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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
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Biomedical Informatics1
Expanding the SPL Model Beyond Indexing to Include Annotations
Richard D. Boyce, PhD University of Pittsburgh
2014 DailyMed Jamboree Public WorkshopSeptember, 18th 2014
Department of Biomedical Informatics
Biomedical Informatics2
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
Biomedical Informatics3
“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
Biomedical Informatics4
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.pdf2. http://www.fda.gov/ForIndustry/DataStandards/StructuredProductLabeling/default.htm3. http://dailymed.nlm.nih.gov/dailymed/downloadLabels.cfm
NLM DailyMedSPL database
Pharma contributes
SPLs to FDA
Active and inactive ingredients
Represented organization
Route of administration
SPL identification (setid, version, effective date)
Names (trade name and generic)
LOINC-coded sections
Clinical Studies
Boxed Warnings
Clinical pharmacology
Drug interactions
Adverse Reactions
…other sections…
FDA indexing(pharmacologic class and billing
unit)
Unstructured textand HTML tables
Biomedical Informatics6
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
Biomedical Informatics7
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
Biomedical Informatics8
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.
Biomedical Informatics9
Example label pharmgx statements
Biomedical Informatics10
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
Biomedical Informatics11
Pharmgx information within SPLs
Unstructured text statements in various sections
Biomedical Informatics12
Finding label pharmgx information (current)
http://www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm083378.htm
Four clicks from here to a PDF version of the label
Biomedical Informatics13
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?
Biomedical Informatics14
Expanding SPLs to include annotationsThe Open Annotation (OA) Data model: An extensible and interoperable framework for annotations [1]
1. http://www.openannotation.org/spec/core/
Biomedical Informatics15
Example pharmgx recommendation
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:body-1 ex:target-1
ex:annotation-1
about
Biomedical Informatics16
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.
Biomedical Informatics17
More on the general annotation model
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:body-1 ex:target-1
ex:annotation-1
about
The use of standard terminologies enables interoperability
Text selection is not dependent on a specific document
Biomedical Informatics18
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
Biomedical Informatics19
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
-----------
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
Biomedical Informatics25
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– 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)
Biomedical Informatics26
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
Biomedical Informatics27
Want more information?• Proof-of-concept:
– https://www.youtube.com/watch?v=Te546vOiruo
• 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/
Biomedical Informatics28
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
Biomedical Informatics29
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)
Biomedical Informatics30
Discussion/questions