An Evidence-Based Framework for Evaluating Pharmacogenomics Knowledge for Personalized Medicine

Abstract

Clinical annotations are one of the most popular resources available on the Pharmacogenomics Knowledgebase (PharmGKB). Each clinical annotation summarizes the association between variant-drug pairs, shows relevant findings from the curated literature, and is assigned a level of evidence (LOE) to indicate the strength of support for that association. Evidence from the pharmacogenomic literature is curated into PharmGKB as variant annotations, which can be used to create new clinical annotations or added to existing clinical annotations. This means that the same clinical annotation can be worked on by multiple curators over time. As more evidence is curated into PharmGKB, the task of maintaining consistency when assessing all the available evidence and assigning an LOE becomes increasingly difficult. To remedy this, a scoring system has been developed to automate LOE assignment to clinical annotations. Variant annotations are scored according to certain attributes, including study size, reported P value, and whether the variant annotation supports or fails to find an association. Clinical guidelines or US Food and Drug Administration (FDA)-approved drug labels which give variant-specific prescribing guidance are also scored. The scores of all annotations attached to a clinical annotation are summed together to give a total score for the clinical annotation, which is used to calculate an LOE. Overall, the system increases transparency, consistency, and reproducibility in LOE assignment to clinical annotations. In combination with increased standardization of how clinical annotations are written, use of this scoring system helps to ensure that PharmGKB clinical annotations continue to be a robust source of pharmacogenomic information.

Figure 1

The PharmGKB curation process. Blue boxes represent primary literature and source documents that are curated. Green boxes represent basic PharmGKB annotations derived from curated literature and documents. Orange boxes represent PharmGKB annotations based on aggregated and evaluated basic annotations and curated literature. CPIC, Clinical Pharmacogenetics Implementation Consortium; DPWG, Royal Dutch Association for the Advancement of Pharmacy‐ Pharmacogenetics Working Group; EMA, European Medicines Agency; FDA, US Food and Drug Administration; HCSC, Health Canada (Santé Canada); PD, pharmacodynamics; PharmGKB, Pharmacogenomics Knowledgebase; PK, pharmacokinetics; PMDA, Pharmaceuticals and Medical Devices Agency, Japan; VIPs, Very Important Pharmacogenes.

Figure 2

Illustrated example of clinical annotation scoring. FDA, US Food and Drug Administration; HR, hazard ratio; LOE, level of evidence; OR, odds ratio; RR, relative risk.

Figure 3

Venn diagram showing the number of level 1A clinical annotations with PGx guideline or drug label annotations as support. CPIC, Clinical Pharmacogenetics Implementation Consortium; DPWG, Royal Dutch Association for the Advancement of Pharmacy‐ Pharmacogenetics Working Group; FDA, US Food and Drug Administration; PGx, pharmacogenomics.

Figure 4

An example gene‐level clinical annotation. All clinical annotations provide genotype‐ or allele‐specific summaries of the curated evidence (Box 1) and display the LOE along with associated genes, haplotypes, drugs and phenotypes (Box 2). The Limited Evidence tag on gene‐level clinical annotations is added to alleles which are supported by substantially less evidence than other alleles in the same annotation (Box 3). The clinical annotation score and a scoring breakdown are displayed under the main annotation text (Box 4). This annotation can be viewed on the PharmGKB website at https://www.pharmgkb.org/clinicalAnnotation/1444842106. CPIC, Clinical Pharmacogenetics Implementation Consortium; LOE, level of evidence; PharmGKB, Pharmacogenomics Knowledgebase; PK, pharmacokinetic.