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Record W2118330712 · doi:10.18433/j3x884

Drug Delivery Properties of Macroporous Polystyrene Solid Foams

2012· article· en· W2118330712 on OpenAlexvenueno aff
Cristina Canal, Rosa-M.a Aparicio-Pelegrin, Alejandro Vílchez, Jordi Esquena, María José Núñez García

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2012
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsnot available
FundersGeneralitat de Catalunya
KeywordsPorosityMaterials scienceChemical engineeringDrug deliveryPolystyrenePhase inversionKetoprofenPolymerizationActive ingredientNanotechnologyChromatographyComposite materialChemistryPolymerMembrane

Abstract

fetched live from OpenAlex

PURPOSE: Polymeric porous foams have been evaluated as possible new pharmaceutical dosage forms. METHODS: These materials were obtained by polymerization in the continuous phase of highly concentrated emulsions prepared by the phase inversion temperature method. Their porosity, specific surface and surface topography were characterized, and the incorporation and release of active principles was studied using ketoprofen as model lipophilic molecule. RESULTS: Solid foams with very high pore volume, mainly inside macropores, were obtained by this method. The pore morphology of the materials was characterized, and very rough topography was observed, which contributed to their nearly superhydrophobic properties. These solid foams could be used as delivery systems for active principles with pharmaceutical interest, and in the present work ketoprofen was used as a model lipophilic molecule. CONCLUSIONS: Drug incorporation and release was studied from solid foam disks, using different concentrations of the loading solutions, achieving a delayed release with short lag-time.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.378
Teacher spread0.286 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations16
Published2012
Admission routes1
Has abstractyes

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