Evidence map›Paper›PMID 24558010›Full record

ArticlePharmaceutical research2014

Long-acting atypical antipsychotics: characterization of the local tissue response.

Sara Montminy Paquette, Had Dawit, Magali B Hickey, Elaine Merisko-Liversidge, Orn Almarsson, Daniel R Deaver

Open access · hybridAbstract read
In one paragraph

Article in Pharmaceutical research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

16 citing papers in PubMed, 40 citations in OpenAlex.

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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

6 authors at 1 institution in 2 countries.

Sara Montminy PaquetteAlkermes, Inc., 852 Winter Street, Waltham, Massachusetts, 02451, USA, sara.paquette@alkermes.com.
Had Dawit
Magali B Hickey
Elaine Merisko-Liversidge
Orn Almarsson
Daniel R Deaver
Alkermes (Ireland) · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeLong-acting injectables (LAIs) are increasingly recognized as an effective therapeutic approach for treating chronic conditions. Many LAIs are formulated to create a poorly soluble depot from which the active agent is delivered over time. This long residing depot can cause localized chronic-active inflammation in the tissue, which has not been well defined in the literature. The purpose of this work is to establish an experimental baseline for describing these responses.

methodsNon-human primates and rodents were used to examine the response to LAI formulations of two clinically relevant atypical antipsychotics, aripiprazole monohydrate and olanzapine pamoate monohydrate.

resultsA foreign body response develops with elevations of key cytokines such as IL-1α, IL-1β, TNFα, and IL6 at the site of injection. However, the tissue response for the two atypical antipsychotics compounds diverge as evidenced by quantitative differences observed in cytokine levels at various time points after dosing.

conclusionsOur studies show that, while the drugs are in the same therapeutic class, the response to each of these compounds can be distinguished qualitatively and quantitatively, supporting the idea that the injection site reaction involves a multiplicity of factors including the properties of the compound and cellular dynamics at the site of injection.

Indexed as

AnimalsAntipsychotic AgentsAripiprazoleDose-Response Relationship, DrugInflammation MediatorsInjections, SubcutaneousMacaca fascicularisMalePiperazinesQuinolonesRatsRats, Sprague-DawleyTissue DistributionAntipsychotic AgentsAripiprazoleInflammation MediatorsPiperazinesQuinolones

Identifiers

PMID24558010
PMCPMC4153971
OpenAlexW2134149108

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.