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Record W2953165972 · doi:10.1021/bk-2006-0934.ch003

Hydroxypropylcellulose in Oral Drug Delivery

2006· book-chapter· en· W2953165972 on OpenAlexaff
Mira F. Francis, Mariella Piredda, Françoise M. Winnik

Bibliographic record

VenueACS symposium series · 2006
Typebook-chapter
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDrug deliveryDrugAmphiphilePolymerDrug carrierNanotechnologyMaterials scienceCopolymerDosage formChemistryPharmacologyOrganic chemistryChromatographyMedicine

Abstract

fetched live from OpenAlex

Peroral drug administraion is by far the most common and most convenient route of drug delivery. The need of polymeric carriers permitting controlled release of a desired drug following oral administration has led to the screening of a large variety of synthetic and natural polymers. In oral solid dosage forms, hydroxypropylcellulose (HPC) is widely used as binder due to its excellent physico-chemical characteristics combined with mucoadhesive properties. Graft copolymers of HPC, decorated at random with short amphiphilic chains, form nanoparticles in water, consisting of a hydrophobic core surrounded by a hydrophilic, mucoadhesive shell. Such HPC-based assemblies can act as carrier of highly lipophilic drugs. The molecular design and characterization of HPC-based drug delivery systems are discussed, together with their ability to entrap cyclosporin A (CsA), and to carry it through model intestinal membrane.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.014

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 head0.006
GPT teacher head0.207
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2006
Admission routes1
Has abstractyes

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