Pharmacokinetics of Emtricitabine, Tenofovir, and GS-9137 Following Coadministration of Emtricitabine/Tenofovir Disoproxil Fumarate and Ritonavir-Boosted GS-9137
Bibliographic record
Abstract
OBJECTIVES: To evaluate the potential for clinically relevant drug-drug interaction between emtricitabine/tenofovir disoproxil fumarate (FTC/TDF) and the ritonavir-boosted HIV integrase inhibitor GS-9137 (GS-9137/r). METHODS: Healthy adults were administered FTC/TDF (200/300 mg once daily) for 7 days, followed by randomization to the order of receiving GS-9137/r (50/100 mg once daily) and GS-9137/r plus FTC/TDF in a crossover fashion under fed conditions for 10 days. Pharmacokinetic (PK) blood draws were performed on days 7, 17, and 27. Lack of PK alteration for FTC, tenofovir (TFV), and GS-9137 was defined as a 90% confidence interval (CI) for the estimated ratio of geometric least squares means (coadministration/alone) between 70% and 143% for the primary PK parameters: maximum observed plasma concentration (Cmax), area under the plasma concentration-time curve over dosing interval (AUCtau), and trough concentration (Ctau). RESULTS: Twenty-four of the 26 enrolled subjects completed the study with no serious adverse events or discontinuations attributable to adverse events. FTC, TFV, and GS-9137 PKs were unaffected during coadministration, with Cmax, AUCtau, and Ctau, meeting the protocol definition of equivalence and also the stricter bioequivalence criteria (90% CI: 80% to 125%). FTC and TFV PK parameters were comparable to historical values. CONCLUSION: There is no clinically relevant drug-drug interaction between FTC/TDF and GS-9137/r on their coadministration.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| 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".