Piloting a Comprehensive Knowledge Base for Pharmacovigilance Using Standardized Vocabularies Authors and contributors Vojtech Huser, MD, PhD Jeremy Jao Jon Duke, MD, MS Patrick B. Ryan, PHD Scott D. Nelson, PharmD Richard D. Boyce, PhD Erica A. Voss, MPH Michel Dumontier, PhD Nicholas Tatonetti, PhD Lee Evans Majid Rastegar-Mojarad, MS Abraham G. Hartzema, PhD Johan Ellenius, PhD Rave Harpaz, PhD Magnus Wallberg, MSc Christian Reich, MD, PhD AMIA CRI 3/26/2015
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Piloting a Comprehensive Knowledge Base for Pharmacovigilance Using Standardized Vocabularies
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Piloting a
Comprehensive
Knowledge Base for
Pharmacovigilance
Using Standardized
VocabulariesAuthors and contributors
Vojtech Huser, MD, PhD
Jeremy Jao
Jon Duke, MD, MS
Patrick B. Ryan, PHD
Scott D. Nelson, PharmD
Richard D. Boyce, PhD
Erica A. Voss, MPH
Michel Dumontier, PhD
Nicholas Tatonetti, PhD
Lee Evans
Majid Rastegar-Mojarad, MS
Abraham G. Hartzema, PhD
Johan Ellenius, PhD
Rave Harpaz, PhD
Magnus Wallberg, MSc
Christian Reich, MD, PhD
AMIA CRI 3/26/2015
2
Disclosures
• I disclose that neither I nor my wife have
relevant financial relationships with
commercial interests
3
Problem statement
• An overwhelming amount of information
relevant to drug safety-relevant is being
generated
– stored in a wide array of disparate
information sources
– using differing terminologies
– at a faster pace than ever before
The relevant evidence sourcesSpontaneous adverse
event data(FAERS, VigiBase™,
ClinicalTrials.gov)
Literature(PubMed, SemMed)
Product labeling(SPL, SPC)
Indications / Contraindications
(FDB™)
Observational healthcare data(claims + EHR)
FAERS – FDA Adverse Event Reporting System; SPL – Structured Produce Labeling; SPC – Summary of
Product Characteristics; FDB™ - First DatabankTM EHR – Electronic Health Record;
5
Objective
• Synthesize adverse drug event evidence within a
standard framework for clinical research
– The Observational Health Data and Informatics
Initiative (OHDSI)
• A common data model and standard vocabulary
– Easy to adopt and used by numerous sites
• A suite of tools that improve the value of
observational clinical data
– data characterization, population- level estimation, patient-
level prediction,
– phenotyping, cohort and quality measure design
A new adverse event evidence
base built into OHDSI
Largescale Adverse Effects Related to Treatment
Evidence Standardization (Laertes)
7
The pilot version of Laertes
• Merging sources into the OHDSI
standard vocabulary
• The data schema
• Current progress
Merging the sources
Drugs (RxNorm)
Conditions (SNOMED)
Spontaneous adverse event data
(FAERS, VigiBase™, ClinicalTrials.gov)
MedDRA
->
SNOMED
Freetext,
ATC
-> RxNorm
Literature(PubMed, SemMed)
MeSH, UMLS
-> SNOMED
MeSH,
UMLS
-> RxNorm
Product labeling(SPL, SPC)
Freetext ->
MedDRA®
->
SNOMED
SPL Set ID
-> RxNorm
Indications / Contraindications
(FDB™)
ICD-9-CM
->
SNOMED
NDC/GenS
eqNum
-> RxNorm
Observational healthcare data(claims + EHR)
ICD-9-CM,
ICD-10
->
SNOMED
NDC/GPI/ATC
-> RxNorm
Drug classifications
(ATC, NDF-RT)
Condition classifications(MedDRA®, Ontology of
Adverse Events)
Source to Drug
MappingSource to
HOI Mapping
Evidence
Sources
Current progress on evidence sources
Spontaneous adverse event data
(FAERS, VigiBase™, ClinicalTrials.gov)
Literature(PubMed, SemMed)
Product labeling(SPL, SPC)
Indications / Contraindications
(FDB™)
Observational healthcare data(claims + EHR)
Evidence
Sources
PubMed (Avillach et al.):
• Case reports: 84,181
• Clinical trials: 25,813
• Other: 1,146
SemMed (Kilicoglu et al)
• Case reports: 2,372
• Clinical trials: 1,169
Avillach P, Dufour JC, Diallo G, Salvo F, Joubert M, Thiessard F, Mougin F, Trifirò G, Fourrier-Réglat A, Pariente A, Fieschi M. Design and val idation of an automated
method to detect known adverse drug reactions in MEDLINE: a contribution from the EU-ADR project. J Am Med Inform Assoc. 2013 May 1;20(3):446-52
Kilicoglu H, Rosemblat G, Fiszman M, Rindflesch TC. Constructing a semantic predication gold standard from the biomedical literature. BMC Bioinformatics. 2011 Dec
20;12:48
Duke, Jon, Jeff Friedlin, and Patrick Ryan. "A quantitative analysis of adverse events and “overwarning” in drug labeling." Archives of internal medicine 171.10 (2011): 941-