Validation of a green and sensitive spectrofluorimetric method for determination of Bilastine and its application to pharmaceutical preparations, content uniformity test, and spiked human plasma
Bibliographic record
Abstract
Abstract Bilastine (BIL) is a new second-generation antihistaminic drug used for the management of urticaria and rhino-conjunctivitis symptoms. Herein, a spectrofluorimetric method for determining BIL is described. The method is very sensitive, simple, quick, and green. The suggested method depended on the measurement of the original fluorescence of BIL in 1.0 M sulfuric acid at an emission wavelength of 385 nm after an excitation at 272 nm. The method was evaluated by the International Council on Harmonization (ICH) requirements. The relationship between BIL concentrations and the fluorescence intensities was linear in a range of 10.0–500.0 ng mL− 1, and the correlation coefficient was 0.9999. The detection limit was 2.9 ng mL− 1 and the quantitation limit was 8.8 ng mL− 1. The suitable sensitivity and selectivity of the suggested method enabled its application successfully in analyzing BIL in pharmaceutical tablets without any interfering effect from their excipients and in spiked human plasma with appropriate recoveries from 95.72 to 97.24%. Additionally, the suggested method was utilized for content uniformity testing.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".