Development of a RP-HPLC method for analysis of docetaxel in tumor-bearing mice plasma and tissues following injection of docetaxel-loaded pH responsive targeting polymeric micelles
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: A simple, rapid, and sensitive reversed-phase high performance liquid chromatography (RP-HPLC) method based on liquid-liquid extraction was developed and validated for determination of docetaxel (DTX) in plasma and homogenate tissues of tumor-bearing mice. EXPERIMENTAL APPROACH: Samples were spiked with celecoxib as the internal standard and separation was achieved on a μ-Bondapak C18 HPLC column. The mobile phase consisted of a mixture of acetonitrile/water (40/60 v/v) at flow rate of 1.2 mL/min and the effluent was monitored at 230 nm. RESULTS: Calibration curves were linear over the concentration range of 0.1-10 μg/mL of DTX in plasma and 0.25-50 μg/mL in tissue homogenates with acceptable precision and accuracy. The mean recoveries of the drug from plasma extraction was 94.6 ± 1.44% while those of tissue homogenates ranged from 73.5 ± 3.2 to 85.3 ± 2.8% depending on the type of tissues examined. DTX was stable in biological samples with no evidence of degradation during 3 freeze-thaw cycles and two months of storage at -70 ± 15 °C. The developed HPLC method was applied to quantify DTX in the mouse plasma and tissues after intravenous administration of 7.5 mg equivalent DTX/kg dose of DTX-loaded folic acid-polyethylene glycol-heparin-tocopherol (FA-PEG-HEP-CA-TOC) micelle formulation to female Balb/c mice. CONCLUSION: A simple, sensitive, rapid, accurate, and prudent RP-HPLC method was developed, validated, and applied for DTX determination in plasma and tissues.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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".