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Record W3217385275 · doi:10.3390/ph14111201

Cellulosic Polymers for Enhancing Drug Bioavailability in Ocular Drug Delivery Systems

2021· review· en· W3217385275 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePharmaceuticals · 2021
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsLaurentian University
Fundersnot available
KeywordsBioavailabilityDrug deliveryDrugPharmacologyCellulosic ethanolMedicineChemistryCellulose

Abstract

fetched live from OpenAlex

One of the major impediments to drug development is low aqueous solubility and thus poor bioavailability, which leads to insufficient clinical utility. Around 70-80% of drugs in the discovery pipeline are suffering from poor aqueous solubility and poor bioavailability, which is a major challenge when one has to develop an ocular drug delivery system. The outer lipid layer, pre-corneal, dynamic, and static ocular barriers limit drug availability to the targeted ocular tissues. Biopharmaceutical Classification System (BCS) class II drugs with adequate permeability and limited or no aqueous solubility have been extensively studied for various polymer-based solubility enhancement approaches. The hydrophilic nature of cellulosic polymers and their tunable properties make them the polymers of choice in various solubility-enhancement techniques. This review focuses on various cellulose derivatives, specifically, their role, current status and novel modified cellulosic polymers for enhancing the bioavailability of BCS class II drugs in ocular drug delivery systems.

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.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.212
GPT teacher head0.497
Teacher spread0.285 · 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