Evidence map›Paper›PMID 23523629›Full record

ReviewAdvanced drug delivery reviews2013

Delivering systems pharmacogenomics towards precision medicine through mathematics.

Yaqun Wang, Ningtao Wang, Jianxin Wang, Zhong Wang, Rongling Wu

Abstract readReview
In one paragraph

Review in Advanced drug delivery reviews, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Mapping genes for drug chronotherapy.Drug discovery today · 2018
    Review
  3. Mapping complex traits as a dynamic system.Physics of life reviews · 2015
    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

5 authors.

Yaqun WangCenter for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA.
Ningtao Wang
Jianxin Wang
Zhong Wang
Rongling Wu

Funding

Penn State Clinical and Translational Science InstituteUL1TR000127 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI SINOWAY, LAWRENCE I · 2012 to 2015
$17.1M
NCATS NIH HHS UL1 TR000127
6 · The paper itself

Abstract

The latest developments of pharmacology in the post-genomic era foster the emergence of new biomarkers that represent the future of drug targets. To identify these biomarkers, we need a major shift from traditional genomic analyses alone, moving the focus towards systems approaches to elucidating genetic variation in biochemical pathways of drug response. Is there any general model that can accelerate this shift via a merger of systems biology and pharmacogenomics? Here we describe a statistical framework for mapping dynamic genes that affect drug response by incorporating its pharmacokinetic and pharmacodynamic pathways. This framework is expanded to shed light on the mechanistic and therapeutic differences of drug response based on pharmacogenetic information, coupled with genomic, proteomic and metabolic data, allowing novel therapeutic targets and genetic biomarkers to be characterized and utilized for drug discovery.

Indexed as

Models, BiologicalPharmacogeneticsPrecision MedicineDrug TherapyHumansSystems Biology

Identifiers

PMID23523629
PMCPMC3988791

What OpenQuestion holds

Textmetadata
LicenceTDM
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.