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Toward semantic modeling of pharmacogenomic knowledge for clinical and translational decision support

Richard Boyce*, University of PittsburghRobert Freimuth, Mayo ClinicKatrina M. Romagnoli, University of PittsburghTara Pummer, University of PittsburghHarry Hochheiser, University of PittsburghPhilip E. Empey, University of Pittsburgh

Department of Biomedical Informatics

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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 CYP2D6*2X2.

• Lauren wants to quickly know what the implications are for each drug that her patient is taking

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What does she need to know?For each drug ?d taken by her patient, who carries the CYP2D6*2X2 genotype, what is the… …potential impact

– pharmacokinetic / pharmacodynamic

...patient specific risk factors– Concomitant medications

– Medical conditions

…recommendations– dosage, drug administration, alternatives, monitoring, and

tests

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Where can she look?• Local clinical setting

– Institution/clinic specific information

– Likely to be very few in number

• Scientific literature– CPIC and Dutch pharmacogenomics working group

guidelines

– High quality but may be infrequently updated

– Available in PharmGKB, does she know that?

• Product Labeling– Concise, clinically oriented information

– Possibly the first place many clinicians look

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This talk is going focus on product labeling…

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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.

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The current status of pharmgx statements in labeling• March 2013 [1]:

– 38 biomarkers

– 107 active ingredients• > 1000 products

– 19 indications

1. FDA. Clinical Pharmacogenomics: Premarketing Evaluation in Early Phase Clinical Studies. Rockville, MD: Federal Drug Administration; 2011.

2. FDA. Table of Pharmacogenomic Biomarkers in Drug Labels. 2012. Available at: http://www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm083378.htm.

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Examples“For HLA-B*5701-positive patients, initiating or reinitiating treatment with an abacavir-containing regimen is not recommended”

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Examples“Nursing mothers who are ultra-rapid metabolizers may also experience overdose symptoms such as extreme sleepiness, confusion, or shallow breathing.”

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Examples

“Patients with low or absent TPMT activity are at an increased risk of developing severe, life-threatening myelotoxicity if receiving conventional doses of azathioprine.”

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Examples

“There is no relevant effect of genetic variation in CYP2B6, CYP2C9, CYP2C19, or CYP3A5 on the pharmacokinetics of prasugrel's active metabolite or its inhibition”

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Problem statementPharmacogenomics knowledge written in product labeling is important for clinical use cases and complements other resources.

However, this knowledge is currently unstructured which presents barriers to its efficient acquisition and use in the clinical setting

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Our approach• Work with pharmacists to:

– Develop a semantic model for pharmacogenomics statements

– Train them on how to annotate the statements

• Publish annotated statements using the Open Annotation standard [1]

• Integrate the annotated statements with other sources of pharmgx information– an interactive prototype

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

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What is “Open Annotation”

• An extensible and interoperable framework for expressing annotations [1]

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

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Open Data Annotation example

Predicate Object

drug CODEINE

biomarker CYP2D6

variant Ultra-rapid metabolizer

Pharmacokinetic effect

Metabolism-increase

Pharmacodynamic effect

Drug-toxicity-risk-increase

Predicate Object

hasSource URL to product label

Exact-text “Nursing mothers…”

Preceding-text

…

Post-text …

ex:body-1 ex:target-1

ex:annotation-1

about

“Nursing mothers who are ultra-rapid metabolizers may also experience overdose symptoms such as extreme sleepiness, confusion, or shallow breathing.”

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Semantic model - descriptions

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Description example

Predicate Object

drug CODEINE

biomarker CYP2D6

variant Ultra-rapid metabolizer

Pharmacokinetic effect

Metabolism-increase

Pharmacodynamic effect

Drug-toxicity-risk-increase

Predicate Object

hasSource URL to product label

Exact-text “Nursing mothers…”

Preceding-text

…

Post-text …

ex:body-1 ex:target-1

ex:annotation-1

about

“Nursing mothers who are ultra-rapid metabolizers may also experience overdose symptoms such as extreme sleepiness, confusion, or shallow breathing.”

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Semantic model - recommendations

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Recommendation example

Predicate Object

drug codeine

biomarker HLA-B*5701

variant 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

““For HLA-B*5701-positive patients, initiating or reinitiating treatment with an abacavir-containing regimen is not recommended”

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Semantic model - references

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Progress

• Since September 2012:• Further annotation training

• Improved agreement• Finalizing first-round annotations (~140)• Proof-of-concept dataset

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Want more information?• Proof-of-concept:

– Dataset (RDF/XML): http://goo.gl/Spd0p

– Example queries: http://goo.gl/3pQ8q (under GRAPH: http://purl.org/net/nlprepository/spl-pharmgx-annotation-poc)

– Integration with W3C Genomic-CDS: https://genomic-cds.googlecode.com/svn

• Google code project– code.google.com/p/swat-4-med-safety/

• Open Data Anotation– http://www.openannotation.org/spec/core/

• Semantic Science Integrated Ontology– http://code.google.com/p/semanticscience/

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Acknowledgements

• 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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Backup Slides

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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

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More about SPLs