Drugs targeting novel pathways in pulmonary arterial hypertension
Bibliographic record
Abstract
Over the past three decades, several drugs have been developed to target three major dysfunctional pathways in pulmonary arterial hypertension (PAH), including the prostacyclin, endothelin and nitric oxide pathways. Despite these advances, PAH remains incurable, necessitating further drug discovery efforts. New therapies focus on previously untargeted pathways, especially the bone morphogenetic protein (BMP)/transforming growth factor (TGF)-β signalling pathway. Dysregulation of this pathway, involving the Smad2/3 and Smad1/5/8 signalling branches, plays a key role in pulmonary vascular remodelling. Sotatercept, a fusion protein acting as an activin receptor ligand trap to rebalance growth-promoting and growth-inhibiting signalling has shown promise in clinical trials by reducing pulmonary vascular resistance, improving exercise capacity and lowering risk of a composite of morbi-mortality events. Other emerging treatments aim to restore balance within the BMP/TGF-β pathway. Therapies targeting receptor tyrosine kinases (RTKs), such as imatinib, inhibit the platelet-derived growth factor pathway. Though oral imatinib has shown efficacy, its side-effects have limited widespread use. Additional strategies exploring lower doses of imatinib and novel delivery methods, such as inhalation, to reduce systemic side-effects failed to demonstrate clinical benefit. Novel RTK inhibitors such as seralutinib administered by inhalation have shown promising results in a phase 2 clinical trial. Other emerging approaches include anti-inflammatory therapies, hormonal modulation and metabolism-targeting agents like ranolazine and sodium-glucose cotransporter 2 inhibitors, which could expand the therapeutic landscape for PAH. Overall, the continued development of novel drugs targeting these pathways offers hope for better disease management and improved outcomes for patients with PAH.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".