The Pharmacokinetics of Fluticasone Furoate Given Intranasally in Healthy Subjects Using an Ultra-Sensitive Analytical Assay
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Purpose It has been previously shown that the complete pharmacokinetic profile, in particular the elimination phase, of intranasal fluticasone furoate has not been fully characterized due to the inability to quantify concentrations at low enough levels. This study was designed to evaluate the pharmacokinetic profile of intranasal FF using a validated, ultra-sensitive analytical method in healthy subjects. Methods This was an open-label, single-dose, two-period, one-treatment, crossover study. A dose of 880 µg fluticasone furoate was administered intra nasally. Blood samples for pharmacokinetic analysis were collected at 23 time points up to 36 h and analyzed for FF plasma levels using a lower limit of quantitation (LLOQ) of 0.1 pg/mL. Medical and adverse events (AE) were monitored throughout the study. Results Eighteen subjects were enrolled in and 17 completed the study. The results showed that all 17 subjects had measurable fluticasone furoate plasma concentrations at all time points with a clearly defined elimination phase, thus allowing estimation of AUCinf and t1/2. Median Tmax was 1.33 h (range=0.75–6.00), mean Cmax was 13.05±7.59 pg/mL, mean AUCt was 148.48±77.76 pg/mL*h, mean AUCinf was 279.07±187.81 pg/mL*h, and mean t1/2 was 31.67±29.23 h. In total 4 subjects (22.2%) experienced 4 AEs. Conclusion Using a lower LLOQ than what has been previously reported, a complete characterization of intranasal fluticasone furoate pharmacokinetics, including a clearly defined terminal elimination phase, was achieved. This method will allow for further investigations into the pharmacokinetics of fluticasone furoate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it