Determination of Clobazam and Its Major Metabolite N-desmethylclobazam in Human Plasma with High-Performance Liquid Chromatography
Bibliographic record
Abstract
Clobazam (CLB) is a benzodiazepine that is used in many types of epilepsy. Although therapeutic drug monitoring (TDM) of CLB is not routine, there is evidence that TDM may be of value in conditions where pharmacokinetic alterations are suspected. Therefore, determination of both CLB and its active metabolite concentrations is essential for TDM. Herein, we present a simple and practical method for determination of CLB and N-desmethylclobazam (NDMCLB) in human plasma by high-performance liquid chromatography (HPLC). The drugs were extracted by hexane:dichloromethane (1:1, v/v) from 0.3 mL plasma. The separation was carried out with a C18 reverse phase column using a mobile phase of water:acetonitrile (57:43, v/v) pumped at 0.8 mL/min. The analytes were detected at 228 nm. The method was linear over the concentration range 20–500 ng/mL for CLB and 200–3000 ng/mL for NDMCLB. The intra-day coefficient of variation (CV) was <10% for CLB and <6% for NDMCLB, while the inter-day CV for CLB was <16%. The metabolite inter-day CV was <6%. The accuracy of intra- and inter-day assessments determined for CLB and NDMCLB was within ±10%. This paper describes a rapid, reliable, and simple method for measuring CLB and its metabolite NDMCLB in human plasma. This UV-HPLC procedure offers acceptable precision and accuracy to quantify CLB and its metabolite in human plasma.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".