PharmGKB: Pharmacogenetic Database

PharmGKB: Pharmacogenetic Database

PharmGKB is a publicly available internet research tool that provides information about how genetic variation among individuals contributes to differences in reactions to drugs. Developed by Stanford University and funded by the National Institutes of Health (NIH), PharmGKB is the largest pharmacogenetic database.

The information in the database contains pharmacogenetic prescribing information with dosing guidelines, annotated drug labels, pathways, very important pharmacogenes (VIPs), clinical annotations, and variant annotations.

PharmGKB levels of evidence

A very important aspect of PharmGKB is the level of evidence assigned to every clinical annotation. The level of evidence is a measure of confidence in the association as determined by the PharmGKB curators based on several criteria. The data collected includes published clinically actionable gene-drug associations and genotype-phenotype relationships. Curators combine and summarize the associations from each publication and produce a single clinical annotation.

The single clinical annotation includes a summary for each genotype-phenotype interaction and is supported by the studies that reported the association. The studies are used to assign a level of evidence score for each clinical annotation and are included in the database with their unique PubMed identifiers.

The level of evidence is based on different factors including replication of the association, P value (after correction for multiple-hypothesis testing, if applicable), and odds ratio, if available.

Retrieved from

Level 1A: CPIC or medical society-endorsed PGx guideline, or implemented at a PGRN site or in another major health system
Level 1B: Cohort studies with statistical significance and strong effect size
Level 2A: Established drug response variant likely to have functional significance including VIPs (Very Important Pharmacogenes)
Level 2B: Association has been replicated but some studies do not show statistical significance or have small effect size
Level 3: Annotation based on a single significant (not yet replicated) study or on multiple studies lacking clear association
Level 4: Annotation based on a case report, non-significant study or in vitro, molecular or functional assay evidence

For example, a number of studies have reported the association between variants in the CYP2C19 gene and efficacy as well as toxicity of citalopram and escitalopram in depression. PharmGKB includes 55 annotations supported by a number of clinical trials and a meta-analysis. The meta-analysis showed a very strong correlation between CYP2C19 genotypes and plasma levels of citalopram and escitalopram. Based on this strong correlation and a CPIC endorsed pharmacogenetic guideline for CYP2C19, PharmGKB has assigned the highest level of evidence, 1A, to this association.

For more information about levels of evidence of clinical annotations please refer to Whirl-Carrillo M, et al 2012 Clinical pharmacology and therapeutics [Article:22992668]


TreatGxPlus is an evidence-based pharmacogenetic service that provides safe, effective, and personalized prescribing options. The TreatGxPlus pharmacogenetic test was developed using an evidence-based approach, following a rigorous review process of scientific studies, databases and professional guidelines including PharmGKB, CPIC – Clinical Pharmacogenetics Implementation Consortium, and DPWG – Dutch Pharmacogenetics Working Group. This process allows us to select genetic variants with strong evidence for a significant clinical outcome indicating a change in dose of a medication, or a change of medication.

Unlike any other system, the TreatGxPlus software starts by considering an individual’s condition and combines the individual’s unique pharmacogenetic data with non-genetic information, including the clinical stage of the condition, the biophysical profile of the individual (age, gender, renal function, etc.), and concurrent medications.

In Canada, TreatGxPlus is brought to you in partnership with LifeLabs

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