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Acquiring and representing drug-
drug interaction
knowledge and evidence​
Jodi Schneider
March 29, 2016
Litman Lab, CS, Un...
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...
Problem
o Drug Compendia synthesize PDDI evidence into
knowledge claims but:
• Disagree on whether specific evidence items...
Problem
o Drug Compendia synthesize PDDI evidence into
knowledge claims but:
• Disagree on whether specific evidence items...
Silos
Post-market studies
Reported in
Scientific literature
Reported in
Pre-market studies Clinical experience
Drug produc...
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
• A biological process that results in a clinically
meaningful change to the response ...
Existing approaches: Representation
Bradford-Hill criteria (1965)
1. Strength
2. Consistency
3. Specificity
4. Temporality...
Existing approaches: Representation
Horn, J. R., Hansten, P. D., & Chan, L. N. (2007). Proposal for a new tool to evaluate...
Existing approaches: Representation
Royal Dutch Association for the Advancement of
Pharmacy (2005)
1. Existence & quality ...
Existing approaches: Representation
Boyce, DIKB, 2006-present 15
Existing approaches: Acquisition
o Evidence
16Boyce, 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
18
Multiple layers of evidence
Medication Safety
Studies Layer
Clinical Studies and
Experiments
Scientific Evidence Layer
19
Scientific Evidence Layer: Micropublications
20
Clark, Ciccarese, Goble (2014) Micropublications: a semantic model for cla...
MP:Claim
21
Building up an MP graph
22
Building up an MP graph
23
Building up an MP graph
24
Building up an MP graph
Building up an MP graph
26
Building up an MP graph
27
Building up an MP graph
28
Building up an MP graph
29
Building up an MP graph
30
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
32https://github.com/DIDEO
EVIDENCE CURATION:
ACQUIRING KNOWLEDGE
Hand-extracting knowledge claims and
evidence
o Sources
• Primary research literature
• Case reports
• FDA-approved drug l...
35
36
37
DIRECTIONS & FUTURE WORK
We are developing a search/retrieval portal
It will:
o Integrate information (removing silos)
o Offer the same information...
40
Evaluation plan for the search/retrieval portal
o 20-person user study
o Measures of
• Completeness of information
• Level...
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 T15LM007059 from the National
Library of Medicine and the National Inst...
“Addressing gaps in clinically useful
evidence on drug-drug interactions”
4-year project, U.S. National Library of Medicin...
Jodi Schneider, Mathias Brochhausen, Samuel Rosko, Paolo Ciccarese,
William R. Hogan, Daniel Malone, Yifan Ning, Tim Clark...
o Evidence
48
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, Litman Lab, University of Pittsburgh, 2016-03-29
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Acquiring and representing drug-drug interaction knowledge and evidence, Litman Lab, University of Pittsburgh, 2016-03-29

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Presentation to Diane Litman's lab at the University of Pittsburgh about modeling and acquiring evidence for the Drug Interaction Knowledge Base (DIKB) project.

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Acquiring and representing drug-drug interaction knowledge and evidence, Litman Lab, University of Pittsburgh, 2016-03-29

