Evidence map›Paper›PMID 28833066›Full record

ReviewClinical pharmacology and therapeutics2018

Critical Issues and Optimized Practices in Quantification of Protein Abundance Level to Determine Interindividual Variability in DMET Proteins by LC-MS/MS Proteomics.

Deepak Kumar Bhatt, Bhagwat Prasad

Abstract readReview
In one paragraph

Review in Clinical pharmacology and therapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

28 citing papers in PubMed, 61 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Mining the Wheat Grain Proteome.International journal of molecular sciences · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. The Respective Roles of CYP3A4 and CYP2D6 in the Metabolism of Pimozide to Established and Novel Metabolites.Drug metabolism and disposition: the biological fate of chemicals · 2020
    Article
  15. Impact of Microbiome on Hepatic Metabolizing Enzymes and Transporters in Mice during Pregnancy.Drug metabolism and disposition: the biological fate of chemicals · 2020
    Article
  16. Article
  17. Review
  18. Article
  19. Membrane Transporters in Human Parotid Gland-Targeted Proteomics Approach.International journal of molecular sciences · 2019
    Article
  20. Article
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.

Deepak Kumar BhattDepartment of Pharmaceutics, University of Washington, Seattle, Washington, USA.
Bhagwat PrasadDepartment of Pharmaceutics, University of Washington, Seattle, Washington, USA.
University of Washington · US

Funding

PBPK prediction of ontogeny mediated alteration in hepatic drug eliminationR01HD081299 · NICHD · WASHINGTON STATE UNIVERSITY · PI PRASAD, BHAGWAT · 2015 to 2025
$4.6M
NICHD NIH HHS R01 HD081299
6 · The paper itself

Abstract

Protein quantification data on drug metabolizing enzymes and transporters (collectively referred as DMET proteins) in human tissues are useful in predicting interindividual variability in drug disposition. While targeted proteomics is an emerging technique for quantification of DMET proteins, the methodology involves significant technical challenges especially when multiple samples are analyzed in a single study over a long period of time. Therefore, it is important to thoroughly address the critical variables that could affect DMET protein quantification.

Indexed as

PharmacogeneticsHumansPharmacogenomic VariantsPrecision MedicineProteomics

Identifiers

PMID28833066
PMCPMC5816727
OpenAlexW2750262502

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.