

Imaging RT Sensing

Next Generation Platforms -> Data Explosion

Challenges in running internal biomarker programs

• Study population, design & data collection is defined by clinical development program– Typically not optimised for biomarker discovery

• Cost of running sufficiently powered Longitudinal Observational Studies designed for biomarker discovery (and validation) is prohibitive

• Collaborate…Industry

Academia

Public Private Consortium

Sharing costs enables bigger studies

Pros:• Shared costs: increase in scale – breadth & depth• Diverse specialisms enabling increased complexity and insight• Multiple centres: Improved recruitment

Cons:• IP complexity• Coordination

Example Translational Study Consortium

Stratified Medicine:• GAUCHERITE Consortium• Stop HCV• MATURA

• RA-Map• COPD-Map

22 CTMM research projects are active, involving a total of 119 partners and a research budget of 302.7 M€.

Translational Research Information Flow

eCRF software

Data Data

Data

Biobank

Samples

Analytical Labs

Databases

External Analytics API

External Visualisation API

Collaboration and KM platform

Clinical Sites

LIMS / Sample Tracker

Ontology Management

Service

Analytical Workflows

Central Cloud-based Platform

Challenge 1:The Science Priority

ScienceScience

InfrastructureInfrastructure

Data Infrastructure costs are consistently underestimated

Who Pays?

Challenge 2: Data Collaboration

Sharing data securely across the individual organisations…

Org 2Org 2

Org nOrg n

Org 1Org 1

Org 3Org 3

Org 4Org 4

What tools and standards?

Challenge 3: Fixed Time Line

The value of data is long lived, virtual organisations are not:

Project Consortium

Org 2Org 2

Org nOrg n

Org 1Org 1

Org 3Org 3

Org 4Org 4

5 Years

Who stewards the data when the consortium ends?

So in IMI what are we doing about it?

Translational Research Information and Knowledge Management Service

2008 2009 2010 2011 2012 2013

IMIInitiates

EFPIA KMGroup adviseson need for KMIn IMI

GSK/JnJ/ICLPilot tranSMART

RDG acceptProposal for KM call

eTRIKSCall Published

EoISelected FPP

Agreed

eTRIKSInitiates (Q4)

FirstProjectOnboarded

Objectives

• Objectives: – Provision of a KM Service to support Private/Public Translational Research

(TR) in IMI– Single access point to standardised curated , IMI TR study information along

with IMI project relevant historic translational studies– Establishing a common, open source, interoperable TR platform, based on

open agree standards across the IMI TR projects.– Development of an active TR analytics & informatics community across IMI

• Budget: €23.79m for 5 years (Oct 2012---Sept 2017)

• Members:– 10 Pharma, 3 Academic, 1 standards, 2 Commercial Suppliers

The Consortium…

10 Pharma 6 Partners

+

Business Logic

• Reduced risk of data loss post IMI

• Improved operational efficiency for TR PPPs

• Improved access to secure data generated in TR PPPs

• Improved access to relevant historic TR study data

• Increased innovation in analytics tools and applications

Work Packages

WP1

WP2

WP3

WP4

WP5

WP6

WP7

Platform Deployment

Platform Development

Data Standards

Curation and Analysis

Management and Sustainability

Community and Outreach

Ethics

CNRS/JPNV

Imperial/Sanofi/Pfizer

Roche/IDBS/Merck/CDISC

Luxembourg/Sanofi

AstraZeneca/BioSci Consulting

Janssen/BioSci Consulting

GSK/CNRS/Bayer/Sanofi

WP Number WP Name WP Leads

Engagement and Governance

Demand

Execution

Progress Reports

IMI Client

Project

Demand1

Demand2

Demand3

Platform Deployment

Platform Development

Data Standards

Curation and Analysis

Community and Outreach

Ethics

eTRIKS Resour

ces

Decision

Delivery Packages

Deliveries

Progress UpdatesProject Input

3-6 Month Cycle

Projects Engaging eTRIKS

Oncology Safety

InflammationRA-Map

InfectionND4BB

Core Technology

Clinical CohortPhenotypic Data

Demographics

Clinical Observations

Clinical Trial Outcomes

Adverse Events

High Content Biomarker Data

Gene Expression

Genotyping

Metabolomic

PK/PD Markers

Reference Data

Literature

Pathway Data

Gene Metadata

tranSMARTETL

Mining

GPLv3

eTRIKS Platform

Collaboration Platform • Collaboration • Research process • IP capture and management• Secure access

Analytics Environment• Access to analytics tools • Open API for public and commercial

software to plug-in

TR Knowledge Hub • Cloud Infrastructure • Load procedures• ‘Big Data’ storage• Ontology management

Study Book / Visual Research

Access Management

Ontology Management

Scientific Data Architecture

Study Management

Global non-profit organization devoted to realizing the promise of translational biomedical research through development of the tranSMART knowledge management platform.

