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Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

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Addressing gaps in clinically useful evidence on drug- drug interactions Update to W3C HCLS September 10 th 2013 Richard Boyce, University of Pittsburgh Department of Biomedical Informatics
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Page 1: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

Addressing gaps in clinically useful evidence on drug-drug interactions

Update to W3C HCLSSeptember 10th 2013

Richard Boyce, University of Pittsburgh

Department of Biomedical Informatics

Page 2: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

A new paradigm for drug-drug interaction knowledge representation

Product labeling

Scientific literature

A framework for representing PDDI assertions and evidence as interoperable Linked Data available for community annotation

Pharmacoepidemiology studies

Semantic annotation

High priority PDDIs for research

Semantic annotation

Reduced risk of a PDDI medication

error!

Clinical experience

Better synthesis of PDDI evidence, easier identification of gaps

Expected benefits:• More complete and accurate PDDI evidence• Better informed pharmacists and other

clinicians• More effective PDDI alerting and decisions

support systems

Page 3: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

DailyMed Linked Structured Product Labels

• LinkedSPLs is a Linked Data version of SPLs– http://dbmi-icode-01.dbmi.pitt.edu/linkedSPLs/

• >40,000 FDA-approved prescription and over-the-counter drugs present in DailyMed (09/2013)

• simplifies access to SPL content• interoperable with other important drug

terminologies and resources– RxNorm, NDF-RT, DrugBank, ChEBI

• Pharmacogenomics biomarker statements– http://www.youtube.com/watch?v=Te546vOiruo

Page 4: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

PDDI information mashups

http://dbmi-icode-01.dbmi.pitt.edu/dikb-evidence/outfiles-poc-10252012/dikb-label-mashup-citalopram-001714c1-a292-40be-bfbd-0ff67193ace6.html

Page 5: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

Open Data Annotation

http://www.openannotation.org/spec/core/

Page 6: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

Semantic Annotation of potential drug-drug interactions (PDDIs)

Page 7: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

Scientific Discourse modeling

Page 8: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

Drug Interaction Knowledge Base (DIKB) Open Data Anotation + Scientific Discourse

• See • >300 evidence sources • >1500 links to ~1300

assertions

A production rule base for inferring pharmacokinetic PDDIs

DIKB: http://dbmi-icode-01.dbmi.pitt.edu/dikb/

Initial conversion (not ready for release):http://swat-4-med-safety.googlecode.com/svn/trunk/analyses/dikb-open-annotation/

Page 9: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

Work in progress…A pipeline for the extraction PDDIs from SPLs and publishing them as semantically annotated Linked Data

Page 10: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

Potential for PDDI semantic annotation dissemination

• As Linked Data, it automatically extends– DrugBank, ChEBI, RxNorm, NDF-RT

• A user friendly knowledge base portal– Currently testing Domeo: http://swan.mindinformatics.org/

– Enables community annotation and scientific discourse

• Other possibilities:– The FDAs SPL indexing initiative

• Could guide future requirements for SPL submissions• Complements our work on representing pharmacogenomics clinical

statements [18]

Page 11: Brief update to W3C HCLS on representing and linking potential drug-drug interaction knowledge

AcknowledgementsCollaborators: • Harry Hochheiser, Qian Zhu, Robert Freimuth, Carol

Collins, John Horn, Mathias Brochhausen, Serkan Ayvaz, Majid Rastegar-Mojarad, Anita DeWaard, Jodi Schneider, Maria Liakata, Oktie Hassanzadeh, Joanne Luciano, Michel Dumontier, and the W3C HCLS

Funding:• Agency for Healthcare Research and Quality

(K12HS019461). • NIH/NCATS (KL2TR000146),• NIH/NIGMS (U19 GM61388; the Pharmacogenomic

Research Network) • NIH/NLM (T15 LM007059-24)


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