Evidence map›Paper›PMID 41809645›Full record

ArticleFrontiers in toxicology2026

From prediction to adaptation: rethinking the epistemic role of inhalation toxicology.

Samir Dekali

Abstract read
In one paragraph

Article in Frontiers in toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Samir DekaliBiomedical Research Institute of the Armed Forces (IRBA), EBR Department, Emerging Technological Risks Unit (U.RTE), Brétigny-sur-Orge, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inhalation toxicology has long aimed to predict the health effects of airborne substances before exposure occurs, relying on stable dose-response relationships and well-characterized hazards. This approach becomes increasingly limited when confronted with emerging materials, complex mixtures, and dynamic exposure scenarios, where key mechanisms and variables are not fully known in advance. In this Perspective, we propose reframing inhalation toxicology from a predictive toward an adaptive science, in which experimental and computational systems are designed to rapidly generate and integrate information under conditions of uncertainty. We outline how flexible

Indexed as

adaptive toxicologycomputational modelingevidence integrationinhalation toxicologyin vitro modelsnew approach methodologiesuncertainty

Identifiers

PMID41809645
PMCPMC12968013

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.