Physicochemical, in vitro and in vivo evaluation of flurbiprofen microemulsion
Bibliographic record
Abstract
Flurbiprofen, a potent nonsteroidal anti-inflammatory drug, is widely used for relief of pain in patients suffering from rheumatic diseases, migraine, sore throat and primary dysmenorrheal. However, this drug has many gastrointestinal side effects produced by its oral administration, such as gastric bleeding and peptic ulcer. These effects were responsible for non-compliance among patients, which ultimately results in treatment failure. The physicochemical properties of flurbiprofen, make it a suitable candidate for transdermal drug delivery, which can overcome the drawbacks of oral administration. In this sense, microemulsions have been proved to increase the cutaneous absorption of lipophilic drugs when compared to conventional drug delivery systems. The purpose of this study was to formulate and characterize gel based microemulsions, for topical delivery of flurbiprofen. Different gel bases, containing microemulsion and hydro-alcoholic solution of flurbiprofen, were developed and compared. In vitro study showed that gels containing microemulsion had a higher permeation rate than those containing hydro-alcoholic solutions. Additionally, formulation of Carbopol-I (microemulsion) showed higher percent of inhibition of inflammation than others bases. Further, skin irritation study demonstrated that Carbopol-I was none irritating. Flurbiprofen microemulsion incorporated on Carbopol-I showed physicochemical, in vitro and in vivo characteristics suitable for the development of alternative transdermal delivery formulation.
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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".