Population Pharmacokinetics of Fentanyl in Healthy Volunteers
Bibliographic record
Abstract
The authors compared the population pharmacokinetics of fentanyl using a standard individualized modeling (SIM) approach versus that of a nonparametric expectation maximization (NPEM) approach. The pharmacokinetic properties of fentanyl administered as a single 5 ug/kg intravenous infusion were evaluated in 18 healthy volunteers by use of SIM as well as with NPEM. NPEM-derived parameters were a total body clearance of 2.12 +/- 0.28 L/kg/h, distributional clearance of 8.43 +/- 4.58 L/kg/h, central volume of distribution of 1.22 +/- 0.21 L/kg, and peripheral volume of distribution of 1.81 +/- 1.47 L/kg. Identified parameter values from the modeling methods resulted in virtually identical simulated profiles; this finding was confirmed when median values noted were not statistically significantly different between modeling methods (SIM or NPEM). However, the NPEM algorithm uniquely identified a greater distributional clearance in the elderly population and also illustrated a profile with at least 10% of the study population having a very high clearance of fentanyl. This finding may affect the therapeutic use of fentanyl. NPEM allows for a more informative global representation of a drug's pharmacokinetics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".