Evidence map›Paper›PMID 41477471›Full record

ArticleJournal of pharmaceutical innovation2026

Chewable Tablets for Precise Unit Dosing of Animals.

Reese E Landes, Pradeep Valekar, Muslim Abbas, Kieran A DeLoatch, James B Schreiber, Ira S Buckner, Rehana K Leak

Abstract read
In one paragraph

Article in Journal of pharmaceutical innovation, 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. 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.

Reese E LandesDuquesne University, Pittsburgh, PA USA.
Pradeep ValekarDuquesne University, Pittsburgh, PA USA.
Muslim AbbasDuquesne University, Pittsburgh, PA USA.
Kieran A DeLoatchDuquesne University, Pittsburgh, PA USA.
James B SchreiberDuquesne University, Pittsburgh, PA USA.
Ira S BucknerDuquesne University, Pittsburgh, PA USA.
Rehana K LeakDuquesne University, Pittsburgh, PA USA.

Funding

Myelination and Resilience Against Limbic Alpha-SynucleinopathyR15NS130532 · NINDS · DUQUESNE UNIVERSITY · PI LEAK, REHANA KHAN · 2022 to 2022
$447k
NINDS NIH HHS R15 NS130532
6 · The paper itself

Abstract

Introduction: Peroral administration of preclinical drugs is commonly achieved through oral gavage or food formulations. However, oral gavage induces distress and is unsuitable for behavior studies, whereas food mixing and delivery are less precise. Therefore, we manufactured and tested tablets with the appropriate physical properties for precise unit dosing of laboratory mice. Methods: Various tablet compositions were evaluated for compactability and compressibility and tested for voluntary consumption by CD-1 mice. The most bitter compound known, denatonium benzoate, was added to tablets at escalating doses, and daily consumption by male and female CD-1 mice was measured across four weeks. Results: Tablet consumption increased with the number of exposures in 5 of 6 mice, suggesting that a habituation period was necessary. A bitterant was then added at escalating doses (3 to 48 micrograms) for four weeks. After one week of habituation to placebo tablets, 9 of 11 mice ate all bitter tablets, consuming 97% of tablet masses within the first hour. No changes in bodyweight were noted. Conclusion: These findings support the utility of tablets as a method for drug delivery in laboratory and possibly other settings. Supplementary Information: The online version contains supplementary material available at 10.1007/s12247-025-10312-0.

Indexed as

OralOral gavagePeroralPest controlPreclinical researchTabletsVeterinary

Identifiers

PMID41477471
PMCPMC12748284

What OpenQuestion holds

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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.