Evidence map›Paper›PMID 32365122›Full record

ArticlePloS one2020

PG-path: Modeling and personalizing pharmacogenomics-based pathways.

Joo Young Hong, Ju Han Kim

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 29% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions.International journal of molecular sciences · 2021
    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

2 authors at 1 institution in 1 country.

Joo Young HongDivision of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea.
Ju Han KimDivision of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea.ORCID 0000-0003-1522-9038
Seoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A pharmacogenomics-based pathway represents a series of reactions that occur between drugs and genes in the human body after drug administration. PG-path is a pharmacogenomics-based pathway that standardizes and visualizes the components (nodes) and actions (edges) involved in pharmacokinetic and pharmacodynamic processes. It provides an intuitive understanding of the drug response in the human body. A pharmacokinetic pathway visualizes the absorption, distribution, metabolism, and excretion (ADME) at the systemic level, and a pharmacodynamic pathway shows the action of the drug in the target cell at the cellular-molecular level. The genes in the pathway are displayed in locations similar to those inside the body. PG-path allows personalized pathways to be created by annotating each gene with the overall impact degree of deleterious variants in the gene. These personalized pathways play a role in assisting tailored individual prescriptions by predicting changes in the drug concentration in the plasma. PG-path also supports counseling for personalized drug therapy by providing visualization and documentation.

Indexed as

SoftwareComputational BiologyDatabases, GeneticDrug-Related Side Effects and Adverse ReactionsDrug TherapyGastrointestinal AbsorptionGenetic Association StudiesHumansInactivation, MetabolicInformation Storage and RetrievalMetabolic Networks and PathwaysModels, TheoreticalPharmaceutical PreparationsPharmacogeneticsPrecision MedicinePharmaceutical Preparations

Identifiers

PMID32365122
PMCPMC7197763
OpenAlexW3022143520

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.