Population pharmacokinetics of mavacoxib in osteoarthritic dogs
Bibliographic record
Abstract
Mavacoxib (Trocoxil™) is an oral long-acting COX-2 inhibitor approved for the treatment of osteoarthritis in dogs. Two field trials were conducted in client-owned dogs suffering from osteoarthritis, with dosages of 4 mg/kg body weight (BW) (Study 1) or 2 mg/kg BW (Study 2). Mavacoxib plasma concentrations were determined from trough blood samples and from blood samples collected at 4-10 months after the last dose. A one-compartment linear model was fitted to the concentration data (1317 concentration records from 286 patients), and parameters for oral clearance (Cl/F), apparent volume of distribution (V(d) /F) and their between-subject variabilities (BSV) were estimated. Covariates were included in the model based on the outcomes of stepwise regression procedures. In the final model, the typical value of Cl/F was a function of BW, age and breed. German shepherds and Labrador retrievers were found to have 31% higher values of Cl/F than patients from different breeds with similar ages and BWs. The typical value of V(d) /F was found to be dependent only on BW. The two field studies appeared to differ similarly with respect to Cl/F and V(d) /F. The explanation for this difference is not known, but the difference was accounted for in the final model as a 23.9% lower bioavailability in Study 2. Mavacoxib exhibited relatively broad BSV in Cl/F and V(d) /F, with coefficients of variation of 47% and 19%, respectively. The typical value for mavacoxib's terminal elimination plasma half-life (t(1/2) ) was 44 days, but a minority of patients (approximately 5%) had empirical Bayes estimates of t(1/2) exceeding 80 days. Simulations with the model indicated that the majority of patients treated with mavacoxib 2 mg/kg will maintain trough plasma mavacoxib concentrations associated with efficacy. Results of the population pharmacokinetic analysis helped to reduce the dose from 4 to 2 mg/kg and thus increased the therapeutic index for this molecule.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".