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Record W2436107268 · doi:10.18433/j3w904

Bioavailability Improvement Strategies for Poorly Water-Soluble Drugs Based on the Supersaturation Mechanism: An Update

2016· review· en· W2436107268 on OpenAlexvenueno aff
Meiyan Yang, Wei Gong, Yuli Wang, Shan Li, Ying Li, Chunsheng Gao

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2016
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug Solubulity and Delivery Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSupersaturationBioavailabilityDrug deliveryDrugChemistrySolubilityNanotechnologyBiochemical engineeringMechanism (biology)PharmacologyMaterials scienceMedicineEngineeringPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The formulation development for poorly soluble drugs still remains a challenge. Supersaturating drug delivery systems (SDDS) or drug delivery systems based on supersaturating provide a promising way to improve the oral bioavailability of poorly water-soluble drugs. In supersaturable formulations, drug concentration exceeds the equilibrium solubility when exposed to gastrointestinal fluids, and the supersaturation state is maintained long enough to be absorbed, resulting in compromised bioavailability. In this article, the mechanism of generating and maintaining supersaturation and the evaluation methods of supersaturation assays are discussed. Recent advances in different drug delivery systems based on supersaturating are the focus and are discussed in detail.This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

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)0.014
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.248
GPT teacher head0.496
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations33
Published2016
Admission routes1
Has abstractyes

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