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.
Subject(s)
Pharmacogenetics/standards , Precision Medicine/standards , Databases, Genetic/standards , Drug Labeling/standards , Drug Prescriptions/standards , Humans , Knowledge Bases , Prescription Drugs/standards , Reproducibility of ResultsABSTRACT
Pharmacogenomics (PGx) can be seen as a model for biomedical studies: it includes all disease areas of interest and spans in vitro studies to clinical trials, while focusing on the relationships between genes and drugs and the resulting phenotypes. This review will examine different characteristics of PGx study publications and provide examples of excellence in framing PGx questions and reporting their resulting data in a way that maximizes the knowledge that can be built on them.
Subject(s)
Periodicals as Topic , Pharmacogenetics/methods , Terminology as Topic , Translational Research, Biomedical/methods , Humans , Periodicals as Topic/trends , Pharmacogenetics/trends , Translational Research, Biomedical/trendsSubject(s)
Antineoplastic Agents/pharmacology , Neoplasms/drug therapy , Pharmacogenomic Variants , Pyrimidines/pharmacology , Sulfonamides/pharmacology , Antineoplastic Agents/adverse effects , Clinical Trials as Topic , Gene Regulatory Networks , Humans , Indazoles , Neoplasms/genetics , Pyrimidines/adverse effects , Sulfonamides/adverse effects , Treatment OutcomeSubject(s)
Anti-Inflammatory Agents, Non-Steroidal , Ibuprofen , Metabolic Networks and Pathways/drug effects , Metabolic Networks and Pathways/genetics , Pharmacogenetics , Anti-Inflammatory Agents, Non-Steroidal/administration & dosage , Anti-Inflammatory Agents, Non-Steroidal/adverse effects , Anti-Inflammatory Agents, Non-Steroidal/pharmacokinetics , Biological Transport/genetics , Drug Interactions/genetics , Humans , Ibuprofen/administration & dosage , Ibuprofen/adverse effects , Ibuprofen/pharmacokinetics , Inactivation, Metabolic/genetics , Kidney/drug effects , Kidney/metabolism , Liver/drug effects , Liver/metabolismABSTRACT
The Clinical Pharmacogenetics Implementation Consortium (CPIC) publishes genotype-based drug guidelines to help clinicians understand how available genetic test results could be used to optimize drug therapy. CPIC has focused initially on well-known examples of pharmacogenomic associations that have been implemented in selected clinical settings, publishing nine to date. Each CPIC guideline adheres to a standardized format and includes a standard system for grading levels of evidence linking genotypes to phenotypes and assigning a level of strength to each prescribing recommendation. CPIC guidelines contain the necessary information to help clinicians translate patient-specific diplotypes for each gene into clinical phenotypes or drug dosing groups. This paper reviews the development process of the CPIC guidelines and compares this process to the Institute of Medicine's Standards for Developing Trustworthy Clinical Practice Guidelines.
Subject(s)
Genetic Testing/methods , Pharmacogenetics/methods , Practice Guidelines as Topic , Genotype , Humans , Pharmaceutical Preparations/administration & dosage , Phenotype , Practice Patterns, Physicians'Subject(s)
Antineoplastic Agents, Alkylating/pharmacology , Antineoplastic Agents, Alkylating/pharmacokinetics , Cytochrome P-450 Enzyme System/genetics , Ifosfamide/pharmacology , Ifosfamide/pharmacokinetics , Neoplasms/genetics , Cytochrome P-450 Enzyme System/metabolism , Humans , Neoplasms/drug therapy , Neoplasms/metabolism , Pharmacogenetics , Signal TransductionSubject(s)
Antineoplastic Agents, Hormonal/pharmacokinetics , Breast Neoplasms/drug therapy , Cytochrome P-450 CYP2D6/genetics , Receptors, Estrogen/antagonists & inhibitors , Tamoxifen/pharmacokinetics , Antineoplastic Agents, Hormonal/metabolism , Antineoplastic Agents, Hormonal/therapeutic use , Arylsulfotransferase/genetics , Arylsulfotransferase/metabolism , Breast Neoplasms/genetics , Breast Neoplasms/metabolism , Cytochrome P-450 CYP2D6/metabolism , Female , Humans , Pharmacogenetics , Signal Transduction , Tamoxifen/metabolism , Tamoxifen/therapeutic useABSTRACT
The Pharmacogenomics Knowledge Base, PharmGKB, is an interactive tool for researchers investigating how genetic variation affects drug response. The PharmGKB Web site, http://www.pharmgkb.org , displays genotype, molecular, and clinical knowledge integrated into pathway representations and Very Important Pharmacogene (VIP) summaries with links to additional external resources. Users can search and browse the knowledgebase by genes, variants, drugs, diseases, and pathways. Registration is free to the entire research community, but subject to agreement to use for research purposes only and not to redistribute. Registered users can access and download data to aid in the design of future pharmacogenetics and pharmacogenomics studies.
Subject(s)
Internet , Knowledge Bases , Pharmacogenetics/methods , Algorithms , Databases, Genetic , HumansSubject(s)
Diuretics/pharmacokinetics , Hypertension/drug therapy , Diuretics, Potassium Sparing/pharmacokinetics , Female , Genetic Association Studies , Humans , Hypertension/genetics , Male , Pharmacogenetics , Sodium Chloride Symporter Inhibitors/pharmacokinetics , Sodium Potassium Chloride Symporter Inhibitors/pharmacokineticsABSTRACT
The need for efficient text-mining tools that support curation of the biomedical literature is ever increasing. In this article, we describe an experiment aimed at verifying whether a text-mining tool capable of extracting meaningful relationships among domain entities can be successfully integrated into the curation workflow of a major biological database. We evaluate in particular (i) the usability of the system's interface, as perceived by users, and (ii) the correlation of the ranking of interactions, as provided by the text-mining system, with the choices of the curators.