Design and Synthesis of Self-Assembled Polymeric Nanoparticles for Cancer Drug Delivery
Bibliographic record
Abstract
Current chemotherapeutics are plagued by poor solubility and selectivity, requiring toxic excipients in formulations and causing a number of dose limiting side effects. Nanoparticle delivery has emerged as a strategy to more effectively deliver chemotherapeutics to the tumour site. Specifically, polymeric micelles enable the solubilization of hydrophobic small molecule drugs within the core and mitigate the necessity of excipients. Notwithstanding the significant progress made in polymeric micelle delivery, translation is limited by poor stability and low drug loading. In this work, a rational design approach is used to chemically modify poly(D,L-lactide-co-2-methyl-2-carboxytrimethylene carbonate)-graft-poly(ethylene glycol) (P(LA-co-TMCC)-g-PEG) in order to overcome these limitations and effectively deliver drug to tumours. The PEG density of the polymer system was optimized to enhance the stability of our polymeric micelles. Higher PEG densities permitted the lyophilization of micelles and enhanced the serum stability of the system. To increase the drug loading of our system, we facilitated specific intermolecular interactions within the micelle core. For drugs that form colloidal aggregates, such as pentyl-PABC doxazolidine, polymers were used to stabilize the colloidal core against aggregation and protein adsorption. For more challenging molecules, where self-assembly cannot be controlled, such as docetaxel, we modified the polymeric backbone with a peptide from the binding site of the drug to achieve loadings five times higher than those achieved in conventional micelle systems. This novel docetaxel nanoparticle was assessed in vivo in an orthotopic mouse model of breast cancer, where it showed a wider therapeutic index than the conventional ethanolic polysorbate 80 formulation. The improved tolerability of this formulation enabled higher dosing regimens and led to heightened efficacy and survival in this mouse model. Combined, these studies validated P(LA-co-TMCC)-g-PEG nanoparticles as an effective delivery vehicle for two chemotherapeutics, and presents approaches amenable to the delivery of many other clinically relevant hydrophobic drugs or drug combinations.
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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) | 0.001 | 0.001 |
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".