Pharmacokinetic and pharmacodynamic features of dapoxetine, a novel drug for ‘on‐demand’ treatment of premature ejaculation
Bibliographic record
Abstract
Associate Editor Michael G. Wyllie Editorial Board Ian Eardley, UK Jean Fourcroy, USA Sidney Glina, Brazil Julia Heiman, USA Chris McMahon, Australia Bob Millar, UK Alvaro Morales, Canada Michael Perelman, USA Marcel Waldinger, Netherlands OBJECTIVE To describe the relationship between the pharmacokinetic and pharmacodynamic properties of dapoxetine, a drug specifically developed for treating premature ejaculation (PE). METHODS Data from various stages of the clinical development programme were analysed using validated methods for assessing ejaculatory latency. The clinical characteristics were then compared with the pharmacokinetic profile, determined from measured plasma drug concentrations. RESULTS Pharmacodynamic and pharmacokinetic measurements confirm that ‘on demand’ dapoxetine has a rapid onset of action and is rapidly cleared after sexual intercourse. CONCLUSION Dapoxetine may represent the first of a new category of selective serotonin transport inhibitors. Although dapoxetine has pharmacological similarities to other selective serotonin transport inhibitors, its efficacy after acute administration sets it apart and suggests a different mode of action. Its physicochemical and pharmacokinetic properties and its clinical efficacy make dapoxetine suitable for on‐demand treatment of PE.
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 | 0.002 |
| 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".