Characterization of CYP2D6 reference materials by GeT-RM

The CDC-based Genetic Testing Reference Material Coordination Program (GeT-RM) has published an extended panel of Coriell samples with CYP2D6 genotype information.

Not only have the existing 137 samples been extensively re-tested on different platforms, selected samples have also been sequenced to determine the haplotype of novel or rare allelic variants which have not been characterized in the past. Furthermore, an additional 42 samples with rare, unusual or complex diplotypes were extensively interrogated. All new information was submitted to PharmVar to facilitate dissemination to PharmGKB and CPIC.

These publicly available samples will support academic research as well as the quality-assurance and quality-control programs of clinical laboratories performing CYP2D6 testing. 

Dr. Lisa Kalman of the CDC will present the project at the Annual Meeting & Expo of the Association for Molecular Pathology on Nov 7-9 in Baltimore.

Annotated Swissmedic Drug labels now available on PharmGKB

PharmGKB now has annotated drug labels available from the Swiss Agency of Therapeutic Products (Swissmedic), a regulatory authority responsible for the authorization and supervision of therapeutic products in Switzerland.

The Swissmedic drug label annotations are sourced through a collaboration with the Pharmaceutical Care Research Group (PCRG), Department of Pharmaceutical Sciences, University of Basel. The PCRG group screened and translated pharmacogenomic (PGx) relevant information in the Summaries of Product Characteristics (SmPCs) of all Swissmedic labels through natural language processing (NLP). Using these translations and analysis, PharmGKB annotated Swissmedic drug labels based on our criteria for PGx information.

Like our FDA drug label information, we provide a summary and excerpt of PGx information from the Swissmedic SmPC. Each Swissmedic drug label annotation is also given a PGx level of evidence, and a link to the original full text label on the AmiKo Web (https://amiko.oddb.org/). If the label provides dosing adjustments based on genetic information or metabolizer phenotypes, or states that a drug is either indicated or contraindicated for a particular set of patients, the label annotation will be tagged with "dosing info" or "alternative drug" tag.

It is likely that there are other Swissmedic drug labels that contain PGx information, and PharmGKB welcomes any feedback regarding PGx information within the labels from Swissmedic or other medicine agencies around the world.

View our complete list of drug labels with PGx information.

Public comment period for CPIC allele function assignment SOP

CPIC is inviting public comments on their draft SOP for assigning function to pharmacogenomic alleles.

CPIC has been assigning “function” to pharmacogenomic alleles since its inception. This has already led to a Delphi process and consensus publication on standardizing terms used for allele function and pharmacogenetic phenotypes for some genes. The unique contribution of CPIC is to assign an allele function that leads to a phenotype assignment that can drive clinical prescribing actionability. Now that several types of genes involved in drug pharmacokinetics and pharmacodynamics have been included in CPIC guidelines, CPIC leadership considers it timely to establish written SOPs that describe the criteria used for assigning pharmacogenetic allele function in greater detail. Many elements of this SOP have been tested in preparation of recent guidelines.

The SOP can be downloaded from the Resources section of the CPIC website. Comments and feedback should be sent to Kelly Caudle (Kelly.caudle@stjude.org) by October 23^rd 2019.

PharmGKB releases automated annotations

We are excited to announce that automated annotations of pharmacogenomic information in the scientific literature are now available from PharmGKB. These annotations have been produced using the PGxMine project, the result of a collaboration with Dr. Jake Lever at Stanford University.

PGxMine uses a supervised machine learning algorithm to carry out text mining of PubMed abstracts and full-text articles from PubMed Central. Sentences which contain a chemical and a variant are found using the PubTator Central resource and subsequently identified as being highly likely to contain PGx information are highlighted as an automated annotation. Automated annotations will also be used by PharmGKB curators to identify papers for manual curation.

The new automated annotations tab can now be found on drug, gene, variant and haplotype pages on the PharmGKB website. Each automated annotation displays the relevant sentence identified by PGxMine as well as information about the article where the sentence was found. PGxMine was deliberately designed to have a high level of precision at the expense of a lower recall rate. This means that PGx associations that are mentioned in multiple papers should be captured by the algorithm while associations mentioned in only one paper may be missed.

Unlike variant annotations or clinical annotations, which are manually curated by PharmGKB curators, automated annotations are found using computational methods only. The accuracy or relevance of these annotations has not been checked by PharmGKB staff. Users should therefore be aware that there is some noise associated with these annotations. Users should also note that this is not a comprehensive annotation of all published articles. Articles which are only accessible through a journal subscription cannot be annotated by PGxMine and will not be displayed in the automated annotations section.

A paper describing PGxMine in greater detail has been accepted by the Pacific Symposium on Biocomputing and will be available online soon. We will add the URL as a comment to this blog post as soon as it is available. An FAQ page about automated annotations and the PGxMine project can be found on the PharmGKB website.

Future updates of our automated annotations will be tied to the update schedule of PubTator Central. The PGxMine code is open source and can be accessed at GitHub while a full data dump can be accessed at Zenodo.