Development, characterization, and in vitro evaluation of poly(ethylene oxide)-block-poly(ε-caprolactone)-α-tocopheryl succinate micelles as a novel nanocarrier for rapamycin delivery
Bibliographic record
Abstract
Rapamycin holds significant therapeutic potential for various diseases; however, its clinical application is limited by several formulation challenges, primarily its extremely low aqueous solubility (2.6 μg/mL). To address this, nanoparticle-based delivery systems have emerged as a promising strategy to enhance solubility and enable sustained drug release. Currently, Fyarro® (Aadi Bioscience, Inc.), an albumin-bound nanoparticle formulation, is the only FDA-approved injectable rapamycin product. In this study, we aimed to develop and evaluate novel poly(ethylene oxide)- block -poly(ε-caprolactone)-α-tocopheryl succinate (PEO- b -PCL-α-TS) micelles and assess their potential as a delivery system for rapamycin. PEO- b -PCL copolymers with varying PCL/PEO ratios were prepared via ring-opening polymerization and modified by α-TS conjugation, as confirmed by 1 H NMR, GPC, XRD, DSC analyses. The optimum rapamycin-loaded micelles (PEO 2000 - b -PCL 4000 -α-TS) exhibited nano-sized particles (< 22 nm) with a narrow polydispersity index (<0.29), high drug encapsulation efficiency (≥92 %), and enhanced solubility (>1.3 mg/mL). Stability studies demonstrated that encapsulation protected rapamycin from degradation, maintaining over 90 % drug retention for three months at 4 °C, while in vitro release studies showed sustained release, with 50 % of rapamycin released from PEO 2000 - b -PCL 4000 -α-TS micelles over 72 h. In vitro cytotoxicity assays revealed anticancer activity against lung carcinoma epithelial cells (A549), and the human colon adenocarcinoma cell line (HCT116). Minimal toxicity (≥70 % viability) was observed in normal human fibroblast cells (HFF1). These results point to the potential of PEO- b -PCL-α-TS micelles as a promising nanocarrier system, offering improved rapamycin solubility, enhanced stability, sustained release, and effective anticancer activity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".