eTRIKS: A Knowledge Management Service for PPP Translational Research

Yike GuoeTRIKS academic coordinator

Example Stratified Medicine Consortium

2 Billion €

Partnership

I Billion €

Public

I Billion €

Private

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€.

Scientific Output

Patient enters medical center

Intellectual Property

Improved Healthcare

Experimental data

Downstreamanalysis

Clinical Procedures

Imaging Samples ExperimentsElectronicHealth Record

DataIntegration

External data

Image database Biobank database

Clinical database

Strat Med Project Process

• Clinical Data Capture (& Anonymisation)

• Sample tracking

• Biological assay data capture & processing

• Consortia Data & KM Platform

• Data Analytics tools

• Consortia Collaboration toolbox

Data Management Components

The eTRIKS Project

• Service Project – not Research. ~80% of project activities driven by demand from supported IMI projects (customer driven).

• Mandate to support PPP Translational studies with data & KM services:• Open Platform development, enhancement and support• Installation support• Training• Curation ETL support• Standards development• Data hosting• Limited retrospective content curation to support studies

• 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

+

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/Janssen

Imperial/Pfizer

Roche/IDBS/Merck/CDISC

Luxembourg/Sanofi

AstraZeneca/BioSci Consulting

Janssen/BioSci Consulting

CNRS/SanofiBios

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WP Number WP Name WP Leads

Projects Engaging eTRIKS

Oncology Safety

InflammationRA-Map

InfectionND4BB

• Discoverable Data – Basis for an IMI archive

• Enables re-usable innovation – common plug’n’play interface. Enables entrepreneurial Biz Models

• Minimises re-invention of the wheel by each project: e.g. ‘Big Data’ omic challenges or data security once.

• Facilitates easy interoperation & integration for partners with each new consortia

• Cost effective use of tax payers €s – operational efficiency

• Drives standardisation in data capture and management

Business Logic

This is what we are starting with

Data gets capturedOrganized / ManagedStoredAnalyzedViewed / disseminatedAssimilation / Synthesis

This is what we really need to support

• A key to translational research advancement is allowing a• continuous feedback loop between outcomes of basic and

clinical • research to accelerate translation of data into knowledge

eTRIKS Platform

DM KM

Product Management

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

Product Management Process

• All requests for new features (via forms) are be submitted 6 weeks before the Resource Team meeting, in order to be considered. An appointed member of the PMP will consolidate the requests and place on the eTRIKS PM wiki.

• PMP Decision making TC meeting is held 4 weeks before upcoming Resource team meeting, where the ranking proposal will be agreed upon.

• The PMP reviews all requests for entering into eTRIKS product backlog and selects a set of features from the product backlog to be implemented in the following development period following Resource Team meeting approval.

• Potentially, there is an additional PMP meeting (TC), 3 week before the Resource team meeting, in case the PMP decides they require further information and/or a user demo of the requested feature.

• The ranked list from the PMP is be placed on the eTRIKS PM wiki 2 weeks prior to the Resource team meeting, where all eTRIKS participants can comment.

Schematic Representation on PM

Internal Stakeholder Request

External Stakeholder Request

Consolidation of Project Requests of by AM1

Competition Analysis

PM-wiki

Consolidation of all requests by PM2

Ranking of requests by PMP

Proposal to Resource Team

Approval

Development Roadmap

Requirement GatheringRequirementConsolidation

RequirementRanking & Proposal

DevelopmentRoadmap

*3

*3

1: AM - Account Manager, 2: PM – Product Manager, 3: Clarification of request by requesting stakeholder/AM

User Requirement Gathering

Platform

http://requirements.etriks.org/twiki/bin/view/RequestManagement/

User Requirement GatheringKey fields

• Benefit Estimate: Stakeholders must provide for each request an estimate of the relative benefit that each feature provides to the users and/or to achieving the eTRIKS objectives (e.g. establishing a centralized European data base) on a scale from 1 to 5, with 1 indicating very little benefit and 5 being the maximum possible benefit.

• Cost Estimate: Stakeholders interface with the WP2 Architect to provide a rough estimate of the effort (in person month) or required financial investment (in Euros). PMP will transform absolute costs into a relative cost value, again on a scale ranging from a low of 1 to a high of 5. Cost ratings are be based on factors such as the requirement complexity, the extent of user interface work required, the potential ability to reuse existing designs or code, and the levels of testing and documentation needed.

