Pharmacokinetic Profile of Temsirolimus With Concomitant Administration of Cytochrome P450‐Inducing Medications<sup>1</sup>
Bibliographic record
Abstract
Temsirolimus is a novel inhibitor of the mammalian target of rapamycin, with antitumor activity in advanced tumors. Because temsirolimus and its metabolite, sirolimus, are cytochrome P450 (CYP) 3A4/5 substrates, the potential exists for interaction with drugs that induce CYP3A activity, including enzyme inducers and rifampin. Cancer patients received once-weekly intravenous (IV) 220 mg/m(2) temsirolimus with or without enzyme inducers. Coadministration with enzyme inducers decreased temsirolimus maximum plasma concentration (C(max)) by 36% and increased volume of distribution by 99%. Sirolimus C(max) and area under the concentration-time curve (AUC) were decreased by 67% and 43%, respectively. In healthy adult subjects, coadministration of 25-mg intravenous temsirolimus with rifampin had no significant effect on temsirolimus C(max) and AUC but decreased sirolimus C(max) and AUC by 65% and 56%, respectively. Rifampin decreased AUC(sum) by 41%. Temsirolimus was well tolerated in both studies. If concomitant agents with CYP3A induction potential are used, higher temsirolimus doses may be needed to achieve adequate tumor tissue drug levels.
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 | 0.000 | 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 | 0.001 |
| 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".