This document summarizes presentations from the CDISC 2020 Europe Interchange conference on April 1-2, 2020. It introduces Maxim Moinat who works on converting healthcare data to the OMOP Common Data Model. It also introduces Nigel Hughes who is the project lead for the IMI2 European Health Data & Evidence Network (EHDEN) and was previously involved in other real-world data projects. The document provides an agenda for the conference sessions which will discuss EHDEN, OHDSI, a EHDEN study-a-thon, using real-world data in clinical trials and for regulatory purposes.

1. CDISC 2020 Europe Interchange
Virtual Conference
1-2 April 2020

2. Maxim Moinat is a data engineer at The Hyve with
a background in Bioinformatics and Medical
Sciences. In the last few years, he has been an
active member of the OHDSI community and
gained a vast experience in converting a variety of
observational healthcare data to the OMOP
Common Data Model.
As a co-lead of the technical work package in the
EHDEN consortium, he is contributing to
establishing an European health data network.
Besides EHDEN, Maxim is driving The Hyve's
involvement in two other public consortia,
BigData@Heart and PIONEER, where The Hyve is
responsible for the OMOP CDM conversion work
and technical infrastructure.
CDISC 2020 Europe Interchange | #CDISCEurope #ClearDataClearImpact2
Maxim Moinat, EHDEN
WP4 co-lead, The Hyve

3. Nigel Hughes, EHDEN
Project Leader, Janssen
Nigel Hughes has a thirty-five year career spanning the
NHS in the UK (16 years), NGOs and patient organisations
(10 years) and within the pharmaceutical industry (17
years). He has worked clinically in HIV and viral hepatitis,
liver disease, and in sales & marketing, medical affairs,
market access and health economics, R&D, precision
medicine, advanced diagnostics, health IT and Real World
Data/Real World Medicine.
His experience covers clinical, education, as an advisor,
consulting, communications and lobbying over the years.
He is currently the Project Lead for the IMI2 European
Health Data & Evidence Network (EHDEN), and was
Platform Co-Lead for the IMI1 European Medical
Information Framework (EMIF), as well as consulting on
numerous projects and programmes in the domain of
RWD/RWE
CDISC 2020 Europe Interchange | #CDISCEurope #ClearDataClearImpact3

4. Disclaimer and Disclosures
• The views and opinions expressed in this presentation are those of the
author(s) and do not necessarily reflect the official policy or position of
CDISC.
4
• The author(s) have no real or apparent conflicts of interest to report.

5. Enabling Large-Scale Analysis of Electronic
Health Records in Europe
April 2nd 2020
Session 11

6. Agenda
1. What is EHDEN? Goals and Achievements
2. What is OHDSI? Mission, Community and Data Standards
3. EHDEN Study-a-thon. The power of collaborative science
4. Clinical Trials. Setting new OHDSI conventions
5. RWD in Regulatory Setting

7. 7
The challenge of Real World Data

8. What is EHDEN?
Goals and Achievements

9. 9
European Network: EHDEN

10. EHDEN Consortium
Start date: 1 Nov 2018
End date: 30 Apr 2024
Duration: 66 months
Non-for-profit organisations
Small to medium-sized companies
EFPIA & Associated partners
Universities, public bodies and research organisations
Almost €29
million
Academic
coordinator
EFPIA Lead
22 partners
Innovative Medicines Initiative
Project
10

11. A sustainable ecosystem: call process overview
12

12. A sustainable ecosystem: call process overview
Tailored for project
objectives and
sustainability
Data sources Open calls
Evaluated via a pre-
defined set of criteria
by the Data source
prioritisation
committee
Grant awarding
Max. 100k
13
First workplans
created

13. A sustainable ecosystem: call process overview
Tailored for project
objectives and
sustainability
Data sources
Supporting SMEs
Open calls
Focusing on SMEs
able to support
mapping and
sustainability
Open calls
Evaluated via a pre-
defined set of criteria
by the Data source
prioritisation
committee
Grant awarding
Training & Certification
SME certification
committee prioritizes
SMEs for training and
certification
Max. 100k
14
First two groups certified!

14. A sustainable ecosystem: call process overview
Tailored for project
objectives and
sustainability
Data sources
Supporting SMEs
Open calls
Focusing on SMEs
able to support
mapping and
sustainability
Open calls
Workshop
Source
Data
Evaluation
Share of
Mapping
Process
Mapping
Audit
Mapping
Cycle
Evaluated via a pre-
defined set of criteria
by the Data source
prioritisation
committee
Harmonisation fund
Data sources can
choose the SME from
the pool of EHDEN
certified SMEs
SMEs are paid via
grants from the
harmonisation fund
Payments are
milestone based
Mapped data sources are encouraged to be
active members of the EHDEN community,
participating in research studies.
Grant awarding
Training & Certification
SME certification
committee prioritizes
SMEs for training and
certification
Max. 100k
15

15. EHDEN hit the ground running
OMOP CDM
EHR Catalogue Private remote
research
environment
Accessible InteroperableFindable Reusable
ATLAS
Ethical code of
practice
17
Main developers
of many of the
OHDSI tools are
EHDEN partners
Collaborators

16. What is OHDSI?
Mission, Challenges and the Community

17. 19
OHDSI Vision
A world in which observational research produces a comprehensive
understanding of health and disease.
OHDSI Mission
To improve health by empowering a community to collaboratively
generate the evidence that promotes better health decisions and
better care.
https://www.ohdsi.org/who-we-are/mission-vision-values/

