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Record W2172264060 · doi:10.3390/pharmaceutics5010081

Pharmacokinetic Evaluation of a DSPE-PEG2000 Micellar Formulation of Ridaforolimus in Rat

2012· article· en· W2172264060 on OpenAlexaff
Connie M. Remsberg, Yunqi Zhao, Jody K. Takemoto, R. Bertram, Neal M. Davies, M. Laird Forrest

Bibliographic record

VenuePharmaceutics · 2012
Typearticle
Languageen
FieldMedicine
TopicMetal complexes synthesis and properties
Canadian institutionsUniversity of Manitoba
FundersAmerican Foundation for Pharmaceutical EducationAmerican Cancer Society
KeywordsMicelleBioavailabilitySolubilityPharmacokineticsAqueous solutionMaterials scienceChemistrySolventDrug deliveryPharmacologyChromatographyMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

The rapamycin analog, ridaforolimus, has demonstrated potent anti-proliferative effects in cancer treatment, and it currently is being evaluated in a range of clinical cancer studies. Ridaforolimus is an extremely lipophilic compound with limited aqueous solubility, which may benefit from formulation with polymeric micelles. Herein, we report the encapsulation of ridaforolimus in 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-methoxy-poly(ethylene glycol 2000) (DSPE-PEG2000) via a solvent extraction technique. Micelle loading greatly improved the solubility of ridaforolimus by approximately 40 times from 200 μg/mL to 8.9 mg/mL. The diameters of the drug-loaded micelles were 33 ± 15 nm indicating they are of appropriate size to accumulate within the tumor site via the enhanced permeability and retention (EPR) effect. The DSPE-PEG2000 micelle formulation was dosed intravenously to rats at 10 mg/kg and compared to a control of ridaforolimus in ethanol/PEG 400. The micelle significantly increased the half-life of ridaforolimus by 170% and decreased the clearance by 58%, which is consistent with improved retention of the drug in the plasma by the micelle formulation.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.055
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.224
GPT teacher head0.417
Teacher spread0.193 · 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

Citations17
Published2012
Admission routes1
Has abstractyes

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