Evidence map›Paper›PMID 37745076›Full record

ArticleFrontiers in pharmacology2023

Integrating distribution kinetics and toxicodynamics to assess repeat dose neurotoxicity

Carolina Nunes, Susana Proença, Giovanna Ambrosini, David Pamies, Aurélien Thomas, Nynke I Kramer, Marie-Gabrielle Zurich

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Extrapolation steps in quantitativeCurrent research in toxicology · 2026
    Review
  3. Review
  4. 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

7 authors.

Carolina NunesDepartment of Biomedical Sciences, University of Lausanne, Lausanne, Switzerland.
Susana ProençaInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands.
Giovanna AmbrosiniBioinformatics Competence Center, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
David PamiesDepartment of Biomedical Sciences, University of Lausanne, Lausanne, Switzerland.
Aurélien ThomasUnit of Forensic Toxicology and Chemistry, CURML, Lausanne and Geneva University Hospitals, Geneva, Switzerland.
Nynke I KramerInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands.
Marie-Gabrielle ZurichDepartment of Biomedical Sciences, University of Lausanne, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For ethical, economical, and scientific reasons, animal experimentation, used to evaluate the potential neurotoxicity of chemicals before their release in the market, needs to be replaced by new approach methodologies. To illustrate the use of new approach methodologies, the human induced pluripotent stem cell-derived 3D model BrainSpheres was acutely (48 h) or repeatedly (7 days) exposed to amiodarone (0.625-15 µM), a lipophilic antiarrhythmic drug reported to have deleterious effects on the nervous system. Neurotoxicity was assessed using transcriptomics, the immunohistochemistry of cell type-specific markers, and real-time reverse transcription-polymerase chain reaction for various genes involved in the lipid metabolism. By integrating distribution kinetics modeling with neurotoxicity readouts, we show that the observed time- and concentration-dependent increase in the neurotoxic effects of amiodarone is driven by the cellular accumulation of amiodarone after repeated dosing. The development of a compartmental

Indexed as

hiPSCin silico modelingin vitro distribution kineticslipid metabolismmicrophysiological systemneurotoxicityspheroid

Identifiers

PMID37745076
PMCPMC10512064

What OpenQuestion holds

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Registered trials

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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.