Pharmacokinetics and estimated bioavailability of grapiprant, a novel selective prostaglandin E<sub>2</sub> receptor antagonist, after oral administration in fasted and fed dogs
Bibliographic record
Abstract
AIMS: To assess the effect of food intake on the pharmacokinetics of grapiprant administered orally at 2 mg/kg, and to estimate its oral bioavailability in dogs. METHODS: Eight healthy female Labrador Retriever dogs, aged 4-10 years were used. In the initial trial two dogs were administered a 0.5 mg/kg I/V bolus of grapiprant dissolved in ethanol. In the second trial, six dogs were assigned to two treatment groups, using a randomised cross-over design, and received 2 mg/kg of grapiprant orally, as pure powder, after fasting for 12 hours or after being fed. Blood samples were collected at preassigned times up to 36 hours after administration, and concentrations of grapiprant in plasma determined using validated high performance liquid chromatography. RESULTS: After I/V administration in the two dogs the terminal half life was 5.30 and 6.06 hours, clearance was 444 and 476 mL/hours/kg, and volume of distribution was 3,642 and 3,883 mL/kg. Compared with fasted dogs, oral administration in fed dogs resulted in reduced median peak concentrations in plasma (1,598 vs. 614 ng/mL) and delayed median time of peak concentration (1.0 vs. 3.0 hours). The estimated bioavailability in fasted and fed dogs was 111.9 and 59.1%, respectively. Concentrations of grapiprant in plasma following oral administration, in either fed or fasted dogs, remained higher than 164 ng/mL for up to 6 hours. This concentration has been estimated to be the minimal effective concentration required to control pain in dogs. CONCLUSION AND RELEVANCE: Oral administration of 2 mg/kg grapiprant in fed and fasted dogs resulted in different pharmacokinetics of the drug, but did not influence the length of time when concentrations in plasma exceeded theoretical effective concentrations. Further studies are necessary to verify these findings using pharmacokinetic-pharmacodynamic studies and in clinical subjects.
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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 | 0.001 | 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 | 0.001 |
| 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".