1. STDMIG-PGx Implementation in Clinical Trials Using Legacy PGx DB
Eun-Young Kim, MD, PhD1, Su-Yeon Park, BS2, Na-Yul Kim, MS2, Eun-Young Cha, MS2, Jae-Gook Shin, MD, PhD1,2
1Department of Clinical Pharmacology, 2Deparment of Pharmacology and PharmacoGenomics Research Center
Inje University College of Medicine, Busan, Korea
Introduction
Results
Required data standardization in clinical trials as developing electronic data capture technologies
Clinical Data Interchange Standards Consortium (CDISC, a standards developing organization, issued Study Data Tabulation Model (SDTM) for clinical trial data standardization
The Unite States Food and Drug Administration (FDA): clinical trial data submission as a SDTM format in product application process
The mapping specification after comparison between data variables in our legacy PGx DB and SDTMIG-PGX domains and adding more required data
The auto-converter based on the above work: developed and applied to generate the standard format of PGx datasets using genotype results of clinical trial subjects
Used genotype data: CYP2C9 (warfarin) and CYP2D6 (dextromethorphan) gene-related data (Figure 4)
Generated PB, PF, SB, and newly defined SB2 domain data in Figure 5
SDTM Implementation Guide for Pharmacogenomics/Genetics (SDTMIG-PGx, Figure 1): to guide the organization, structure, and format of gene-related data to submit into regulatory authority such as FDA (2015)
Purpose: to develop STDMIG-PGx implementation tool using our legacy PGx DB ( Figure 1) which is not compatible to SDTMIG-PGx guide
Figure 1. SDTMIG-PGx domains and datasets by CDISC PGx team
Materials and Methods
The legacy DB (Figure 2): subject, sample, genetic test results, gene information, etc.
The data standardization process: demonstrated on Figure 3
1. The comparison and mapping specification between STDMIG-PGx domains and our legacy data variables
2. Adding more required data (e.g. terms by Human Genome Variation Society)
3. The auto-converter development based on the work
- Generated newly defined SB2 domain for easily identifying drug related genotype to phenotype relationship: poor metabolizer to ultrarapid metabolizer
PHP ( and MySQL ( for AP
Tested the converter using previous clinical trial data included PGx test results
Figure 4. Auto-converter of PGx data and the extracted standardized datasets
Figure 2. Data properties of our legacy PGx DB
Figure 5. Extracted standardized datasets from PB, PF, SB domains and newly defined our SB2 domain
Conclusion
Developed an auto-converter for SDTMIG-PGx implementation using our legacy PGx DB
Generated new domain, SB2, to identify drug metabolizing activity in a subject based on his/her genotype
- Improving clinical trial data quality and strengthening competitiveness in clinical trial industry
Figure 3. Data standardization process using legacy PGx DB