Evidence map›Paper›PMID 36320126›Full record

ArticleApplied spectroscopy2023

Quantification of Drugs in Brain and Liver Mimetic Tissue Models Using Raman Spectroscopy.

Nathan Woodhouse, Jan Majer, Peter Marshall, Steve Hood, Ioan Notingher

Open access · hybridFull text read
In one paragraph

Article in Applied spectroscopy, 2023. 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
1.3field-weighted citation impact, top 15% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Raman Spectroscopy as a Tool to Study the Pathophysiology of Brain Diseases.International journal of molecular sciences · 2023
    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 at 2 institutions in 1 country.

Nathan WoodhouseSchool of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK.
Jan Majer113460GlaxoSmithKline, Stevenage, UK.
Peter Marshall113460GlaxoSmithKline, Stevenage, UK.
Steve Hood113460GlaxoSmithKline, Stevenage, UK.
Ioan NotingherSchool of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK.ORCID 0000-0002-5360-230X
GlaxoSmithKline (United Kingdom) · GBUniversity of Nottingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative analysis of drug delivery with in biological systems is an integral challenge in drug development. Analytical techniques are important for assessing both drug target delivery, target action, and drug toxicology. Using mimetic tissue models, we have investigated the efficacy of Raman spectroscopy in quantitative detection of alkyne group and deuterated drugs in rat brain and rat liver tissue models. Lasers with 671 nm and 785 nm wavelengths were assessed for their feasibility in this application due to opposing relative benefits and disadvantages. Thin tissue sections have been tested as a practical means of reducing autofluorescent background by minimizing out-of-focus tissue and therefore maximizing photobleaching rates. Alkyne-tagged drugs were quantitatively measured at 18 ± 5 μg/g drug/tissue mass ratio in rat brain and at 34 ± 6 μg/g in rat liver. Quantification calibration curves were generated for a range of concentrations from 0-500 μg/g. These results show the potential of Raman spectroscopy as a diffraction-limited spatially resolved imaging technique for assessing drug delivery in tissue applications.

Indexed as

LiverSpectrum Analysis, RamanAlkynesBrainPharmaceutical PreparationsAlkynesPharmaceutical PreparationsDrug deliverydrug quantificationmicroscopyRaman spectroscopy

Identifiers

PMID36320126
PMCPMC10034474
OpenAlexW4307970831

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read59
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.