Evidence map›Paper›PMID 33157376›Full record

ArticleEnvironment international2021

Pharmacology-informed prediction of the risk posed to fish by mixtures of non-steroidal anti-inflammatory drugs (NSAIDs) in the environment.

Philip Marmon, Stewart F Owen, Luigi Margiotta-Casaluci

Open access · goldAbstract read
In one paragraph

Article in Environment international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

15 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
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  8. Review
  9. Frontiers in systems biology · 2024
    Article
  10. Article
  11. Acute Traumatic Pain in the Emergency Department.Diseases (Basel, Switzerland) · 2023
    Review
  12. Article
  13. Article
  14. Article
  15. 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

3 authors at 2 institutions in 1 country.

Philip MarmonDepartment of Life Sciences, College of Health, Medicine, and Life Sciences, Brunel University London, London, UB8 3PH, UK.
Stewart F OwenAstraZeneca, Global Environment, Alderley Park, Macclesfield, Cheshire SK10 4TF, UK.
Luigi Margiotta-CasaluciDepartment of Life Sciences, College of Health, Medicine, and Life Sciences, Brunel University London, London, UB8 3PH, UK. Electronic address: Luigi.Margiotta-Casaluci@brunel.ac.uk.
Brunel University of London · GBAstraZeneca (United Kingdom) · GB

Funding

Biotechnology and Biological Sciences Research Council BB/P505018/1
6 · The paper itself

Abstract

The presence of non-steroidal anti-inflammatory drugs (NSAIDs) in the aquatic environment has raised concern that chronic exposure to these compounds may cause adverse effects in wild fish populations. This potential scenario has led some stakeholders to advocate a stricter regulation of NSAIDs, especially diclofenac. Considering their global clinical importance for the management of pain and inflammation, any regulation that may affect patient access to NSAIDs will have considerable implications for public health. The current environmental risk assessment of NSAIDs is driven by the results of a limited number of standard toxicity tests and does not take into account mechanistic and pharmacological considerations. Here we present a pharmacology-informed framework that enables the prediction of the risk posed to fish by 25 different NSAIDs and their dynamic mixtures. Using network pharmacology approaches, we demonstrated that these 25 NSAIDs display a significant mechanistic promiscuity that could enhance the risk of target-mediated mixture effects near environmentally relevant concentrations. Integrating NSAIDs pharmacokinetic and pharmacodynamic features, we provide highly specific predictions of the adverse phenotypes associated with exposure to NSAIDs, and we developed a visual multi-scale model to guide the interpretation of the toxicological relevance of any given set of NSAIDs exposure data. Our analysis demonstrated a non-negligible risk posed to fish by NSAID mixtures in situations of high drug use and low dilution of waste-water treatment plant effluents. We anticipate that this predictive framework will support the future regulatory environmental risk assessment of NSAIDs and increase the effectiveness of ecopharmacovigilance strategies. Moreover, it can facilitate the prediction of the toxicological risk posed by mixtures via the implementation of mechanistic considerations and could be readily extended to other classes of chemicals.

Indexed as

Anti-Inflammatory Agents, Non-SteroidalPharmaceutical PreparationsAnimalsDiclofenacHumansInflammationAnti-Inflammatory Agents, Non-SteroidalDiclofenacPharmaceutical PreparationsDiclofenacEnvironmental risk assessmentFishNSAIDPharmaceuticals in the environmentPredictive toxicology

Identifiers

PMID33157376
PMCPMC7786791
OpenAlexW3097157407

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.