Non-PEGylated liposomes for convection-enhanced delivery of topotecan and gadodiamide in malignant glioma: initial experience
Bibliographic record
Abstract
Convection-enhanced delivery (CED) of highly stable PEGylated liposomes encapsulating chemotherapeutic drugs has previously been effective against malignant glioma xenografts. We have developed a novel, convectable non-PEGylated liposomal formulation that can be used to encapsulate both the topoisomerase I inhibitor topotecan (topoCED) and paramagnetic gadodiamide (gadoCED), providing an ideal basis for real-time monitoring of drug distribution. Tissue retention of topoCED following single CED administration was significantly improved relative to free topotecan. At a dose of 10 microg (0.5 mg/ml), topoCED had a half-life in brain of approximately 1 day and increased the area under the concentration-time curve (AUC) by 28-fold over free topotecan (153.8 vs. 5.5 microg day/g). The combination of topoCED and gadoCED was found to co-convect well in both naïve rat brain and malignant glioma xenografts (correlation coefficients 0.97-0.99). In a U87MG cell assay, the 50% inhibitory concentration (IC(50)) of topoCED was approximately 0.8 microM at 48 and 72 h; its concentration-time curves were similar to free topotecan and unaffected by gadoCED. In a U87MG intracranial rat xenograft model, a two-dose CED regimen of topoCED co-infused with gadoCED greatly increased median overall survival at dose levels of 0.5 mg/ml (29.5 days) and 1.0 mg/ml (33.0 days) vs. control (20.0 days; P < 0.0001 for both comparisons). TopoCED at higher concentrations (1.6 mg/ml) co-infused with gadoCED showed no evidence of histopathological changes attributable to either agent. The positive results of tissue pharmacokinetics, co-convection, cytotoxicity, efficacy, and lack of toxicity of topoCED in a clinically meaningful dose range, combined with an ideal matched-liposome paramagnetic agent, gadoCED, implicates further clinical applications of this therapy in the treatment of malignant glioma.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".