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Record W2594259964 · doi:10.1016/j.jconrel.2017.03.010

A simple passive equilibration method for loading carboplatin into pre-formed liposomes incubated with ethanol as a temperature dependent permeability enhancer

2017· article· en· W2594259964 on OpenAlexafffund
Mohamed Wehbe, Armaan Malhotra, Malathi Anantha, Jeroen Roosendaal, Ada W.Y. Leung, David Plackett, Katarina Edwards, Roger Gilabert‐Oriol, Marcel B. Bally

Bibliographic record

VenueJournal of Controlled Release · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of British ColumbiaCentre for Drug Research and DevelopmentBC Cancer Agency
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchUniversity of British ColumbiaBC Cancer AgencyDeutsche Forschungsgemeinschaft
KeywordsLiposomeCarboplatinEthanolEnhancerPermeability (electromagnetism)ChemistryChromatographyMembraneMedicineBiochemistrySurgery

Abstract

fetched live from OpenAlex

A passive equilibration method which relies on addition of candidate drugs to pre-formed liposomes is described as an alternative method for preparing liposome encapsulated drugs. The method is simple, rapid and applicable to liposomes prepared with high (45 mol%) or low (< 20 mol%) levels of cholesterol. Passive equilibration is performed in 4-steps: (i) formation of liposomes, (ii) addition of the candidate drug to the liposomes in combination with a permeability enhancing agent, (iii) incubation at a temperature that facilitates diffusion of the added compound across the lipid bilayer, and (iv) quenching the enhanced membrane permeability by reduction in temperature and/or removal of the permeabilization enhancer. The method is fully exemplified here using ethanol as the permeabilization enhancer and carboplatin (CBDCA) as the drug candidate. It is demonstrated that ethanol can be added to liposomes prepared with 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) and Cholesterol (Chol) (55:45 mol ratio) in amounts up to 30% (v/v) with no change in liposome size, even when incubated at temperatures > 60 °C. Super-saturated solutions of CBDCA (40 mg/mL) can be prepared at 70 °C and these are stable in the presence of ethanol even when the temperature is reduced to < 30 °C. maximum CBDCA encapsulation is achieved within 1 h after the CBDCA solution is added to pre-formed DSPC/Chol liposomes in the presence of 30% (v/v) ethanol at 60 °C. When the pre-formed liposomes are mixed with ethanol (30% v/v) at or below 40 °C, the encapsulation efficiency is reduced by an order of magnitude. The method was also applied to liposomes prepared from other compositions include a cholesterol free formulations (containing 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[carboxy(polyethylene glycol)-2000] (DSPE-PEG2000)) and a low Chol (< 20 mol%) formulations prepared with the distearoyl-sn-glycero-3-phospho-(1′-rac-glycerol) DSPG)). The cytotoxic activity of CBDCA was unaffected when prepared in this manner and two of the resultant formulations exhibited good stability in vitro and in vivo. The cytotoxic activity of CBDCA was unaffected when prepared in this manner and the resultant formulations exhibited good stability in vitro and in vivo. Pharmacokinetics studies in CD-1 mice indicated that the resulting formulations increased the circulation half life of the associated CBDCA significantly (AUC0–24 h of CBDCA = 0.016 μg·hr/mL; AUC0-24h of the DSPC/Chol CBDCA formulation = 1014.0 μg·hr/mL and AUC0-24h of the DSPC/DSPG/Chol CBDCA formulation = 583.96 μg·hr/mL). Preliminary efficacy studies in Rag-2M mice with established subcutaneous H1975 and U-251 tumors suggest that the therapeutic activity of CBDCA is improved when administered in liposomal formulations. The encapsulation method described here has not been disclosed previously and will have broad applications to drugs that would normally be encapsulated during liposome manufacturing.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.293
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations46
Published2017
Admission routes2
Has abstractyes

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