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Expanding the SPL Model Beyond 
Indexing to Include Annotations 
Richard D. Boyce, PhD 
University of Pittsburgh 
2014 Dai...
What is annotation? 
• “Annotation” involves turning unstructured 
text descriptions into a normalized data 
structure 
– ...
“Take home” point 
• Annotation of specific content written into 
SPLs will enable innovative downstream 
uses 
– Decision...
Structured Product Labels (SPLs) 
• All package inserts for currently marketed 
drugs are available in this format [1-3] 
...
NLM DailyMed 
SPL database 
Pharma 
contributes 
SPLs to FDA 
Active and inactive 
ingredients 
Represented 
organization ...
Scenario 
• Lauren is a physician in an outpatient 
clinic. She receives a pharmacogenomics 
test result for one of her fe...
What does she need to know? 
For each drug ?d taken by her patient, 
who carries the HLA-B*5701 genotype, 
what is the… 
…...
FDA’s goals for pharmacogenomics 
and product labeling [1] 
“Inform prescribers about the impact, 
or lack of impact, of g...
Example label pharmgx statements 
9 Biomedical Informatics
The current status of pharmgx 
statements in labeling 
• August 18, 2014 [1]: 
– 138 drugs, 43 
biomarkers 
– 11 drug/biom...
Pharmgx information within SPLs 
Unstructured text statements in 
various sections 
11 Biomedical Informatics
Finding label pharmgx information (current) 
Four clicks from here to a PDF 
version of the label 
http://www.fda.gov/Drug...
Annotation vs indexing 
• The FDA biomarker table basically 
indexes pharmacogenomics information 
– This information coul...
Expanding SPLs to include annotations 
The Open Annotation (OA) Data model: An 
extensible and interoperable framework for...
Example pharmgx recommendation 
ex:body-1 ex:target-1 
15 Biomedical Informatics 
Predicate Object 
drug abacavir 
biomark...
One annotation for many labels 
Once created, annotations can be rendered in an OA 
client for any label where the stateme...
More on the general annotation model 
ex:body-1 ex:target-1 
17 Biomedical Informatics 
Predicate Object 
drug abacavir 
b...
Our multidisciplinary approach 
• Work with pharmacists to: 
– Understand their information needs 
– Develop a semantic mo...
Progress 
• Semi-structured interviews 
– 14 completed with different types of 
pharmacists 
– Their information needs are...
-----------
Revisiting how to find label pharmgx 
information 
Video of the concept: https://www.youtube.com/watch?v=Te546vOiruo
Video of the concept: https://www.youtube.com/watch?v=Te546vOiruo
Video of the concept: https://www.youtube.com/watch?v=Te546vOiruo
Some lessons learned while annotating 
• Which labels to annotate? 
– Innovator labels chosen. Further work needed 
to det...
Future work 
• Determining the stability of 
annotations 
– across labels 
– over time 
• Task based usability studies 
– ...
Want more information? 
• Proof-of-concept: 
– https://www.youtube.com/watch?v=Te546vOiruo 
27 Biomedical Informatics 
• C...
Research Team 
University of Pittsburgh Department of 
Biomedical Informatics: 
•Harry Hochheiser, Katrina M. Romagnoli, 
...
Acknowledgements 
• Annotators (U of Pitt School of Pharmacy): 
– Solomon Adams, Allison Doherty, Jocelyn Hatfield, Alex R...
Discussion/questions 
30 Biomedical Informatics
Pharmacogenomics annotation in drug structured product labeling for clinical decision support
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Pharmacogenomics annotation in drug structured product labeling for clinical decision support

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Prof. Boyce presents work on a semantic model for clinical pharmacogenomics statements in structured product labeling (SPLs) and how it can be integrated into clinical decision support.