  1. 1. Acquiring and representing drug- drug interaction knowledge and evidence​ Jodi Schneider March 29, 2016 Litman Lab, CS, University of Pittsburgh
  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. Problem o Drug Compendia synthesize PDDI evidence into knowledge claims but: • Disagree on whether specific evidence items can support or refute PDDI knowledge claims
  7. 7. Problem o Drug Compendia synthesize PDDI evidence into knowledge claims but: • Disagree on whether specific evidence items can support or refute PDDI knowledge claims • May fail to include important evidence
  8. 8. Silos Post-market studies Reported in Scientific literature Reported in Pre-market studies Clinical experience Drug product labels
  9. 9. 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.
  10. 10. MEDICATION SAFETY DOMAIN
  11. 11. Definitions o Drug-drug interaction • A biological process that results in a clinically meaningful change to the response of at least one co- administrated drug. o Potential drug-drug interaction • POSSIBILITY of a drug-drug interaction • Data from a clinical/physiological study OR reasonable extrapolation about drug-drug interaction mechanisms 11
  12. 12. 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. 12
  13. 13. Existing approaches: Representation Horn, J. R., Hansten, P. D., & Chan, L. N. (2007). Proposal for a new tool to evaluate drug interaction cases. Annals of Pharmacotherapy, 41(4), 674-680. 13
  14. 14. 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. 14
  15. 15. Existing approaches: Representation Boyce, DIKB, 2006-present 15
  16. 16. Existing approaches: Acquisition o Evidence 16Boyce, DIKB, circa 2006
  17. 17. DATA MODEL: REPESENTING KNOWLEDGE
  18. 18. Why is a new data model needed? o Need computer integration o Want a COMPUTABLE model that can make inferences 18
  19. 19. Multiple layers of evidence Medication Safety Studies Layer Clinical Studies and Experiments Scientific Evidence Layer 19
  20. 20. Scientific Evidence Layer: Micropublications 20 Clark, Ciccarese, Goble (2014) Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications
  21. 21. MP:Claim 21
  22. 22. Building up an MP graph 22
  23. 23. Building up an MP graph 23
  24. 24. Building up an MP graph 24
  25. 25. Building up an MP graph
  26. 26. Building up an MP graph 26
  27. 27. Building up an MP graph 27
  28. 28. Building up an MP graph 28
  29. 29. Building up an MP graph 29
  30. 30. Building up an MP graph 30
  31. 31. Medication Safety Studies Layer: DIDEO Brochhausen et al, work in progress, example of Clinical Trial
  32. 32. DIDEO: Drug-drug Interaction and Drug- drug Interaction Evidence Ontology 32https://github.com/DIDEO
  33. 33. EVIDENCE CURATION: ACQUIRING KNOWLEDGE
  34. 34. Hand-extracting knowledge claims and evidence o Sources • Primary research literature • Case reports • FDA-approved drug labels o Process • Spreadsheets • PDF annotation 34
  35. 35. 35
  36. 36. 36
  37. 37. 37
  38. 38. DIRECTIONS & FUTURE WORK
  39. 39. We are developing a search/retrieval portal It will: o Integrate information (removing silos) o Offer the same information to all compendium editors o Provide direct access to information • E.g. quotes in context
  40. 40. 40
  41. 41. Evaluation plan for the search/retrieval portal o 20-person user study o Measures of • Completeness of information • Level of agreement • Time required • Perceived ease of use
  42. 42. Implications o Implications for evidence modeling & curation o Implications for ontology development. o Implications for improving medication safety.
  43. 43. 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.
  44. 44. Thanks to collaborators & funders o Training grant T15LM007059 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; R01LM011838) and other collaborators 44
  45. 45. “Addressing gaps in clinically useful evidence on drug-drug interactions” 4-year project, U.S. National Library of Medicine R01 grant (PI, Richard Boyce; R01LM011838) 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, Louisa Zhang 45
  46. 46. Jodi Schneider, Mathias Brochhausen, Samuel Rosko, Paolo Ciccarese, William R. Hogan, Daniel Malone, Yifan Ning, Tim Clark and Richard D. Boyce. “Formalizing knowledge and evidence about potential drug-drug interactions.” International Workshop on Biomedical Data Mining, Modeling, and Semantic Integration: A Promising Approach to Solving Unmet Medical Needs (BDM2I 2015) at ISWC 2015 Bethlehem, Pennsylvania, USA. Jodi Schneider, Paolo Ciccarese, Tim Clark and Richard D. Boyce. “Using the Micropublications ontology and the Open Annotation Data Model to represent evidence within a drug-drug interaction knowledge base.” 4th Workshop on Linked Science 2014—Making Sense Out of Data (LISC2014) at ISWC 2014 Riva de Garda, Italy. Mathias Brochhausen, Jodi Schneider, Daniel Malone, Philip E. Empey, William R. Hogan and Richard D. Boyce “Towards a foundational representation of potential drug-drug interaction knowledge.” First International Workshop on Drug Interaction Knowledge Representation (DIKR-2014) at the International Conference on Biomedical Ontologies (ICBO 2014) Houston, Texas, USA. Richard D. Boyce, John Horn, Oktie Hassanzadeh, Anita de Waard, Jodi Schneider, Joanne S. Luciano, Majid Rastegar-Mojarad, Maria Liakata, “Dynamic Enhancement of Drug Product Labels to Support Drug Safety, Efficacy, and Effectiveness.” Journal of Biomedical Semantics. 4(5), 2013. doi:10.1186/2041-1480-4-5
  47. 47. o Evidence 48 7.19 Drugs Metabolized by Cytochrome P4502D6 In vitro studies did not reveal an inhibitory effect of escitalopram on CYP2D6.

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