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From pharmacogenomic knowledge acquisition to clinical applications: the PharmGKB as a clinical pharmacogenomic biomarker resource.

ABSTRACT: The mission of the Pharmacogenomics Knowledge Base (PharmGKB; www.pharmgkb.org ) is to collect, encode and disseminate knowledge about the impact of human genetic variations on drug responses. It is an important worldwide resource of clinical pharmacogenomic biomarkers available to all. The PharmGKB website has evolved to highlight our knowledge curation and aggregation over our previous emphasis on collecting primary data. This review summarizes the methods we use to drive this expanded scope of 'Knowledge Acquisition to Clinical Applications', the new features available on our website and our future goals.

SUBMITTER: McDonagh EM

PROVIDER: S-EPMC3339046 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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From pharmacogenomic knowledge acquisition to clinical applications: the PharmGKB as a clinical pharmacogenomic biomarker resource.

McDonagh Ellen M EM Whirl-Carrillo Michelle M Garten Yael Y Altman Russ B RB Klein Teri E TE

Biomarkers in medicine 20111201 6

The mission of the Pharmacogenomics Knowledge Base (PharmGKB; www.pharmgkb.org ) is to collect, encode and disseminate knowledge about the impact of human genetic variations on drug responses. It is an important worldwide resource of clinical pharmacogenomic biomarkers available to all. The PharmGKB website has evolved to highlight our knowledge curation and aggregation over our previous emphasis on collecting primary data. This review summarizes the methods we use to drive this expanded scope ...[more]

PMID: 22103613

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Project description:BackgroundEvery year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics.MethodsWe developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles.ResultsOur methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners.ConclusionsThe ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.

Project description:(1) Background: As prescribers, physicians play a decisive role in applying and promoting pharmacogenomic (PGx) testing in clinical practices. So far, little is known about physicians' perspectives on PGx testing in China. The aim of this study was to assess physicians' knowledge of, attitude towards, and experience of PGx testing in China. (2) Methods: A 39-question online survey was developed. Participants were physicians recruited through two platforms, MEDLINKER and "Dazhuanjia". (3) Results: A total of 450 respondents completed the survey and 366 questionnaires were eligible for analysis based on the inclusion criteria. Among all included physicians, 275 (75.1%) had heard of PGx testing before. More than half rated their knowledge of PGx testing as "Fair" (61.5%) while 20.0% chose "Excellent" or "Good" and 18.6% chose "Poor" or "Terrible". "Guidelines, consensus, and treatment paths for disease diagnosis and treatment" (72.7%) were the most preferred sources of information about PGx testing. Respondents were confident in their personal capacity to conduct PGx, with an average score of 3.30 ± 0.09 (out of 5.00). Most respondents (75.6%) believed that PGx could "help to improve efficacy and reduce the incidence of adverse reactions". Targeted cancer therapy (score 78.95 ± 1.26 out of 100) was considered the field where PGx testing had its highest value. Lack of professionals and knowledge (n = 186, 67.6%), high costs of testing (n = 170, 61.8%), and lack of hospitals to offer PGx testing (n = 166, 60.4%) were identified as the primary obstacles to increasing the uptake of PGx testing in China. Academic conference (n = 213, 72.4%) was considered the most efficient way for physicians to obtain information about PGx testing. (4) Conclusions: Physicians in China have poor knowledge about PGx testing; nonetheless, they generally had confidence in their capacity to order PGx testing and positive attitudes towards the use of PGx testing in routine clinical practices. Future efforts to promote the uptake of PGx testing should focus on foundational education and practical training.

Dataset Information

From pharmacogenomic knowledge acquisition to clinical applications: the PharmGKB as a clinical pharmacogenomic biomarker resource.

Publications

From pharmacogenomic knowledge acquisition to clinical applications: the PharmGKB as a clinical pharmacogenomic biomarker resource.

Similar Datasets

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