This document discusses using Neo4j to create a graph database from clinical trial data related to COVID-19. It describes modeling clinical trial metadata from JSON files into nodes and relationships in Neo4j. Challenges with missing data in the JSON files are addressed. The graph database allows for analyzing and visualizing the clinical trial data in new ways. Creating the COVID-19 graph provided an opportunity to gain experience with Cypher queries and graph modeling.

1. Covid–19 Graph!
Bringing Clinical Data
Together with Neo4j
Dave Iberson-Hurst
Partner, S-cubed
Kirsten Walther Langendorf
Principal Consultant, S-cubed
17th September 2020
Copenhagen

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S-cubed
• A3 Suite platform
• MDR
• SWB
• Linked Data Services
• CDISC Training and
Support
• Regulatory Development
Strategy
• Clinical Trial Documentation
• Marketing Authorisation
Applications & Licence
Maintenance
• EU SME Status, EU
OMPD Holder
• QA & GXP Services
• Statistical Consultancy
• SAS Programming
• Data Management
• CDISC services
• Statistical Analysis and
Reporting
• Quality Assurance
• Biostatistics
• Clinical Data Management
• Pharmacovigilance
• Medical Monitoring
• Risk Based Monitoring
• Operational Reporting
• Qlik Extensions Data Analytics
(Qlik)
Biometrics
Clinical
Standards
Management
Regulatory
Affairs

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Our “Study” World
Collect Organize Analyse ResultsPlan

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Neo4j Use

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Study Workbench

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Study Workbench

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Electronic Health Records

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Mining for Definitions

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And Some Cypher …
o We use a lot of rectangular
structures, but we can recreate these
with Cypher queries

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Change in daily life due to COVID-19
11th March 2020
How can I
help?
Letter from authorities

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Covidgraph.org
Mycontribution

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The source data
ClinicalTrials.gov API
Limit
More studies than limit
Study counter

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Looping with Cypher
Allowing for all studies to be included
Getting the total number of
studies and divide by 1000 to
get the number of loops needed

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Looping with Cypher
Allowing for all studies to be included
Getting the total number of
studies returned by the looping

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Modelling ClinicalTrials
Converting tabular info to a graph
My pharma
experience
with Clinical
Trials

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{
"NCTId": [
"NCT04366271"
],
"LocationFacility": [
"Hospital Universitario de Getafe",
"Hospital Universitario de Cruces",
"Hospital Universitario de La Princesa",
"Hospital Infantil Universitario Niño Jesus",
"Hospital Ramón Y Cajal",
"Complejo Universitario La Paz"
],
"Rank": 2,
"LocationCity": [
"Getafe",
"Barakaldo",
"Madrid",
"Madrid",
"Madrid",
"Madrid"
],
"LocationState": [
"Madrid"
],
"LocationCountry": [
"Spain",
"Spain",
"Spain",
"Spain",
"Spain",
"Spain"
]
}
}
From Json to nodes and relationships
From lists to graph
1
1
1
UNWIND study_metadata.NCTId as Id
match(ct:ClinicalTrial{NCTId:Id})
WITH Id, ct, study_metadata, RANGE(0,size(study_metadata.LocationFacility)-1) as
nfacil
FOREACH(i in nfacil |
MERGE(fa:Facility{name:study_metadata.LocationFacility[i]})
MERGE(ci:City{name:study_metadata.LocationCity[i]})
MERGE(c:Country{name:study_metadata.LocationCountry[i]})
MERGE(ct)-[:CONDUCTED_AT]->(fa)
MERGE(fa)-[:LOCATED_IN]->(ci)
)
WITH Id, study_metadata, RANGE(0,size(study_metadata.LocationCity)-1) as ncity
FOREACH(i in ncity |
MERGE(ci:City{name:study_metadata.LocationCity[i]})
MERGE(c:Country{name:study_metadata.LocationCountry[i]})
MERGE(ci)-[:LOCATED_IN]->(c)
)

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Missing values
In json input
?

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Missing values
In json input
Split in two

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o Neo4j Professional certification in 2019
• The task with covidgraph was a great opportunity to get
some cypher and graph experience
o Modelling can be improved
• Data consistency can be a challenge when creating
nodes and relationships
• Could consider some more advanced techniques to
‘clean’ the data (ML)
• Need to be aware of missing values in json when
creating queries
• Next steps: adding trial results
o Great to be part of a helpful team
• Even though I am not a healthcare professional I can
help to provide a better understanding of COVID-19
Lessons Learned
Virtual collaboration

20. Contact Details
Kirsten Langendorf
kl@s-cubed.dk