Evidence map›Paper›PMID 37242565›Full record

ArticlePharmaceutics2023

Veering to a Continuous Platform of Fused Deposition Modeling Based 3D Printing for Pharmaceutical Dosage Forms: Understanding the Effect of Layer Orientation on Formulation Performance.

Vineet R Kulkarni, Jaidev Chakka, Faez Alkadi, Mohammed Maniruzzaman

Abstract read
In one paragraph

Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Vineet R KulkarniPharmaceutical Engineering and 3D Printing (PharmE3D) Lab, Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin, Austin, TX 78705, USA.ORCID 0000-0003-3444-0525
Jaidev ChakkaPharmaceutical Engineering and 3D Printing (PharmE3D) Lab, Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin, Austin, TX 78705, USA.ORCID 0000-0003-0039-0064
Faez AlkadiPharmaceutical Engineering and 3D Printing (PharmE3D) Lab, Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin, Austin, TX 78705, USA.
Mohammed ManiruzzamanPharmaceutical Engineering and 3D Printing (PharmE3D) Lab, Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin, Austin, TX 78705, USA.ORCID 0000-0002-3373-5586

Funding

CoM3D Ltd. OSP #201901238CoM3D Ltd. OSP #202000967
6 · The paper itself

Abstract

Three-dimensional (3D) printing of pharmaceuticals has been centered around the idea of personalized patient-based 'on-demand' medication. Fused deposition modeling (FDM)-based 3D printing processes provide the capability to create complex geometrical dosage forms. However, the current FDM-based processes are associated with printing lag time and manual interventions. The current study tried to resolve this issue by utilizing the dynamic

Indexed as

3D printingadditive manufacturingamorphous solid dispersioncontinuous printingfused deposition modelinghot-melt extrusionlayer orientation

Identifiers

PMID37242565
PMCPMC10224244

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.