See a video of the talk starting at 32:04 at the following link: http://videocast.nih.gov/summary.asp?Live=14776&bhcp=1

Published in: Health & Medicine
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Pharmacogenomics annotation in drug structured product labeling for clinical decision support

  1. 1. Expanding the SPL Model Beyond Indexing to Include Annotations Richard D. Boyce, PhD University of Pittsburgh 2014 DailyMed Jamboree Public Workshop September, 18th 2014 1 Biomedical Informatics Department of Biomedical Informatics
  2. 2. What is annotation? • “Annotation” involves turning unstructured text descriptions into a normalized data structure – Different from “indexing” which simply tags mentioned entities “Drug X indicated for condition Y” – Indexing: tags Drug X and Condition Y to aid information retrieval • does not retain the relationship “indicated for” – Annotation: retains the relationship 2 Biomedical Informatics
  3. 3. “Take home” point • Annotation of specific content written into SPLs will enable innovative downstream uses – Decision support – Drug safety – Drug discovery / repositioning • Pharmacogenomics will be used as a case study – Other potentially relevant kinds of information exist • drug-drug interactions, adverse drug reactions 3 Biomedical Informatics
  4. 4. Structured Product Labels (SPLs) • All package inserts for currently marketed drugs are available in this format [1-3] 1. http://www.fda.gov/OHRMS/DOCKETS/98fr/FDA-2005-N-0464-gdl.pdf 2. http://www.fda.gov/ForIndustry/DataStandards/StructuredProductLabeling/default.htm 3. http://dailymed.nlm.nih.gov/dailymed/downloadLabels.cfm 4 Biomedical Informatics
  5. 5. NLM DailyMed SPL database Pharma contributes SPLs to FDA Active and inactive ingredients Represented organization Route of administration Names (trade name and generic) SPL identification (setid, version, effective date) LOINC-coded sections Boxed Warnings Clinical Studies Clinical pharmacology Adverse Reactions Drug interactions …other sections… FDA indexing (pharmacologic class and billing unit) Unstructured text and HTML tables
  6. 6. Scenario • Lauren is a physician in an outpatient clinic. She receives a pharmacogenomics test result for one of her female patients. • The result states that the patient has the genotype HLA-B*5701 • Lauren wants to quickly know what the implications are for each drug that her patient is taking 6 Biomedical Informatics
  7. 7. What does she need to know? For each drug ?d taken by her patient, who carries the HLA-B*5701 genotype, what is the… …potential impact – pharmacokinetic / pharmacodynamic ...patient specific risk factors – Concomitant medications – Medical conditions …recommendations – dosage, drug administration, alternatives, monitoring, and tests 7 Biomedical Informatics
  8. 8. FDA’s goals for pharmacogenomics and product labeling [1] “Inform prescribers about the impact, or lack of impact, of genotype on phenotype” “Indicate whether a genomic test is available and if so, whether testing should be considered, recommended, or necessary.” 1. FDA. Clinical Pharmacogenomics: Premarketing Evaluation in Early Phase Clinical Studies. Rockville, MD: Federal Drug Administration; 2011. 8 Biomedical Informatics
  9. 9. Example label pharmgx statements 9 Biomedical Informatics
  10. 10. The current status of pharmgx statements in labeling • August 18, 2014 [1]: – 138 drugs, 43 biomarkers – 11 drug/biomarker pairs with boxed warning or warning and precaution mentions – 19 drug therapeutic areas 1. FDA. Table of Pharmacogenomic Biomarkers in Drug Labels. 2014. Available at: http://www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm083378.htm. Last accessed 09/15/2014 10 Biomedical Informatics
  11. 11. Pharmgx information within SPLs Unstructured text statements in various sections 11 Biomedical Informatics
  12. 12. Finding label pharmgx information (current) Four clicks from here to a PDF version of the label http://www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm083378.ht m 12 Biomedical Informatics
  13. 13. Annotation vs indexing • The FDA biomarker table basically indexes pharmacogenomics information – This information could be provided as supplementary SPL files – Some basic kinds of queries would be supported • But, many clinician use cases would not be met • What about extending the SPL to include annotations? 13 Biomedical Informatics
  14. 14. Expanding SPLs to include annotations The Open Annotation (OA) Data model: An extensible and interoperable framework for annotations [1] 14 Biomedical Informatics 1. http://www.openannotation.org/spec/core/