• Risk Estimate / Mitigation Analysis: Stakeholders and WP2 architect should provide a brief description of possible risks associated with the feature development and mitigation strategy for each risk. In addition, Stakeholders and WP2 Architect to estimate the relative degree of technical or other risk associated with each feature on a scale from 1 to 5. An estimate of 1 means you can program it in your sleep, while 9 indicates serious concerns about feasibility, the availability of staff with the needed expertise, or the use of unproven or unfamiliar tools and technologies.

Click here for Request Page

eTRIKS DM Component

Example : GUI Design for Study Repository

One data tree for all investigations- Cross study searches- Every data type viewed in context

Consistent Data Organization

Consistent Vocabulary

Consistent Layout

• Becoming functional – recruitment, op norms, reporting, legal docs, etc

• Production tranSMART v1.1 released this month.– PostgreSQL open platform

• Installations at: Imperial (UBIOPRED), Liverpool (PredictTB), Alacris (Oncotrack), QMUL (RA-Map), Luxembourg (eTRIKS), and CC-IN2P3 (eTRIKS)

• Curation of retrospective public content: – EBI Atlas gene fold change data (subset): SearchApp– Public Asthma & RA related GEO data: DataSetExplorer App– TCGA Datasets (Clinical and Gene Expression Data):

• Breast invasive carcinoma [BRCA]• Colon adenocarcinoma [COAD]• Uterine Corpus Endometrial Carcinoma [UCEC]• Ovarian serous cystadenocarcinoma [OV]

• Support of 5 IMI projects to date:– January: UBIOPRED: server set-up at ICL, 625 patients to date (screening & baseline), Low density

Eicosanoid Lipidomic data, gene expression data, proteomic data and animal model clinical data loaded. Training provided.

– May: Oncotrack, ABIRISK, PredictTB and ABPI/MRC RA-Map: tranSMART installations and training to date.

• Active discussions with 4-5 other projects re requirements and support

Progress (1)

• Requirements gathering1. 2 x User requirement workshops:

• 1. tranSMART developer and user meeting , Amsterdam, June 2013 (tranSMART foundation collaboration)• 2. eTRIKS User requirement session, London, 2013 (eTRIKS Request)

2. Requirements reviewed and consolidated (identical request merged into one)3. eTRIKS Product Management WIKI (functions such as voting and automatic pre-prioritisation: based on number or

requests, benefit, cost and risk estimates, enabled) implemented and requirements uploaded to it

Progress (2)

Proposed Future Model

Patient Stratification

Predicting Therapy Response

Biomarker Discovery: Correlating Signatures to Clinical Outcome

Animal: Human model validation

IMIArchive

DiseaseModelling

COPD -

Local Instance lMI Instance

DataTransfer

ABIRISK

UBIOPRED

StratMed X

SecureFederated

Search(data & samples)

Metadata Query

What Longitudinal Arteriosclerosis

studies have been run in the UK involving >

500 subjects?

• Robust• Responsive• Fit for Purpose• Stable• Supported• Backed-up• Secure• Re-usable• Sustainable• Community Led• Efficient

• 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

Ultimately…

Medical CentresAnalytics

Specialists

DiseaseSpecialists

IT Services

CRO

AssaySpecialists

Regulatoryauthorities

Patient organization

P

P

P

Fully Integrated Stratified

Medicine Ecosystem

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

End

• Clinical Data Capture: – EDCs for the capture and validation of the clinical assay and patient data. Needs to be standardised

for project across all recruiting centres. e.g. OpenClinica, REDCap

• Sample tracking: – human and animal biopsy/fluid and cell line samples need tracking as they are stored and shipped

between the consortia partners for assays. Operational logistics tool.

• Biological assay data capture: – Multiple LIMS (laboratory information management systems) platforms for the different assay

technologies (NGS, omic, etc). Either vendor supplied, open source or locally developed. Important that data pre-processing is transparent and results in processed data in standard formats.

• Consortia Data & KM Platform: – A consortia wide platform for normalized data storage, integration, querying, and long term

archiving. Requires multiple ETL processes to export data from the local EDCs & LIMS. Needs a pluggable interface to allow the integration of analytics tools. Archive – but what to keep???

• Data Analytics tools: – Range of commercial, open and local data analysis tools to find signals in the phenotypic and

biological information.

• Consortia Collaboration toolbox: – Tools to support communication, project management and document sharing across the consortia

partners. Basic collaboration tools such as calendar, document management, project management, tc facilities etc, including a common ELN (E-Lab Notebook) for the capture of experimental design, analysis processes, results and conclusions.

Data Management Components