18. Large-scale observational research is feasible
“Characterizing treatment pathways at scale using the OHDSI network.”
George Hripcsak et al. - PNAS (2016)27:7329–7336
11 Data sources
4 Countries
> 250 million patients
T2 Diabetes Mellitus Hypertension Depression
21

19. Common Data Model to enable Standardised
Analytics
22

20. OMOP Common Data Model
24

21. 25
OMOP standard vocabularies
Standardised globally
Analytical standards: SNOMED, RxNorm, LOINC
More than 100 ‘source’ vocabularies mapped to the
standards
7.4 million concepts
3.0 million standard + 0.5 million classification
Comprehensive hierarchy: ~45 million relationships
Publically available: https://athena.ohdsi.org

22. EHDEN Study-a-thon
The power of collaborative science

23. 27
Two successful Study-a-thons
https://youtu.be/X5yuoJoL6xs
Results published as dashboards
PLEE: http://data.ohdsi.org/UkaTkaSafetyEffecIveness/
PLP: http://data.ohdsi.org/oxfordMortalityExternalValidaIon/
"From question to publication in 5 days”

24. Results
“To compare the risk of post-operative complications
(infection, revision, and venous thrombo-embolism)
between Unicompartmental (UKR) vs Total Knee Replacement (TKR).”
On multiple, distinct datasets

25. COVID-19 study-a-thon
• Virtual event
• >300 collaborators
• Four timezones
• Three focus areas
• Nine concurrent network
studies
29

26. Converting Clinical Trial to the OMOP CDM
Setting new OMOP CDM conventions

27. Use cases at the intersection of OHDSI and CT
Using RWD for Clinical Trial Design
● Patient enrichment phase
● Trial planning and recruitment
optimization
● Virtual patient cohorts
● Predict trial adherence
31
Linking RWD and CT data
● Standardize cohort definitions
across CT and RWD
● Use CT data as source for RWE
● Perform cross clinical trial study
analysis.
● Enabling RWD assets to support
interventional analyses

28. 32
Derive person id
Measurement date
measurement concept
4232915 - Sitting systolic
blood pressure (LOINC)
measurement value
Vital Signs -> Measurement
Derive Visit id
measurement unit

29. Initial Findings: differences OMOP and SDTM
1. Trial visits
2. Study and arm assignment
3. Measurement Modifiers
4. Include new vocabularies for e.g.:
a. Biomarkers
b. Novel drug assets
c. ...
33
New conventions needed!

30. OHDSI Clinical Trials Working Group
Next step: apply these conventions
to available data sources:
• CSDR
• Datasphere
• C-path
• Vivli
• PHUSE
34

31. Using RWD for Regulatory Purposes
Accelerating Clinical Research

32. For Regulatory & HTA Bodies, Real World Data is now
very real….
36CDISC 2020 Europe Interchange | #CDISCEurope #ClearDataClearImpact
“Post-launch evidence is not a means of
replacing randomized clinical trials, but should
be seen as complementary knowledge”2
“Increase the access to and analysis of real-
world data in EU so that it supports robust
decision-making, noting however that Post
Licensing Evidence Generation (PLEG) includes
experimental and observational data”2
1. HMA-EMA Joint Big Data Taskforce; Phase II report – Evolving Data-Driven Regulation; Amsterdam, 20th January 2020
2. Moseley J, et al; Regulatory and health technology assessment advice on Post-licensing and Post-Launch Evidence Generation is a foundation for lifecycle data
collection for medicines; British Journal of Clinical Pharmacology 2020; online, 11 March
“Big Data is not necessarily the solution to all the challenges faced by
regulators in reaching appropriate decisions. While randomised,
double-blind, controlled clinical trials will remain the reference
standard for most regulatory use cases, the complementary evidence
that new Big Data sources generate may facilitate, inform and
improve our decisions. It is clear that the data landscape is evolving
and that the regulatory system needs to evolve as well.
In this way we can realise opportunities for public health and
innovation through better evidence for decisions on the development,
authorisation and on-market safety and effectiveness monitoring of
medicines. If we work now, smartly and collaboratively, and embrace
change we can evolve to deliver better regulation for patients and
establish the EU medicines regulatory network as a reference for
data-driven decision-making”1
HMA-EMA Big Data Taskforce,
20th January 2020

33. The poster child of RWD/adaptive studies….
37CDISC 2020 Europe Interchange | #CDISCEurope #ClearDataClearImpact
1. http://www.gsk.com/en-gb/media/press-releases/2016/salford-lung-study-results-show-copd-patients-treated-with-relvar-ellipta-achieve-superior-reduction-in-
exacerbations-compared-with-usual-care/; accessed 23/06/16

34. Current use cases on e.g. synthetic controls exist….
38CDISC 2020 Europe Interchange | #CDISCEurope #ClearDataClearImpact
1. https://dcricollab.dcri.duke.edu/sites/NIHKR/KR/GR-Slides-06-15-18.pdf; accessed 24th March 2020
Roche met EU coverage requirements
for marketing alectinib in 20 European
markets using a synthetic control arm
Rather than waiting for phIII data, Roche
used a synthetic control arm of 67 patients to
provide the necessary evidence of relative
performance. This accelerated coverage by
18 months

35. Thank You!

36. ohdsi.org | ohdsi-europe.org
github.com/ohdsi
forums.ohdsi.org
ohdsi.org/2019-ohdsi-symposium-materials/
ehden.eu
github.com/ehden
enquiries@ehden.eu
More Information
thehyve.nl
github.com/thehyve
office@thehyve.nl
blog.thehyve.nl/blog/topic/omop-ohdsi
💡
💡
40

37. The Book of OHDSI
41
book.ohdsi.org