Pharmacokinetic and Toxicodynamic Characterization of a Novel Doxorubicin Derivative
Bibliographic record
Abstract
Doxorubicin (Dox) is an effective anti-cancer medication with poor oral bioavailability and systemic toxicities. DoxQ was developed by conjugating Dox to the lymphatically absorbed antioxidant quercetin to improve Dox’s bioavailability and tolerability. The purpose of this study was to characterize the pharmacokinetics and safety of Dox after intravenous (IV) and oral (PO) administration of DoxQ or Dox (10 mg/kg) and investigate the intestinal lymphatic delivery of Dox after PO DoxQ administration in male Sprague–Dawley rats. Drug concentrations in serum, urine, and lymph were quantified by HPLC with fluorescence detection. DoxQ intact IV showed a 5-fold increase in the area under the curve (AUC)—18.6 ± 1.98 compared to 3.97 ± 0.71 μg * h/mL after Dox—and a significant reduction in the volume of distribution (Vss): 0.138 ± 0.015 versus 6.35 ± 1.06 L/kg. The fraction excreted unchanged in urine (fe) of IV DoxQ and Dox was ~5% and ~11%, respectively. Cumulative amounts of Dox in the mesenteric lymph fluid after oral DoxQ were twice as high as Dox in a mesenteric lymph duct cannulation rat model. Oral DoxQ increased AUC of Dox by ~1.5-fold compared to after oral Dox. Concentrations of β-N-Acetylglucosaminidase (NAG) but not cardiac troponin (cTnI) were lower after IV DoxQ than Dox. DoxQ altered the pharmacokinetic disposition of Dox, improved its renal safety and oral bioavailability, and is in part transported through intestinal lymphatics.
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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) | 0.000 | 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) | 0.001 | 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 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".