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Bringing Clinical Data Together with Neo4j

BioData World Webinar
Kirsten Langendorf, S-Cubed

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Bringing Clinical Data Together with Neo4j

  1. 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
  2. 2. 2 | ©2020 S-cubed 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
  3. 3. 3 | ©2020 S-cubed Our “Study” World Collect Organize Analyse ResultsPlan
  4. 4. 4 | ©2020 S-cubed Neo4j Use
  5. 5. 5 | ©2020 S-cubed Study Workbench
  6. 6. 6 | ©2020 S-cubed Study Workbench
  7. 7. 7 | ©2020 S-cubed Electronic Health Records
  8. 8. 8 | ©2020 S-cubed Mining for Definitions
  9. 9. 9 | ©2020 S-cubed And Some Cypher … o We use a lot of rectangular structures, but we can recreate these with Cypher queries
  10. 10. 10 | ©2020 S-cubed Change in daily life due to COVID-19 11th March 2020 How can I help? Letter from authorities
  11. 11. 11 | ©2020 S-cubed Covidgraph.org Mycontribution
  12. 12. 12 | ©2020 S-cubed The source data ClinicalTrials.gov API Limit More studies than limit Study counter
  13. 13. 13 | ©2020 S-cubed 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
  14. 14. 14 | ©2020 S-cubed Looping with Cypher Allowing for all studies to be included Getting the total number of studies returned by the looping
  15. 15. 15 | ©2020 S-cubed Modelling ClinicalTrials Converting tabular info to a graph My pharma experience with Clinical Trials
  16. 16. 16 | ©2020 S-cubed { "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) )
  17. 17. 17 | ©2020 S-cubed Missing values In json input ?
  18. 18. 18 | ©2020 S-cubed Missing values In json input Split in two
  19. 19. 19 | ©2020 S-cubed 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. 20. Contact Details Kirsten Langendorf kl@s-cubed.dk

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