Penetration and efficacy of transdermal NSAIDs in a model of acute joint inflammation
Bibliographic record
Abstract
Purpose: Prescription and OTC non-steroidal anti-inflammatory drugs (NSAIDs) are ubiquitous treatments for pain and inflammation; however, oral administration of these drugs may produce gastrointestinal (GI) side effects. Transdermal (TD) administration of NSAIDs circumvents these adverse events by avoiding the GI tract and, presumably, achieves regional drug levels of therapeutic effect and thereby, fewer off-target complications. Methods : A drug quantification method was developed for ibuprofen and celecoxib in canine plasma and synovial fluid using liquid chromatography and mass spectrometry. This method was employed to evaluate the penetrance of ibuprofen and celecoxib topical formulations in dogs. Effectiveness of these topical NSAID formulations was compared to the equivalent oral drug concentration in a canine sodium-urate model of acute joint inflammation. In this model, pain was quantified using a modified Canine Brief Pain Inventory questionnaire and regional inflammation using joint caliper measurements; the significance of intervention was evaluated using linear mixed models for repeated measures along with Bonferroni corrections. Results: After seven days of chronic topical administration, Delivra TM (DEL) formulations of ibuprofen and celecoxib generated serum levels of 2.9µg/mL and 220ng/mL and synovial fluid levels of 1.8 µg/mL and 203 ng/mL (respectively). In the canine model of acute inflammation, the overall treatment effects as well as the treatment by time interactions were strongly significant ( P <0.001) for both drugs. Oral ibuprofen proved uniquely effective at the earliest time point, while all ibuprofen formulations were effective at treating pain at 8.5 and 24.5 hours post-induction. Similarly, all celecoxib formulations (oral and topical) were equally effective at 8.5 and 24.5 hours post-induction. Conclusion: DEL formulations of ibuprofen and celecoxib successfully introduced these NSAIDs into synovial fluid at concentrations similar to those observed in circulation. Furthermore, these formulations reduced symptoms of pain associated with acute inflammation. Oral and transdermally delivered NSAIDs have similar pain relief effects; therefore, a replacement or combinatorial treatment may provide a more stable pain relief profile. In conclusion, this work supports further investigation of TD products in the treatment of regional inflammatory events. Keywords: osteoarthritis, ibuprofen, celecoxib, pain, canine model
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".