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Preemptive and multi-variant genotyping is suggested to improve the safety of patient drug therapy. The number of South Koreans who would benefit from this approach is unknown. We aimed to quantify the number of patients who may experience serious adverse drug events (ADEs) due to high-risk pharmacogenetic variants and who may benefit from preemptive genotyping. The health claims dataset of the Korean Health Insurance Review and Assessment service for 3 % of the South Korean population for year 2011 was used to calculate the number of patients exposed to 84 drugs covered by National Health Insurance with pharmacogenomic biomarkers. The product of ADE risk-conferring genotype prevalence, ADE prevalence rates, and genotype effect sizes in South Koreans or East Asians derived from published literature and the 1000 Genomes Project, and the drug exposure data were solved to estimate the number of South Koreans in whom preemptive genotyping may prevent serious ADEs. Among 1,341,077 patients in the dataset with prescriptions, 47.4 % were prescribed a drug whose response was affected by genetic variants and 31.9 % were prescribed at least one drug with serious ADEs modulated by these variants. Without genetic testing, the number of South Korean patients predicted to experience serious ADEs due to their higher ADE risk genotypes was estimated at 729. Extrapolating this to the total South Korean population indicated that approximately 24,300 patients in 2011 might have benefitted from preemptive genotyping. This study quantified the number of South Korean patients predicted to have serious ADEs and demonstrated the need for preemptive genotyping to assist safer drug therapy in South Korea.

Integration of controlled vocabulary-based electronic health record (EHR) observational data is essential for real-time large-scale pharmacovigilance studies. To provide a semantically enriched adverse drug reaction (ADR) dictionary for post-market drug safety research and enable multicenter EHR-based extensive ADR signal detection and evaluation, we developed a comprehensive controlled vocabulary-based ADR signal dictionary (CVAD) for pharmacovigilance. A CVAD consists of (1) administrative disease classifications of the International Classification of Diseases (ICD) codes mapped to the Medical Dictionary for Regulatory Activities Preferred Terms (MedDRA® PTs); (2) two teaching hospitals’ codes for laboratory test results mapped to the Logical Observation Identifiers Names and Codes (LOINC) terms and MedDRA® PTs; and (3) clinical narratives and ADRs encoded by standard nursing statements (encoded by the International Classification for Nursing Practice [ICNP]) mapped to the World Health Organization–Adverse Reaction Terminology (WHO-ART) terms and MedDRA® PTs. Of the standard 4514 MedDRA® PTs from Side Effect Resources (SIDER) 4.1, 1130 (25.03%), 942 (20.86%), and 83 (1.83%) terms were systematically mapped to clinical narratives, laboratory test results, and disease classifications, respectively. For the evaluation, we loaded multi-source EHR data. We first performed a clinical expert review of the CVAD clinical relevance and a three-drug ADR case analyses consisting of linezolid-induced thrombocytopenia, warfarin-induced bleeding tendency, and vancomycin-induced acute kidney injury. CVAD had a high coverage of ADRs and integrated standard controlled vocabularies to the EHR data sources, and researchers can take advantage of these features for EHR observational data-based extensive pharmacovigilance studies to improve sensitivity and specificity.