Anti-Inflammatory Activity of Ensifentrine: A Novel, Selective Dual Inhibitor of Phosphodiesterase 3 and Phosphodiesterase 4
Bibliographic record
Abstract
Ensifentrine is a novel, low-molecular-weight molecule that is a selective, dual inhibitor of phosphodiesterase (PDE)3 and PDE4. Inhibition of PDE3 has been shown to relax airway smooth muscle and inhibition of PDE4 to inhibit inflammatory responses and to stimulate the cystic fibrosis transmembrane conductance regulator in human airway epithelial cells through accumulation of intracellular cyclic adenosine monophosphate. Additionally, the dual inhibition of PDE3 and PDE4 demonstrates enhanced or synergistic effects compared with inhibition of either PDE3 or PDE4 alone on contraction of airway smooth muscle and suppression of inflammatory responses. Ensifentrine inhalation suspension 3 mg was recently approved in the USA for the maintenance treatment of chronic obstructive pulmonary disease in adult patients and is marketed under the trade name Ohtuvayre™. This manuscript describes further evidence that ensifentrine is a selective dual inhibitor of both human PDE3 and PDE4 enzymes and that this drug has significant anti-inflammatory activity in vivo in both allergic guinea pigs and non-human primates. This dual bronchodilator and anti-inflammatory activity of ensifentrine makes it a promising strategy as a novel inhaled "bifunctional" drug for the treatment of obstructive and inflammatory diseases of the respiratory tract. .
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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 | 0.000 |
| 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) | 0.001 | 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".