Formulation of Drugs in Block Copolymer Micelles: Drug Loading and Release
Bibliographic record
Abstract
Block copolymer micelles have become accepted as a viable strategy for drug formulation and delivery. Block copolymer micelles may serve as solubilizers and/or true drug carriers depending on their drug retention properties in vivo. Indeed the formulation of hydrophobic drugs in these micelle systems has been shown to provide up to a 30,000 fold increase in the water solubility of some compounds. In addition, the administration of drugs in copolymer micelles has been shown to reduce their toxicity and improve their therapeutic efficacy. The present review is focused on the drug loading and release properties of block copolymer micelles. Specifically, the properties of the drug, properties of the micelle core and the presence of interactions between the drug and the core-forming block are discussed in terms of their influence on the drug loading and release properties of the micelles. The various methods employed to prepare drug-loaded micelles are reviewed and the in vitro release assays used to predict the in vivo release characteristics of the formulations are discussed. The balance between drug loading and micelle stability is highlighted as a critical factor in the optimization of micelle-based formulations. The in vivo performance of micelles as delivery systems is evaluated by comparing the pharmacokinetics of free drug and drug administered in micelle-based formulations. Overall, the composition-property and property-performance relationships outlined in this review may aid in guiding the rational design of block copolymer micelles for drug delivery. In addition, suggestions for future research in this area are provided as a means to assist in furthering block copolymer micelles as one of the leading advanced drug delivery technologies for the systemic administration of drugs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".