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Record W4282914943 · doi:10.1080/09205063.2022.2088531

Phenylboronic acid modified hydrogel materials and their potential for use in contact lens based drug delivery

2022· article· en· W4282914943 on OpenAlexaff
Lina Liu, Talena Rambarran, Heather Sheardown

Bibliographic record

VenueJournal of Biomaterials Science Polymer Edition · 2022
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSelf-healing hydrogelsPhenylboronic acidContact lensDrug deliveryWettingPolymerizationMaterials scienceControlled releaseContact angleChemistryChemical engineeringAqueous solutionRadical polymerizationNanotechnologyPolymer chemistryPolymerOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The use of hydrogel-based contact lens materials holds promise for ophthalmic drug delivery by increasing drug residence time, improving drug bioavailability, reducing administration frequency, and enhancing special site targeting. Issues such as ease of manufacturing, lens comfort and appropriate release kinetics must be considered. Furthermore, the high water content of hydrogel materials can result in rapid and poorly controlled release kinetics. Herein, we modified common hydrogels used in contact lens manufacturing with phenylboronic acid (PBA). PBA addresses these material design issues since boronate esters are easily formed when boron acid and diols interact, opening up a pathway for simple modification of the model lens materials with saccharide based wetting agents. The wetting agents have the potential to improve lens comfort. Furthermore, the hydrophobicity of PBA and the presence of diols can be useful to help control drug release kinetics. In this work, polymerizable 3-(acrylamido)phenylboronic acid (APBA) was synthesized and incorporated into various hydrogels used in contact lens applications, including poly(2-hydroxyethylmethacrylate) (PHEMA), polyvinylpyrrolidone (PVP) and poly(N,N-dimethyl acrylamide) (PDMA) using UV induced free radical polymerization. The APBA structure and its incorporation into the hydrogel materials were confirmed by NMR and FTIR. The materials were shown to interact with and bind wetting agents such as hyaluronan (HA) and hydroxypropyl guar (HPG) by simple soaking in an aqueous solution. The equilibrium water content of the modified materials was characterized, demonstrating that most materials are still in the appropriate range after the introduction of the hydrophobic PBA. The release of three model ophthalmic drugs with varying hydrophilicity, atropine, atropine sulfate and dexamethasone, was examined. The presence of PBA in the materials was found to promote sustained drug release due to its hydrophobic nature. The results suggest that the modification of the materials with PBA was able to not only provide a mucoadhesive property that enhanced wetting agent interactions with the materials, but had the potential to alter drug release. Thus, the modification of contact lens materials with mucoadhesive functionality may be useful in the design of hydrogel contact lenses for ophthalmic drug release and wetting agent binding.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.017
GPT teacher head0.245
Teacher spread0.228 · 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 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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

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