MétaCan
Menu
Back to cohort
Record W4285095018 · doi:10.3390/polym14142822

Chitosan and Sodium Alginate Implementation as Pharmaceutical Excipients in Multiple-Unit Particulate Systems

2022· article· en· W4285095018 on OpenAlexfundno aff
Martina Čierna, Pavel Mučaji, Miroslava Špaglová, Mária Čuchorová, Oliver Macho

Bibliographic record

VenuePolymers · 2022
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug Solubulity and Delivery Systems
Canadian institutionsnot available
FundersFaculté de pharmacie, Université de MontréalMinisterstvo školstva, vedy, výskumu a športu Slovenskej republiky
KeywordsPelletsPelletDissolutionChitosanExtrusionSphericityMaterials scienceDosage formChemical engineeringGelatinScanning electron microscopeDissolution testingChromatographyPolymerChemistryComposite materialEthyl celluloseOrganic chemistry

Abstract

fetched live from OpenAlex

This study aimed to prepare and evaluate pellets containing acyclovir as a model drug. Pellets were prepared by the extrusion-spheronization process. Aqueous solutions of natural marine polymers (sodium alginate, chitosan) were compared to semi-synthetic hydroxypropyl methylcellulose (HPMC) in the role of binders. The study focused on the characterization of the pellet properties that are crucial for the formulation of the final dosage form, such as in multi-unit pellet system (MUPS) tablets or hard gelatin capsules filled with the pellets. Finally, the mentioned dosage forms were tested for drug dissolution. The morphology of pellets observed by scanning electron microscopy correlated with the shape evaluation performed by dynamic image analysis. Sodium alginate pellets exhibited the lowest value of sphericity (0.93), and many elongated rods and dumbbells were observed in this batch. Chitosan pellets had the highest value of sphericity (0.97) and were also less rough on the surface. The pellets maintained a constant surface geometry during the dissolution studies; they only reduced in size. The most significant reduction in size and weight was assessed after 2 h of dissolution testing. This fact was in line with the drug release from pellets in capsules or MUPS tablets, which was massive during the first hour, in both cases. The dissolution profiles of all of the batches were comparable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.127
GPT teacher head0.444
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePolymersSame topicDrug Solubulity and Delivery SystemsFrench-language works237,207