European Medical Information Framework Pharmaceutical IT Conference London 24 September 2013

1. EMIF
European Medical Information Framework
Bart Vannieuwenhuyse
24 September 2013
Pharmaceutical IT Conference London

2. 10-Mar-14 2
The IMI is a unique Public-Private Partnership (PPP) between the
pharmaceutical industry represented by the European Federation of
Pharmaceutical Industries and Associations (EFPIA) and the
European Union represented by the European Commission.
Pharmaceutical IT Conference 2013

3. Imagine a world where…
10-Mar-14 3
 Researchers can access available patient-level data to gain new
insights around disease etiologies and define new treatment
targets…
 We can optimize Clinical R&D by 50% using existing patient level
data…
 New treatments are effective in 95% of patients…
 You can reduce treatment failure by 60% with timely prediction and
intervention…
 Where we can continuously monitor the risk/benefit profile of new
therapies using naturalistic data…
 All health care providers have access to up-to-date information on
existing and new treatments…
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4. Framework for RWE
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Clinical Care Clinical Research
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5. Challenges with re-use of patient level
data
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Data gaps
• Missing data elements (e.g. outcomes)
• Studies require details that may not be
routinely collected
• Coding often only at first level (e.g. ICD-
9) therefore missing granularity
• 80% of info stored as unstructured data
Data quality
• Longitudinal coherence
• Coding for administrative reasons (up
– down coding)
• Coding often months after patient
encounter
• Data provenance – who entered the
data?
“Semantics”
• Many standards – many versions
• Complex care – many HCP’s involved
– many hand-overs
• Need to pool data cross sites and
cross different countries
• Pharma focused on CDISC
Privacy
• Clearly a top priority
• Different interpretations by country, by
region – complex
• TRUST
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6. Successful example of data
re-use for research
 RWE of ACHeI
> 2500 patient years of therapy
documented in EHR-system
> 8 fold dataset compared to
Cochrane
 Cost effective
Text mining derivation of service
utilisation and costs.
Created in one month
 Resembles cognitive decline
curve derived from clinical trials
Cholinesterase inhibitors
and Alzheimer’s disease
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-1 0 1 2 3
1618202224
time(years)
MMSEscore

7. EMIF Vision
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To be the trusted European hub
for health care data intelligence
enabling new insights into
diseases and treatments
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8. Project objectives
EMIF: one project – three topics
1. EMIF-Platform: Develop a framework for evaluating,
enhancing and providing access to human health data
across Europe, to support the two specific topics below
as well as research using human health data in general
2. EMIF-Metabolic: Identify predictors of metabolic
complications in obesity, with the support of EMIF-
Platform
3. EMIF-AD: Identify predictors of Alzheimer’s Disease
(AD) in the pre-clinical and prodromal phase, with the
support of EMIF-Platform
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9. EMIF – platform for modular
extension
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EMIF-Metabolic
EMIF-AD
Data Privacy
Analytical tools
Semantic Integration
Information standards
Data access / mgmt
IMI Structure and Network
Research Topics
EMIF governance
Preventionalgorithms
Predictivescreening
Riskstratification
Call xCall x
Riskfactoranalysis
Patientgenerateddata
TBD
EMIF-Platform
Metabolic CNS
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10. Data types in platform:
 Identified categories or “types” of data
 Types:
– Primary care data sets
– Hospital data
– Administrative
– Regional record-linkage systems
– Disease-specific registries
– Biobanks
 Selected representative examples –
 Combined around 48MM subjects from 7 EU countries
 And of course the cohorts from the Research Topics
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11. Data bases “typology”
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12. EMIF systems view
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User
admin
User
admin
Remote
user 1
Remote
user 2
Site 1
Site 2
Data
access
Module
extract
Data
access
Module
extract
Commonontology/De-identification
EMIF platform
solution
Governance
Data owners Researchers
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13. EMIF roadmap
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14. EMIF catalogue - prototype
10-Mar-14 14[Meeting name]

15. Re-using existing solutions
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16. Data being loaded in tranSMART
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4 times the number of subjects in ADNI
Data available for analysis end Oct 2013
Data structure aligned with CDISC
AD MCI
Subjective Memory
impairment
CTL/Controls Total
Cohort 1 259 225 232 716
Cohort 2 160 100 50 80 390
ADNI 1 188 405 229 822
Cohort 3 881 881
Cohort 4 20 14 42 76
Cohort 5 420 420
Total 607 1631 64 1003 3305
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17. Framework for RWE
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Clinical Care Clinical Research
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18. Framework for RWE
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System biology
Biomarker definition
Lead identification
Clinical trial Execution
Market Access
Ongoing safety
tracking
incident monitoring &
detection
retrieval of similar
patient history
outcome analysis
care management
patients at risk
re-admission prevention
diagnosis &
treatment assistance
Clinical Care Clinical Research
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19. More info
 EMIF general
– Bart Vannieuwenhuyse (bvannieu@its.jnj.com)
– Simon Lovestone (simon.lovestone@kcl.ac.uk)
– Johan van der Lei (j.vanderlei@erasmusmc.nl)
 EMIF-Platform
– Johan van der Lei (j.vanderlei@erasmusmc.nl)
– Patrick Genyn (pgenyn1@its.jnj.com)
 EMIF-Metabolics
– Ulf Smith (ulf.smith@medic.gu.se)
– Dawn Waterworth
(Dawn.M.Waterworth@gsk.com)
 EMIF-AD
– Pieter Jelle Visser
(pj.visser@maastrichtuniversity.nl)
– Johannes Streffer (jstreffe@its.jnj.com)
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www.emif.eu