Evidence map›Paper›PMID 35456703›Full record

ArticlePharmaceutics2022

Assessment of the Extrusion Process and Printability of Suspension-Type Drug-Loaded Affinisol

Gloria Mora-Castaño, Mónica Millán-Jiménez, Vicente Linares, Isidoro Caraballo

Abstract read
In one paragraph

Article in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

4 authors.

Gloria Mora-CastañoDepartment of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Universidad de Sevilla, 41012 Seville, Spain.
Mónica Millán-JiménezDepartment of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Universidad de Sevilla, 41012 Seville, Spain.
Vicente LinaresDepartment of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Universidad de Sevilla, 41012 Seville, Spain.ORCID 0000-0002-3565-9839
Isidoro CaraballoDepartment of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Universidad de Sevilla, 41012 Seville, Spain.ORCID 0000-0003-1905-7755

Funding

Ministerio de Ciencia, Innovación y Universidades of Spain Project RTI2018-095041-B-C31Regional Government of Andalusia Consejería de Economía, Conocimiento, Empresas y Universidad (Project US-1380923).
6 · The paper itself

Abstract

Three-dimensional (3D) printing technology enables the design of new drug delivery systems for personalised medicine. Polymers that can be molten are needed to obtain extruded filaments for Fused Deposition Modelling (FDM), one of the most frequently employed techniques for 3D printing. The aim of this work was to evaluate the extrusion process and the physical appearance of filaments made of a hydrophilic polymer and a non-molten model drug. Metformin was used as model drug and Affinisol™ 15LV as the main carrier. Drug-loaded filaments were obtained by using a single-screw extruder and, subsequently, their printability was tested. Blends containing up to a 60% and 50% drug load with 5% and 7.5% of auxiliary excipients, respectively, were successfully extruded. Between the obtained filaments, those containing up to 50% of the drug were suitable for use in FDM 3D printing. The studied parameters, including residence time, flow speed, brittleness, and fractal dimension, reflect a critical point in the extrusion process at between 30-40% drug load. This finding could be essential for understanding the behaviour of filaments containing a non-molten component.

Indexed as

3D printingadditive manufacturingcritical pointsdrug-loaded filamentsextrusion processfractal dimensionfused-deposition modellingprintability

Identifiers

PMID35456703
PMCPMC9027497

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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.