Evidence map›Paper›PMID 27919805›Full record

ReviewDrug discovery today2017

UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research.

Ala F Nassar, Terence Wu, Samuel F Nassar, Adam V Wisnewski

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Drug discovery today, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Untargeted Metabolic Phenotyping by LC-MS.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
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  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

4 authors.

Ala F NassarSchool of Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA; Department of Chemistry, University of Connecticut, 55 North Eagleville Road, Storrs, CT, USA. Electronic address: ala.nassar@yale.edu.
Terence WuWest Campus Analytical Core, Yale University, West Haven, CT, USA.
Samuel F NassarYale School of Medicine, Departments of Neurology and Immunobiology, New Haven, CT 06511, USA.
Adam V WisnewskiSchool of Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA.

Funding

Deciphering Occupational Asthma Pathogenesis Caused by IsocyanateR01OH010941 · OH · YALE UNIVERSITY · PI WISNEWSKI, ADAM · 2016 to 2019
$2.2M
Biochemistry connecting glutathione and isocyanate asthmaR21OH010438 · OH · YALE UNIVERSITY · PI WISNEWSKI, ADAM · 2013 to 2014
$452k
NIOSH CDC HHS R01 OH010941NIOSH CDC HHS R21 OH010438
6 · The paper itself

Abstract

Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development.

Indexed as

MetabolomicsPharmaceutical ResearchAnimalsChromatography, LiquidDrug DiscoveryHumansMass Spectrometry

Identifiers

PMID27919805
PMCPMC5721520

What OpenQuestion holds

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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.