Application of capillary zone electrophoresis with indirect UV detection to the determination of a model drug, vigabatrin, in dosage forms.
Bibliographic record
Abstract
PURPOSE: Vigabatrin, an anti-epileptic drug with poor UV absorptivity, is used as a model drug to investigate parameters affecting quantitative determination of cationic drugs using capillary zone electrophoresis with indirect UV detection. METHODS: All experiments were performed on a HP 3D CE instrument equipped with an on-column diode array UV absorbance detector. Untreated fused silica capillaries with an inner diameter of 50 microm, an outer diameter of 365 microm, and a total length of 50 cm (41.5 cm to the detector) were used. Indirect UV detection was performed at 214 nm. Operational parameters such as buffer type and concentration, its pH, probe type and concentration, and the impact of co-ions on the efficiency of separation, were studied. Sabrilex sachets and Sabril tablets were subjected to analysis in this study. RESULTS: Optimal separation and quantification of vigabatrin was obtained using 5 mM sodium phosphate buffer containing 5 mM benzyl tri-ethyl ammonium hydroxide (BTEA) at pH 2.2, with 8-aminocaprylic acid as the internal standard. The method was linear over a range of 5-150 microg/ml (r = 0.9911) and a wider range of 100-600 microg/ml (r = 0.9937) concentration of the drug. The relative standard deviation (RSD) of migration time for 10 consecutive injections of a standard solution of vigabatrin was 0.19%. The limit of quantification (LOQ) was 5 microg/ml. CONCLUSIONS: The method was demonstrated for quantification of vigabatrin in both tablet and sachet dosage forms and proved to be a very specific and fast (8 min) means of routine analysis of the drug in dosage forms, in assay or dissolution 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".