Improved HPLC Method for Determination of Four PPIs, Omeprazole, Pantoprazole, Lansoprazole and Rabeprazole in Human Plasma
Bibliographic record
Abstract
PURPOSE: To develop a simple and rapid HPLC method for measuring of four proton-pump inhibitors (PPIs), omeprazole (OPZ), pantoprazole (PPZ), lansoprazole (LPZ) and rabeprazole (RPZ) concentrations in human plasma. METHODS: Following a single step liquid-liquid extraction analytes along with an internal standard (IS) were separated using an isocratic mobile phase of phosphate buffer (10 mM)/acetonitrile (53/47, v/v adjusted pH to 7.3 with triethylamine) at flow rate of 1 mL/min on reverse phase TRACER EXCEL 120 ODS-A column at room temperature. RESULTS: Total analytical run time for selected PPIs was 10 min. The assays exhibited good linearity (r(2)>0.99) over the studied range of 20 to 2500 ng/mL for OPZ, 20 to 4000 ng/mL for PPZ, 20 to 3000 ng/mL for LPZ and 20 to 1500 ng/mL for RPZ. The recovery of method was equal or greater than 80% and lower limit of quantification (LLOQ) was 20 ng/mL for four PPIs. Coefficient of variation and error at all of the intra-day and inter-day assessment were less than 9.2% for all compounds. CONCLUSIONS: The results indicated that this method is a simple, rapid, precise and accurate assay for determination of four PPIs concentrations in human plasma. This validated method is sensitive and reproducible enough to be used in pharmacokinetic studies and also is time- and cost-benefit when selected PPIs are desired to be analyzed.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".