1. Pharmacogenomics Data Standardization using Clinical Element Models

2. Pharmacogenomics Ontology (PHONT) Network Resource
Pharmacogenomics Research Network (PGRN)
Diverse network of PGx research sites
Goal: Understand how genetic variations affect an individual's response to medications
Normalize data representations
Disease phenotypes
Drugs and drug classes

3. PGRN Data Dictionary Standardization
4483 PGRN Variables
SHARPn CEMs: Patient, Noted Drug, Disease/Disorder, Lab Observation
UMLS Semantic Types

4. Categories of Mapped Variables

5. Person Model Examples of Variables Person PatientExternalId (0-M)
Medical Record Number
data (II)
SSN
Study ID
PersonName (1-M)
First Name
GivenName (0-1)
Last Name
data (ST) …
Date of Birth
Birthdate (0-1)
Year of Birth
data (TS)
AdministrativeGender (0-1)
Patient Gender
data (CD)
AdministrativeRace (0-1)
Patient Race
AdministrativeEthnicGroup (0-1)
Self-Reported Ethnicity …

6. Drug Administration Model
Examples of Variables
NotedDrug
Code
Is the patient taking a diuretic?
data (CD)
Has the subject started any new medications?
StartTimeUnconstrained
data (TS/CD/ST)
EstimatedInd
Date of last antihypertensives
data (CO)
Medication start date
TakenDoseLowerLimit
Dose
Have you taken digoxin in the past?
data (PQ)
RouteMethodDevice
data (CD)
Time on tamoxifen
StatusChange
Subject
If potassium supplementation added, specify daily dose …

7. Example: Patient Took 300 mg Acetaminophen
"300"

8. Categories of Unmapped Variables

9. Unmapped Variables
Some variables are not currently represented by PHONT (SHARP) CEMs
Computed research data (e.g., PK/PD)
Genomic data
Psychometric data
Work with SDOs to address these gaps
CIMI community on extant or new CEMs
HL7 and CDISC for clinical genomics data
W3C, NLM, & SNOMED PGx ontologies

10. Conclusions
Demonstrated CEMs can be used to normalize PGRN data dictionaries
Future Work
Incorporate recently developed SHARP CEMs
Collaborate with SHARP to fill gaps for PGx
Establish best practices
Complex data elements (e.g., semantic links)
Project-specific/workflow data vs EMR

11. PHONT Personnel Scientific Nosologist IT Project Management
Christopher G. Chute
Robert R. Freimuth
Jyotishman Pathak
Qian Zhu
Guoqian Jiang
Nosologist
Donna Ihrke IT
Zonghui Lian
Scott Bauer
Deepak Sharma
Project Management
Mandy Ager
Matthew Durski