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Using Flash Nanoprecipitation To Produce Highly Potent and Stable Cellax Nanoparticles from Amphiphilic Polymers Derived from Carboxymethyl Cellulose, Polyethylene Glycol, and Cabazitaxel

2017· article· en· W2759724202 on OpenAlexafffund
Joseph Bteich, Simon A. McManus, Mark J. Ernsting, Mohammed Z. Mohammed, Robert K. Prud’homme, Kenneth K. Sokoll

Bibliographic record

VenueMolecular Pharmaceutics · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsToronto Metropolitan UniversityOntario Institute for Cancer Research
FundersOntario Institute for Cancer Research
KeywordsNanoparticleAmphiphilePolyethylene glycolCarboxymethyl cellulosePolymerNanomedicineChemistryPEG ratioDrug carrierMethacrylateCabazitaxelCopolymerSolventDrug deliveryMaterials scienceNanotechnologyOrganic chemistrySodiumCancer

Abstract

fetched live from OpenAlex

We report the use of flash nanoprecipitation (FNP) as an efficient and scalable means of producing Cellax nanoparticles. Cellax polymeric conjugates consisting of carboxymethyl cellulose functionalized with PEG and hydrophobic anticancer drugs, such as cabazitaxel (coined Cellax-CBZ), have been shown to have high potency against several oncology targets, including prostate cancer. FNP, a robust method used to create nanoparticles through rapid mixing, has been used to encapsulate several hydrophobic drugs with block copolymer stabilizers, but has never been used to form nanoparticles from random copolymers, such as Cellax-CBZ. To assess the potential of using FNP to produce Cellax nanoparticles, parameters such as concentration, mixing rate, solvent ratios, and subsequent dilution were tested with a target nanoparticle size range of 60 nm. Under optimized solvent conditions, particles were formed that underwent a subsequent rearrangement to form nanoparticles of 60 nm diameter, independent of Cellax-CBZ polymer concentration. This intraparticle relaxation, without interparticle association, points to a delicate balance of hydrophobic/hydrophilic domains on the polymer backbone. These particles were stable over time, and the random amphiphilicity did not lead to interparticle attractions, which would compromise the stability and corresponding narrow size distribution required for parenteral injection. The amphiphilic nature of these conjugates allows them to be processed into nanoparticles for sustained drug release and improved tumor selectivity. Preferred candidates were evaluated for plasma stability and cytotoxicity against the PC3 prostate cancer cell line in vitro. These parameters are important when assessing nanoparticle safety and for estimating potential efficacy, respectively. The optimal formulations showed plasma stability profiles consistent with long circulating nanoparticles, and cytotoxicity comparable to that of free CBZ. This study demonstrates that FNP is a promising technology for development of Cellax nanoparticles.

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 score0.003

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 head0.038
GPT teacher head0.296
Teacher spread0.258 · 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

Citations37
Published2017
Admission routes2
Has abstractyes

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