  15. 15. Example pharmgx recommendation ex:body-1 ex:target-1 15 Biomedical Informatics Predicate Object drug abacavir biomarker HLA-B*5701 drug-selection-recommendation do-not-restart Predicate Object hasSource URL to product label Exact-text “For HLA-B*5701…” Preceding-text … Post-text … ex:annotation-1 about
  16. 16. One annotation for many labels Once created, annotations can be rendered in an OA client for any label where the statement is written the same way. 16 Biomedical Informatics
  17. 17. More on the general annotation model ex:body-1 ex:target-1 17 Biomedical Informatics Predicate Object drug abacavir biomarker HLA-B*5701 drug-selection-recommendation do-not-restart Predicate Object hasSource URL to product label Exact-text “For HLA-B*5701…” Preceding-text … Post-text … ex:annotation-1 about The use of standard terminologies enables interoperability Text selection is not dependent on a specific document
  18. 18. Our multidisciplinary approach • Work with pharmacists to: – Understand their information needs – Develop a semantic model for pharmacogenomics statements – Train them on how to annotate the statements • using a custom plugin for a web annotation tool (Domeo [1]) • Develop a prototype decision support tool [2] 1. Ciccarese P, Ocana M, Clark T. Open semantic annotation of scientific publications using DOMEO. J Biomed Semantics. 2012 Apr 24;3 Suppl 1:S1. doi: 10.1186/2041-1480-3-S1-S1. 2. Boyce, RD., Freimuth, RR., Romagnoli, KM., Pummer, T., Hochheiser, H., Empey, PE. Toward semantic modeling of pharmacogenomic knowledge for clinical and translational decision support. AMIA Summits Transl Sci Proc. Mar 18 2013:28- 32. PMCID: PMC3814496 18 Biomedical Informatics
  19. 19. Progress • Semi-structured interviews – 14 completed with different types of pharmacists – Their information needs are informing a prototype • Pharmacist annotations on labels for 16 drugs – To date 8 pharmacist have participated – Consensus annotations completed for 10 drugs • Annotations published as an annotation web service – in OA at the “LinkedSPLs” RDF endpoint – more to say about this later today 19 Biomedical Informatics
  20. 20. -----------
  21. 21. Revisiting how to find label pharmgx information Video of the concept: https://www.youtube.com/watch?v=Te546vOiruo
  22. 22. Video of the concept: https://www.youtube.com/watch?v=Te546vOiruo
  23. 23. Video of the concept: https://www.youtube.com/watch?v=Te546vOiruo
  24. 24. Some lessons learned while annotating • Which labels to annotate? – Innovator labels chosen. Further work needed to determine consistency of content across labels • Tables should also be annotated 25 Biomedical Informatics – e.g., warfarin dosing • Some annotations are actually on dynamically generated sections – the "Highlights" section is generated by an SPL stylesheet – We decided to annotate within the text and code special (42229-5 SPL UNCLASSIFIED SECTION)
  25. 25. Future work • Determining the stability of annotations – across labels – over time • Task based usability studies – How well are information needs being met – What problems do clinicians have with understanding the information 26 Biomedical Informatics
  26. 26. Want more information? • Proof-of-concept: – https://www.youtube.com/watch?v=Te546vOiruo 27 Biomedical Informatics • Code project – LinkedSPLs : https://code.google.com/p/swat-4-med-safety/ – Domeo Pharmgx and drug-drug interaction plugins: https://github.com/rkboyce/DomeoClient • Open Data Anotation – http://www.openannotation.org/spec/core/
  27. 27. Research Team University of Pittsburgh Department of Biomedical Informatics: •Harry Hochheiser, Katrina M. Romagnoli, Yifan Ning, Andres Hernandez University of Pittsburgh School of Pharmacy •Philip E. Empey, Solomon Adams Harvard/Mass General (Domeo and the OA standard) •Paolo Ciccarese, Tim Clark 28 Biomedical Informatics
  28. 28. Acknowledgements • Annotators (U of Pitt School of Pharmacy): – Solomon Adams, Allison Doherty, Jocelyn Hatfield, Alex R. Cockerham, Linda Huang, Michael Diduch, William Wilson, Fengyee Zhou • Grant funding for the research: – National Library of Medicine (R01LM011838-01), The National Institute of Aging (K01 AG044433-01), NIH/NCATS (KL2TR000146), NIH/NIGMS (U19 GM61388; the Pharmacogenomic Research Network), NIH/NLM (T15 LM007059-24) – Fogarty International Center of Global Health of the National Institutes of Health under the grant No. 1D43TW008443-0 – Agency for Healthcare Research and Quality (K12HS019461). – U of Pitt Institute for Personalized Medicine (PreCISE-Rx: Pharmacogenomics-guided Care to Improve the Safety and Effectiveness of Medications) 29 Biomedical Informatics
  29. 29. Discussion/questions 30 Biomedical Informatics

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