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Acquiring and representing drug-
drug interaction
knowledge and evidence​
Jodi Schneider
TRIADS lab, University of Pittsbu...
Problem
o Thousands of preventable medication errors occur
each year.
o Clinicians rely on information in drug compendia
(...
Prescribers check for known drug interactions.
3
Prescribers consult drug interaction references
which are maintained by expert pharmacists.
Medscape EpocratesMicromedex 2...
Prescribers consult drug interaction references
which are maintained by expert pharmacists.
Medscape EpocratesMicromedex 2...
Goals
o Long-term, provide drug compendia editors with
better information and better tools, to create the
information clin...
MEDICATION SAFETY DOMAIN
Definitions
o Drug-drug interaction
o Potential drug-drug interaction
8
Existing approaches: Representation
Bradford-Hill criteria (1965)
1. Strength
2. Consistency
3. Specificity
4. Temporality...
Existing approaches: Representation
Royal Dutch Association for the Advancement of
Pharmacy (2005)
1. Existence & quality ...
Existing approaches: Representation
Boyce, DIKB, 2006-present
Existing approaches: Acquisition
o Evidence
12Boyce, DIKB, circa 2006
DATA MODEL: REPESENTING
KNOWLEDGE
Why is a new data model needed?
o Need computer integration
o Want a COMPUTABLE model that can make
inferences
14
Multiple layers of evidence
Medication Safety
Studies Layer
Human Subjects
Studies Layer
Scientific Evidence Layer
15
Scientific Evidence Layer: Micropublications
16
Clark, Ciccarese, Goble (2014) Micropublications: a semantic model for cla...
17
18
19
20
21
22
23
24
25
Medication Safety Studies Layer:
DIDEO
Brochhausen et al, work in progress, example of Clinical Trial
DIDEO: Drug-drug Interaction and Drug-
drug Interaction Evidence Ontology
27https://github.com/DIDEO
EVIDENCE CURATION:
ACQUIRING KNOWLEDGE
Hand-extracting knowledge claims and
evidence
o Sources
• Primary research literature
• Case reports
• FDA-approved drug l...
DIRECTIONS & FUTURE WORK
34
Implications
o Implications for evidence modeling & curation
o Implications for ontology development.
o Implications for i...
Implications for evidence modeling &
curation
o Evidence modeling & curation is a general process.
o Analogous processes c...
Thanks to collaborators & funders
o Training grant 5T15LM007059-29 from the National
Library of Medicine and the National ...
“Addressing gaps in clinically useful
evidence on drug-drug interactions”
4-year project, U.S. National Library of Medicin...
o Evidence
40
7.19 Drugs Metabolized by Cytochrome P4502D6
In vitro studies did not reveal an inhibitory effect of
escital...
Acquiring and representing drug-drug interaction knowledge and evidence, TRIADS lab, University of Pittsburgh, 2016-03-25
Acquiring and representing drug-drug interaction knowledge and evidence, TRIADS lab, University of Pittsburgh, 2016-03-25
Acquiring and representing drug-drug interaction knowledge and evidence, TRIADS lab, University of Pittsburgh, 2016-03-25
Acquiring and representing drug-drug interaction knowledge and evidence, TRIADS lab, University of Pittsburgh, 2016-03-25
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Acquiring and representing drug-drug interaction knowledge and evidence, TRIADS lab, University of Pittsburgh, 2016-03-25

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Presentation to the TRanslational Informatics Applied to Drug Safety (TRIADS) lab about modeling and acquiring evidence for the DIKB project.

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Acquiring and representing drug-drug interaction knowledge and evidence, TRIADS lab, University of Pittsburgh, 2016-03-25

