In Vitro and In Vivo Evaluation of PEGylated Layer‐by‐Layer Polyelectrolyte‐Coated Paclitaxel Nanocrystals
Bibliographic record
Abstract
Drug nanocrystals (NCs) are colloidal dispersions composed almost entirely of drug. As such, there is substantial interest in targeting them to diseased tissues, where they can locally deliver high doses of the therapeutic. However, because of their uncontrolled dissolution characteristics in vivo and uptake by the monomolecular phagocyte system, achieving tumor accumulation is challenging. To address these issues, a layer-by-layer approach is adopted to coat paclitaxel NCs with alternating layers of oppositely charged polyelectrolytes, using a PEGylated copolymer as the top layer. The coating successfully slows down dissolution in comparison to the noncoated NCs and to Abraxane (an approved paclitaxel nanoformulation), provides colloidal stability in physiologically relevant media, and has no intrinsic effect on cell viability at the concentrations tested. Nevertheless, their pharmacokinetic and biodistribution profile indicates that the NCs are rapidly cleared from the bloodstream followed by accumulation in the mononuclear phagocyte system organs (i.e., liver and spleen). This is hypothesized to be a consequence of the shedding of the PEGylated polyelectrolyte from the NCs' surface. While therapeutic efficacy was not investigated (due to poor tumor accumulation), overall, this work questions whether approaches that rely solely on electrostatic interactions for retaining coatings on the surfaces of NCs are appropriate for use in vivo.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 teacher head, 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".