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Record W4392817294 · doi:10.3390/pharmaceutics16030398

The Processing Space of the Spray-Dried Mannitol-Leucine System for Pulmonary Drug Delivery

2024· article· en· W4392817294 on OpenAlexaff
Riley T. Schweizer, Mani Ordoubadi, Cody A. Prather, Reinhard Vehring, Kimberly B. Shepard

Bibliographic record

VenuePharmaceutics · 2024
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExcipientMannitolSpray dryingChemical engineeringLeucineParticle sizeParticle (ecology)Materials scienceLamellar structureChemistryChromatographyOrganic chemistryComposite materialAmino acidBiochemistry

Abstract

fetched live from OpenAlex

Designing spray-dried particles for inhalation aims at specific physicochemical properties including a respirable aerodynamic diameter and adequate powder dispersibility. Leucine, an amphiphilic amino acid, has been shown to aid in optimizing bulk powder properties. Mannitol, a model crystalline active and common bulking agent, was co-sprayed with leucine at several excipient ratios, ethanol/water ratios, and spray dryer outlet temperatures in order to experimentally probe the underlying particle formation mechanisms in this binary crystalline system. During the droplet drying of two crystallizing components, the material that nucleates first will preferentially enrich the surface. It is desired to have a completely crystalline leucine shell to improve powder properties, however, mannitol competes with leucine for the surface depending on excipient concentration and manufacturing parameters. The resulting particles were studied initially and at a two-month timepoint via solid state characterization, visual analysis, and particle size analysis in order to detect changes in bulk powder properties. It was determined that, similar to systems where only leucine can crystallize, initial leucine saturation in the formulation dictates powder characteristics.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.310

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.332
Teacher spread0.297 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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