Effect of a Single Dose of Ritonavir on the Pharmacokinetic Behavior of Elvucitabine, a Nucleoside Reverse Transcriptase Inhibitor, Administered in Healthy Volunteers
Bibliographic record
Abstract
The purpose of this study was to determine the effect of a single dose of 300 mg of ritonavir on the plasma pharmacokinetics (PK) of a single dose of 20 mg of elvucitabine when the two drugs were coadministered in healthy subjects. In a three-way crossover design, 30 subjects received 20 mg of elvucitabine, 300 mg of ritonavir, or 20 mg of elvucitabine coadministered with 300 mg of ritonavir. Elvucitabine concentrations were analyzed using a validated liquid chromatography-tandem mass spectrometry assay. The PK of elvucitabine was determined using both noncompartmental and compartmental analyses. Models were developed and tested using ADAPT-II, while a population analysis was performed using IT2S. Comparisons of PK parameters between groups were done with SAS. The pharmacokinetic behavior of elvucitabine was best described by a two-compartment linear model using two absorption rates and a first-order elimination rate. Ritonavir significantly impacted the PK of elvucitabine by reducing elvucitabine's bioavailability, with the most plausible explanation being an inhibition on influx transporters by ritonavir. The decrease in elvucitabine bioavailability when elvucitabine was coadministered with ritonavir may be due to ritonavir's inhibiting influx gut transporters. Continued development of elvucitabine is warranted to better characterize its PK and to determine its in vivo efficacy against human immunodeficiency virus.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".