Goals1.Establish and sustain tranSMART as the preferred data sharing and analytics platform for translational biomedical research.2.Link academic, non-profit and corporate research communities for collaborative research facilitated by tranSMART.3.Align and grow a vibrant developer network around the scientific goals of the tranSMART community.4.Reduce barriers to entry through use of advanced technologies and an active marketplace.

Community: Large scale KM consortia, AMCs, NFPs, Pharma, Regulators, Biotech service suppliers

tranSMART Foundationhttp://www.transmartfoundation.org

What have we done in the first 5 months?

Progress…

1. Becoming Functional…

• Working in partnership with TF to address core issues in tranSMART (2/6 FTEs)

• tranSMART 1.1 (June)– first stable postgres release (UMichigan) * – ETL procedures for postgres (Imperial/Recombinant) *– decoupling of i2b2 (TraIT/Imperial) * – plugin architecture for:

• Ontology data (TraIT/Hyve)• Clinical data (Imperial)

• Data types for higher dimensional data• API for CRC data

• tranSMART 1.2 (October) to be defined: Unit tests, API for analysis in dataset explore, API for high dimensional data, GUI improvements, search improvements…

2. Reinforcing the Foundation

* Complete – currently in testing

• Aim: – eTRIKS server enabling access to public studies of interest to eTRIKS community

• Progress: • Setup

– tranSMART PostgresSQL Dev environment in place– Training and awareness of existing ETL processes for tranSMART

• Population of Search Tool with EBI Atlas fold change data– ETL pipeline built for populating the tranSMART Search tool. – ~2000 human, primate, mouse and rat ATLAS studies selected.– Beta version May 2013, with QC/QA prior to production release in June/July.

• Population of Dataset Explorer Tool with subset of GEO & Arrayexpress data– Selection of UBIOPRED relevant studies from GEO/Arrayexpress– Adaptation of Sanofi Dataset Explorer curation tool for PostgresSQL– Initial data sets being loaded now: production release June/July

3. Public eTRIKS Server

4. First Supported Project: UBIOPRED

Key Facts• Identification of novel biomarkers of

severe asthma

• 40 Partners (20 Academic, 10 SME, 10 EFPIA)

• Novel Cohort and Biobank of Severe Asthma Patients

• Cross-Sectional Comparative Study with Longitudinal Follow up

• Profiling of Genomics, Proteomics, Lipidomic, Breathomic

• Matching with in-vivo and in-vitro models

2604/07/23 R&D IT External Innovation

1,025 Patients 175,000 Samples 3,000,000 Data Points

• Systems Medicine approach toIdentify ‘handprint’ biomarkersacross data

http://www.ubiopred.european-lung-foundation.org/

4. eTRIKS Support of UBIOPRED

Aim (to date): Stand up a secure UBIOPRED server, load clinical and first omic data sets

Progress:Dedicated U-BIOPRED server set-up at ICL running PostgreSQL TM.tranSMART tutorials circulated to UBIOPRED projectAnonymised clinical data loaded - 250 patients to date (baseline visit)Urine and Sputum Lipidomic data loaded (eicosanoid panel)

Next sprints: Animal Model (house dust mite-induced asthma - mouse) dataRobust curation methodology to be developedResearch into Longitudinal Data Model (load & querying)Loading of omics data.

• Onboard 2-3 further projects

• Scope out Animal Model requirements across projects

• Work with Foundation to deliver TM1.1/1.2

• Release the public eTRIKS server: 2000+ studies

Immediate Next Steps

• Accessible Common Infrastructure

• Federation of searchable archives

of translational study information

• Ability to transfer data securely between

organisations within consortia

• Healthy ecosystem of commercial and

NFP service providers supporting projects

and institutions

• Large and diverse innovative

analytics & visualisation toolbox

Ideal Future State(IMI and beyond)

Medical CentresAnalytics

Specialists

DiseaseSpecialists

KM Support

CRO

AssaySpecialists

Regulatoryauthorities

Patient organization

P

P

P

The new reality of

Drug Research

1. Ensure the legacy of project data/results 2. Facilitate dataset integration 3. Increase operational efficiency 4. Establish a common set of standards

www.eTRIKS.orgLinked In Discussion Group: eTRIKS Twitter @etriks1