Evidence map›Paper›PMID 34793633›Full record

ArticleClinical and translational science2022

Physicochemical properties determining drug detection in skin.

Wout Bittremieux, Rohit S Advani, Alan K Jarmusch, Shaden Aguirre, Aileen Lu, Pieter C Dorrestein, Shirley M Tsunoda

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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  6. Physicochemical properties determining drug detection in skin.Clinical and translational science · 2022
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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

7 authors at 4 institutions in 2 countries.

Wout BittremieuxSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-3105-1359
Rohit S AdvaniSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA.
Alan K JarmuschSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA.
Shaden AguirreSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA.
Aileen LuSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA.
Pieter C DorresteinSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA.
Shirley M TsunodaSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA.ORCID 0000-0002-3974-8038
University of California San Diego · USAmherst College · USNational Institutes of Health · USUniversity of Antwerp · BE

Funding

Mass Spectrometry-based Untargeted MetabolomicsZICES103363 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI JARMUSCH, ALAN · 2021 to 2025
$6.5M
Intramural NIH HHS ZIC ES103363
6 · The paper itself

Abstract

Chemicals, including some systemically administered xenobiotics and their biotransformations, can be detected noninvasively using skin swabs and untargeted metabolomics analysis. We sought to understand the principal drivers that determine whether a drug taken orally or systemically is likely to be observed on the epidermis by using a random forest classifier to predict which drugs would be detected on the skin. A variety of molecular descriptors describing calculated properties of drugs, such as measures of volume, electronegativity, bond energy, and electrotopology, were used to train the classifier. The mean area under the receiver operating characteristic curve was 0.71 for predicting drug detection on the epidermis, and the SHapley Additive exPlanations (SHAP) model interpretation technique was used to determine the most relevant molecular descriptors. Based on the analysis of 2561 US Food and Drug Administration (FDA)-approved drugs, we predict that therapeutic drug classes, such as nervous system drugs, are more likely to be detected on the skin. Detecting drugs and other chemicals noninvasively on the skin using untargeted metabolomics could be a useful clinical advancement in therapeutic drug monitoring, adherence, and health status.

Indexed as

FoodSkinHealth StatusHumansMetabolomicsROC CurveUnited States

Identifiers

PMID34793633
PMCPMC8932847
OpenAlexW3211732322

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.