Evidence map›Paper›PMID 32978778›Full record

ArticleClinical pharmacology and therapeutics2021

PharmGKB Tutorial for Pharmacogenomics of Drugs Potentially Used in the Context of COVID-19.

Rachel Huddart, Michelle Whirl-Carrillo, Russ B Altman, Teri E Klein

Abstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. INTEDE 2.0: the metabolic roadmap of drugs.Nucleic acids research · 2024
    Article
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rachel HuddartDepartment of Biomedical Data Science, Stanford University, Stanford, California, USA.
Michelle Whirl-CarrilloDepartment of Biomedical Data Science, Stanford University, Stanford, California, USA.
Russ B AltmanDepartment of Biomedical Data Science, Stanford University, Stanford, California, USA.
Teri E KleinDepartment of Biomedical Data Science, Stanford University, Stanford, California, USA.

Funding

PharmGKB: pharmacogenomics knowledge for precision medicineR24GM061374 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO, KLEIN, TERI ELLEN · 2010 to 2018
$25.2M
PharmGKB: pharmacogenomics discovery and implementationU24HG010615 · NHGRI · STANFORD UNIVERSITY · PI TERI Ellen KLEIN, Michelle Whirl-Carrillo · 2020 to 2026
$9.5M
NHGRI NIH HHS U24 HG010615NIGMS NIH HHS R24 GM061374
6 · The paper itself

Abstract

Pharmacogenomics (PGx) is a key area of precision medicine, which is already being implemented in some health systems and may help guide clinicians toward effective therapies for individual patients. Over the last 2 decades, the Pharmacogenomics Knowledgebase (PharmGKB) has built a unique repository of PGx knowledge, including annotations of clinical guideline and regulator-approved drug labels in addition to evidence-based drug pathways and annotations of the scientific literature. All of this knowledge is freely accessible on the PharmGKB website. In the first of a series of PharmGKB tutorials, we introduce the PharmGKB coronavirus disease 2019 (COVID-19) portal and, using examples of drugs found in the portal, demonstrate some of the main features of PharmGKB. This paper is intended as a resource to help users become quickly acquainted with the wealth of information stored in PharmGKB.

Indexed as

COVID-19COVID-19 Drug TreatmentGene OntologyKnowledge BasesPharmacogeneticsAntiviral AgentsHumansMedication Therapy ManagementPharmacogenomic TestingPrecision MedicineAntiviral Agents

Identifiers

PMID32978778
PMCPMC7537078

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.