The Drug–Drug Interaction Profile of Presatovir
Bibliographic record
Abstract
Abstract Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infections in young children. Presatovir (previously GS‐5806) is a novel, orally administered RSV fusion inhibitor with a favorable safety profile and proven antiviral efficacy in preclinical and clinical studies. In vitro, presatovir is a substrate of the efflux transporters P‐glycoprotein (P‐gp) and breast cancer resistance protein (BCRP) and hepatic uptake transporters organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 and is slowly metabolized by cytochrome P450 (CYP) 3A4 and CYP3A5. This study enrolled 64 healthy subjects to evaluate the effect of cyclosporine, a P‐gp, BCRP, and OATP1B1/1B3 inhibitor; rifampin, a strong CYP3A4 and P‐gp inducer; efavirenz, a moderate CYP3A4 inducer; and cobicistat, a potent CYP3A inhibitor, on presatovir pharmacokinetics. Presatovir plasma exposures (maximum observed plasma concentration [Cmax] and area under the plasma concentration–time curve from time 0 extrapolated to infinity [AUCinf]) were not affected by coadministration of cyclosporine, suggesting presatovir is not a sensitive substrate of P‐gp, BCRP, or OATP1B1/1B3. As expected, based on the role of CYP3A in presatovir metabolism, presatovir exposure was increased by cobicistat (122% in AUCinf), and decreased by rifampin (40.3% in Cmax and 82.5% in AUCinf) and efavirenz (55.7% in AUCinf). These data support coadministration of presatovir with inhibitors of P‐gp, BCRP, OATP1B1/1B3, or CYP3A, but not with moderate or strong CYP3A4 inducers. Presatovir was well‐tolerated with the most common drug‐related adverse events of dizziness (n = 12) and somnolence (n = 4) reported during efavirenz treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.003 | 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".