High-Performance Liquid Chromatographic Determination of Memantine in Human Urine Following Solid-Phase Extraction and Precolumn Derivatization
Bibliographic record
Abstract
A validated HPLC-UV method is presented for the quantification of urinary memantine hydrochloride, a novel medication approved to treat moderate and advanced cases of Alzheimer's disease. The drug and amantadine hydrochloride, the internal standard, were extracted from human urine using SPE. The extract was then buffered and derivatized at room temperature using o-phthalaldehyde in the presence of N-acetyl-L-cyteine. Chromatographic separation of the formed derivatives was achieved on a C18 column using methanol-water mobile phase adjusted to pH 7 and pumped isocratically at 1 mL/min. The UV detector was set at 340 nm. The chromatographic run time did not exceed 10 min. The LOD and LOQ were 8 and 20 ng/mL, respectively. The RSDs for intraday and interday precisions did not exceed 5.5%. The method was used to monitor memantine hydrochloride in human urine in order to determine an appropriate sampling interval for future noninvasive therapeutic drug monitoring. The assay could also be applied to the determination of amantadine. The described assay showed that a postdosing time interval of 25-75 h seems adequate for sampling and monitoring memantine in urine.
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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) | 0.001 | 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 | 0.000 |
| 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".