  1. 1. Acquiring and representing drug- drug interaction knowledge and evidence​ Jodi Schneider TRIADS lab, University of Pittsburgh 2016-03-25
  2. 2. Problem o Thousands of preventable medication errors occur each year. o Clinicians rely on information in drug compendia (Physician’s Desk Reference, Medscape, Micromedex, Epocrates, …). o Compendia have information quality problems: • differ significantly in their coverage, accuracy, and agreement • often fail to provide essential management recommendations about prescription drugs 2
  3. 3. Prescribers check for known drug interactions. 3
  4. 4. Prescribers consult drug interaction references which are maintained by expert pharmacists. Medscape EpocratesMicromedex 2.0 4
  5. 5. Prescribers consult drug interaction references which are maintained by expert pharmacists. Medscape EpocratesMicromedex 2.0 5
  6. 6. Goals o Long-term, provide drug compendia editors with better information and better tools, to create the information clinicians use. o This talk focuses on how we might efficiently acquire and represent • knowledge claims about medication safety • and their supporting evidence o in a standard computable format.
  7. 7. MEDICATION SAFETY DOMAIN
  8. 8. Definitions o Drug-drug interaction o Potential drug-drug interaction 8
  9. 9. Existing approaches: Representation Bradford-Hill criteria (1965) 1. Strength 2. Consistency 3. Specificity 4. Temporality 5. Biological gradient 6. Plausibility 7. Coherence Bradford-Hill A. The Environment and Disease: Association or Causation?. Proc R Soc Med. 1965;58:295-300. 9
  10. 10. Existing approaches: Representation Royal Dutch Association for the Advancement of Pharmacy (2005) 1. Existence & quality of evidence on the interaction 2. Clinical relevance of the potential adverse reaction resulting from the interaction 3. Risk factors identifying patient, medication or disease characteristics for which the interaction is of special importance 4. The incidence of the adverse reaction Van Roon, E.N. et al: Clinical relevance of drug-drug interactions: a structured assessment procedure. Drug Saf. 2005;28(12):1131-9. 10
  11. 11. Existing approaches: Representation Boyce, DIKB, 2006-present
  12. 12. Existing approaches: Acquisition o Evidence 12Boyce, DIKB, circa 2006
  13. 13. DATA MODEL: REPESENTING KNOWLEDGE
  14. 14. Why is a new data model needed? o Need computer integration o Want a COMPUTABLE model that can make inferences 14
  15. 15. Multiple layers of evidence Medication Safety Studies Layer Human Subjects Studies Layer Scientific Evidence Layer 15
  16. 16. Scientific Evidence Layer: Micropublications 16 Clark, Ciccarese, Goble (2014) Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications
  17. 17. 17
  18. 18. 18
  19. 19. 19
  20. 20. 20
  21. 21. 21
  22. 22. 22
  23. 23. 23
  24. 24. 24
  25. 25. 25
  26. 26. Medication Safety Studies Layer: DIDEO Brochhausen et al, work in progress, example of Clinical Trial
  27. 27. DIDEO: Drug-drug Interaction and Drug- drug Interaction Evidence Ontology 27https://github.com/DIDEO
  28. 28. EVIDENCE CURATION: ACQUIRING KNOWLEDGE
  29. 29. Hand-extracting knowledge claims and evidence o Sources • Primary research literature • Case reports • FDA-approved drug labels o Process • Spreadsheets • PDF annotation 29
  30. 30. DIRECTIONS & FUTURE WORK
  31. 31. 34
  32. 32. Implications o Implications for evidence modeling & curation o Implications for ontology development. o Implications for improving medication safety.
  33. 33. Implications for evidence modeling & curation o Evidence modeling & curation is a general process. o Analogous processes could be used in other fields. o Biomedical curation is most mature: structured nature of the evidence interpretation, existing ontologies, trained curators, information extraction and natural language processing pipelines o Curation pipelines need to be designed with stakeholders in mind.
  34. 34. Thanks to collaborators & funders o Training grant 5T15LM007059-29 from the National Library of Medicine and the National Institute of Dental and Craniofacial Research o The entire “Addressing gaps in clinically useful evidence on drug-drug interactions” team from U.S. National Library of Medicine R01 grant (PI, Richard Boyce; 1R01LM011838-01) o Other collaborators: Paolo Ciccarese, Tim Clark 37
  35. 35. “Addressing gaps in clinically useful evidence on drug-drug interactions” 4-year project, U.S. National Library of Medicine R01 grant (PI, Richard Boyce; 1R01LM011838-01) o Evidence panel of domain experts: Carol Collins, Amy Grizzle, Lisa Hines, John R Horn, Phil Empey, Dan Malone o Informaticists: Jodi Schneider, Harry Hochheiser, Katrina Romagnoli, Samuel Rosko o Ontologists: Mathias Brochhausen, Bill Hogan o Programmers: Yifan Ning, Wen Zhang 38
  36. 36. o Evidence 40 7.19 Drugs Metabolized by Cytochrome P4502D6 In vitro studies did not reveal an inhibitory effect of escitalopram on CYP2D6.

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