Docetaxel Distribution Following Intraperitoneal Administration in Mice
Bibliographic record
Abstract
PURPOSE: Intraperitoneal (IP) chemotherapy with high molecular weight lipophilic antineoplastic agents such as the taxanes has shown promise in clinical trial evaluation for treatment of localized peritoneal cancers. We have previously developed an IP injectable hydrogel formulation (PoLigel) for sustained peritoneal delivery of docetaxel (DTX), and observed significant efficacy in murine models of ovarian cancer when compared to Taxotere®, the FDA approved formulation of DTX. In order to understand the relationship between drug distribution and efficacy, the current study compares the tissue distribution and pharmacokinetics of DTX administered IP in the PoLigel or Taxotere® formulations. METHODS: The PoLigel was prepared by blending a water-soluble chitosan derivative, egg phosphatidylcholine and lauric aldehyde with DTX (drug to material ratio 1:8 w/w). DTX concentrations in plasma, heart, liver, spleen, stomach, intestine, kidney and peritoneal muscle were measured over a five day period following IP administration of the PoLigel and Taxotere® formulations in CD-1 female mice. RESULTS: Three days after Taxotere® administration, no detectable levels of DTX were seen in plasma, while sustained DTX plasma levels of 0.06 ug/ml ± 0.01 per day were observed with PoLigel. At five days post Taxotere® administration, only intestine, stomach and peritoneal muscle showed detectable DTX concentrations whereas all tissues and plasma showed sustained DTX levels in mice that received PoLigel. DTX concentrations that resulted from PoLigel administration were significantly higher in the peritoneal cavity and 200 fold higher than concentrations found in plasma. CONCLUSIONS: Overall, the PoLigel formulation increases tissue and plasma drug retention and provides sustained DTX levels compared to the clinically used Taxotere® formulation. The sustained DTX levels seen in the peritoneal cavity following IP administration of the PoLigel may be responsible for the improvement in efficacy that has been observed in our previous studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".